ConnectSoft Audit Trail Platform – 30-Cycle Development Plan¶

Introduction¶

The ConnectSoft Audit Trail Platform (ATP) is a core foundation of the ConnectSoft SaaS ecosystem. Its purpose is to provide enterprise-grade auditability, traceability, and compliance across every ConnectSoft-built or integrated product.

ATP is architected as a distributed suite of bounded-context microservices, each owning a clearly defined part of the domain and communicating through event-driven patterns. Together, these services deliver a cohesive capability for:

Immutable audit record ingestion and storage
High-performance querying and search
Cryptographic integrity verification and tamper evidence
Automated data retention, export, and policy enforcement
Regulatory overlays for SOC 2, GDPR, and HIPAA
Observability, cost efficiency, and extensibility through a standardized microservice foundation

Each microservice is generated and evolved using the ConnectSoft Microservice Template, which encapsulates all cross-cutting concerns, including:

REST + gRPC endpoints
MassTransit / Azure Service Bus integration
NHibernate persistence
Distributed caching
OpenTelemetry traces, metrics, and logs
Swagger / OpenAPI documentation
Health checks, feature flags, and configuration management
Centralized security (RBAC + ABAC) and tenant isolation
Continuous Delivery pipelines with quality gates

Purpose of This Plan¶

This document defines the 30-cycle development roadmap for the Audit Trail Platform — from architectural foundation to compliance maturity and AI-driven evolution.

Each cycle represents a cohesive engineering milestone that can be planned, tracked, and delivered through Azure DevOps. Cycles are structured as Epics, each decomposed into Features and Tasks with clear deliverables and acceptance criteria.

The roadmap is intentionally iterative:

Foundation — architecture, CI/CD, shared frameworks, and tenant infrastructure.
Domain Implementation — development of core microservices: Ingestion, Query, Integrity, Export, Policy, Search, and Gateway.
Operational Excellence — observability, security, compliance overlays, and chaos validation.
Productization — SDKs, UI consoles, documentation, and AI-based insights.

Objectives¶

Deliver a tamper-evident, multi-tenant audit trail aligned with ConnectSoft’s SaaS governance standards.
Provide API-first, event-driven interfaces for all platform and external consumers.
Achieve operational transparency through full observability and compliance metrics.
Ensure extensibility so new SaaS products can seamlessly plug into the audit ecosystem.
Embed security and compliance by design, not as post-hoc controls.

Scope¶

This plan covers the end-to-end engineering effort across all Audit Trail bounded contexts, including:

Layer	Responsibility	Output
Core Services	Audit Ingestion, Query, Integrity, Export, Policy, Search	APIs, events, domain models
Cross-Cutting	Identity, Security, Telemetry, Gateway, Rate Limiting	Reusable shared libraries and templates
DevOps & Ops	Pipelines, IaC, Monitoring, Runbooks	Automated build & deployment system
Governance	Compliance, Retention, Cost Analytics, AI Insights	Certified controls and continuous improvement

Deliverables¶

Complete architecture blueprint with service boundaries, contracts, and message flows.
30 fully versioned Azure DevOps Epics, each with Features and Tasks.
Multi-service source repositories, each generated from the microservice template.
Automated pipelines for build, test, release, and observability.
Operational runbooks and dashboards for live monitoring and troubleshooting.
Final compliance certification artifacts and evidence reports.

Outcomes¶

By the end of the 30-cycle roadmap, the ConnectSoft Audit Trail Platform will:

Provide immutable, verifiable audit records for every tenant and domain event.
Offer centralized APIs and exports for compliance teams and automated systems.
Deliver high availability, observability, and cost efficiency through cloud-native design.
Enable AI-powered insights for anomaly detection and predictive compliance.
Serve as a reference architecture for other ConnectSoft SaaS microservice ecosystems.

Epic `AUD-ARC-001` : Platform Architecture & Vision¶

Epic Description¶

This epic defines the architectural foundation, vision, and standards for the Audit Trail Platform (ATP). It establishes the high-level architecture, bounded contexts, coding standards, repository model, and governance framework that will guide every subsequent microservice implementation.

ATP will consist of multiple bounded-context microservices — each generated from the ConnectSoft Microservice Template — that together enable a distributed, tamper-evident audit trail solution. This first cycle sets the direction and produces the core documentation, diagrams, and initial reference implementation.

Epic Objectives¶

Define the Audit Trail Platform architecture and integration strategy across ConnectSoft’s SaaS ecosystem.
Establish DDD boundaries and aggregates for each microservice.
Enforce standardization of project structure, naming conventions, and DevOps processes.
Validate the ConnectSoft Microservice Template as the baseline for all services.
Approve governance principles and documentation standards for long-term consistency.

Features¶

Feature `AUD-ARC-HLD-001` – High-Level Architecture Blueprint¶

Feature Description Deliver the end-to-end architecture of the Audit Trail Platform, including context, containers, components, and communication protocols. The architecture must define system interactions, technology stack, deployment topology, and integration points (Identity, Configuration, Usage, Notification, Compliance, etc.).

Tasks¶

Task AUD-ARC-HLD-T001 – Define Global Architecture Diagram (C4 Level 1–3)

Create C4 diagrams representing:
- Level 1: System Context — how ATP integrates within ConnectSoft SaaS.
- Level 2: Containers — microservices, databases, event bus, and gateways.
- Level 3: Components — internal modules per service (API, Domain, Infra, Persistence).
Tools: [Structurizr DSL] or [Mermaid C4].
Deliverables: /docs/hld/audit-trail-architecture-c4.md and exported PNG diagrams.
✅ Acceptance Criteria
- Architecture reviewed and approved by CTO and Architecture Board.
- All levels rendered and published in MkDocs under /architecture/.

Task AUD-ARC-HLD-T002 – Define Communication Model and Integration Patterns

Describe how services communicate: REST, gRPC, asynchronous events (MassTransit/Azure Service Bus).
Specify reliability, retry, and idempotency patterns.
Define event contracts between core services (e.g., audit.record.appended, export.job.completed).
✅ Acceptance Criteria
- Communication table documented in /docs/contracts/communication-model.md.
- Integration patterns approved and reused across templates.

Task AUD-ARC-HLD-T003 – Identify Shared Infrastructure Components

List core shared services:
- API Gateway
- Service Bus
- Configuration & Feature Flags
- Identity & Authorization
- Observability Stack (Grafana, Prometheus, Jaeger, Seq)
Define network topology (Azure Container Apps or AKS).
✅ Acceptance Criteria
- Shared component inventory documented and assigned owners.
- Network flow diagram validated by Cloud Architecture team.

Task AUD-ARC-HLD-T004 – Publish High-Level Design (HLD) Document

Consolidate all diagrams, integration flows, and decisions.
Create /docs/hld/hld-overview.md in repository.
Reference architectural principles, context, and major technology choices.
✅ Acceptance Criteria
- HLD published and linked from project homepage.
- Versioned tag created (hld-v1.0) for traceability.

Feature `AUD-ARC-DDD-001` – Domain Model & Context Map¶

Feature Description Define the domain structure of ATP using DDD. Identify all bounded contexts (microservices), aggregates, entities, and ubiquitous language. This will ensure business and technical alignment and prevent model duplication across services.

Tasks¶

Task AUD-ARC-DDD-T001 – Identify Bounded Contexts and Ownership

Define all core microservices:
- Audit.IngestionService
- Audit.StorageService
- Audit.QueryService
- Audit.IntegrityService
- Audit.ExportService
- Audit.PolicyService
- Audit.SearchService
- Audit.GatewayService
- Audit.AdminService
- Audit.ComplianceService
Assign each context a domain owner, repository, and integration type (ACL/Conformist).
✅ Acceptance Criteria
- Context map published as diagram and table in /docs/domain/context-map.md.
- Each context labeled with upstream/downstream dependencies.

Task AUD-ARC-DDD-T002 – Model Aggregates, Entities & Value Objects

Define main aggregates:
- AuditStream (root for logical audit chain)
- AuditRecord (immutable event)
- IntegrityBlock (hash-chain structure)
- ExportJob (asynchronous operation tracking)
- RetentionPolicy (lifecycle rules)
Specify invariants and domain rules per aggregate.
✅ Acceptance Criteria
- Aggregates documented under /docs/domain/aggregates.md.
- Diagrams generated using Mermaid UML syntax.

Task AUD-ARC-DDD-T003 – Define Domain Events and Contracts

Define core event schemas with JSON structure and naming conventions.
Create early schema definitions for future Schema Registry.
✅ Acceptance Criteria
- Event list (audit.record.appended, audit.policy.applied, etc.) documented.
- Sample payloads validated in CI.

Task AUD-ARC-DDD-T004 – Publish Domain Glossary and Ubiquitous Language

Compile glossary terms (Actor, Tenant, Stream, Record, Checksum, etc.).
Ensure consistent terminology across documentation and code.
✅ Acceptance Criteria
- Glossary approved and committed in /docs/domain/glossary.md.

Feature `AUD-ARC-STD-001` – Coding & Repository Standards¶

Feature Description Define uniform coding practices, project layout, and DevOps conventions to ensure all microservices follow identical structure, naming, and quality expectations.

Tasks¶

Task AUD-ARC-STD-T001 – Prepare Repository Structure and Templates

Define standard repo structure:
- /src – Application, Domain, Infrastructure layers
- /tests – Unit, Integration, Acceptance tests
- /docs – Markdown-based documentation
- /build – CI/CD pipelines
Configure template .editorconfig, .gitignore, and solution scaffolding.
✅ Acceptance Criteria
- Repository created and cloned from template.
- Verified via automated “Template Validation” pipeline.

Task AUD-ARC-STD-T002 – Define Naming Conventions

Specify naming for repos, namespaces, projects, and pipelines:
- ConnectSoft.Audit.[Context].Service
- ConnectSoft.Audit.[Context].Tests
Document convention in /docs/standards/naming.md.
✅ Acceptance Criteria
- Naming rules enforced through linter and PR checklist.

Task AUD-ARC-STD-T003 – Publish Branching & Versioning Strategy

Adopt hybrid GitFlow + Trunk-Based approach.
Define branch policies: main, develop, feature/*, release/*, hotfix/*.
Specify semantic versioning rules (vX.Y.Z).
✅ Acceptance Criteria
- Azure Repos branch policies configured.
- Documentation /docs/devops/branching-strategy.md approved.

Task AUD-ARC-STD-T004 – Implement Code Style and Analyzers

Integrate StyleCop, Roslyn analyzers, and code quality ruleset.
Add pre-commit linting hook.
✅ Acceptance Criteria
- All template builds pass dotnet format check.
- CI fails if style violations exceed threshold.

Task AUD-ARC-STD-T005 – Create Repository Contribution Guidelines

Add README.md, CONTRIBUTING.md, and PR template.
✅ Acceptance Criteria
- PR template live and in use for all ATP repos.

Feature `AUD-ARC-GOV-001` – Architecture Governance & Principles¶

Feature Description Define the guiding principles and governance workflow that ensure architectural consistency, quality, and security across all ATP services.

Tasks¶

Task AUD-ARC-GOV-T001 – Define Architectural Principles

Document core principles:
- Security by Design
- API First
- Immutability and Idempotency
- Observability Everywhere
- Tenant Isolation
- ✅ Acceptance Criteria
  - Principles reviewed and approved by Architecture Board.

Task AUD-ARC-GOV-T002 – Create Architecture Decision Record (ADR) Process

Set up /docs/adrs folder.
Provide ADR template (Context → Decision → Consequences).
✅ Acceptance Criteria
- ADR #001 (“Architecture Decision Process”) published.

Task AUD-ARC-GOV-T003 – Define Service Versioning and Deprecation Rules

Establish policy for API versioning (URL-based or header-based).
Define deprecation lifecycle (announcement → sunset).
✅ Acceptance Criteria
- Policy published in /docs/standards/versioning-policy.md.

Feature `AUD-ARC-REF-001` – Reference Microservice Initialization¶

Feature Description Bootstrap the first microservice (Audit.IngestionService) from the ConnectSoft Microservice Template to validate the architecture, CI/CD, and template readiness.

Tasks¶

Task AUD-ARC-REF-T001 – Scaffold Reference Microservice

Command:

dotnet new connectsoft-microservice -n ConnectSoft.Audit.IngestionService

* Verify generated structure matches ATP coding standards. * ✅ Acceptance Criteria * Build successful locally and in pipeline.

Task AUD-ARC-REF-T002 – Configure Initial Dependencies

Register health checks, Serilog, OpenTelemetry, NHibernate, and MassTransit.
✅ Acceptance Criteria
- Service starts and exposes /healthz endpoint.

Task AUD-ARC-REF-T003 – Deploy to Dev Environment

Setup Azure DevOps pipeline with build/test/deploy stages.
Deploy to ACA or AKS Dev namespace.
✅ Acceptance Criteria
- Successful deployment confirmed in Dev environment.
- Logs visible in Grafana/Seq dashboard.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of AUD-ARC-001

Approved High-Level Architecture Blueprint with C4 diagrams.
Completed Domain Context Map with aggregates and events.
Published Coding & Repository Standards and branch model.
Established Architecture Governance and ADR process.
Reference microservice (Audit.IngestionService) scaffolded and successfully deployed.
All artifacts committed under /docs/ and visible in MkDocs portal.

Epic `AUD-OPS-001` : DevOps & CI/CD Foundation¶

Epic Description¶

This epic delivers the end-to-end DevOps and automation foundation for the Audit Trail Platform (ATP). It establishes standardized continuous integration (CI), continuous delivery (CD), and Infrastructure as Code (IaC) pipelines that all ATP microservices will inherit. The goal is to ensure consistent, secure, and repeatable deployments across all environments — Dev, QA, Stage, and Prod — with traceable artifacts and integrated quality gates.

Epic Objectives¶

Implement a unified CI/CD pipeline template for all microservices generated from the ConnectSoft Microservice Template.
Define and enforce security, quality, and compliance gates in every build.
Provision environment infrastructure automatically using Bicep or Pulumi modules.
Establish artifact promotion pipelines for Dev → Stage → Prod.
Integrate observability hooks (build metrics, deployment traces, and audit logs).

Features¶

Feature `AUD-OPS-CI-001` – Continuous Integration (CI) Pipelines¶

Feature Description Create reusable Azure DevOps CI templates that compile, test, and validate each microservice. Pipelines will include unit tests, static code analysis, dependency scanning, and artifact publication.

Tasks¶

Task AUD-OPS-CI-T001 – Create Unified Azure DevOps Pipeline Templates

Build YAML-based templates for .NET 8 microservices using ConnectSoft conventions.
Define CI stages: build, test, analyze, and publish.
Include caching, artifact retention, and version tagging.
✅ Acceptance Criteria
- All generated services build successfully using shared templates.
- Artifacts (.nupkg, .zip, .docker) published to Azure Artifacts/Container Registry.
- Pipeline stored under /build/ci/ci-template.yml.

Task AUD-OPS-CI-T002 – Configure Quality Gates & Security Scanning

Integrate tools:
- CodeQL for static analysis
- SonarQube for code coverage and quality metrics
- Trivy or Snyk for dependency vulnerability scanning
Enforce build failure if thresholds not met.
✅ Acceptance Criteria
- Quality gate reports visible in Azure DevOps dashboard.
- Pipelines block merge on failed code-quality checks.
- Scan results archived under /reports/security/.

Task AUD-OPS-CI-T003 – Automate Test Execution & Coverage Reporting

Run unit, integration, and acceptance tests automatically per commit.
Generate test coverage using coverlet and export results to SonarQube.
✅ Acceptance Criteria
- Code coverage ≥ 80% enforced by CI policy.
- Test results viewable in Azure DevOps Test tab.

Task AUD-OPS-CI-T004 – Publish Build Artifacts to Central Registry

Push build outputs (containers, binaries, docs) to:
- Azure Container Registry (ACR)
- Azure Artifacts feed (for shared NuGets)
✅ Acceptance Criteria
- Build artifacts traceable by version and commit SHA.
- Re-deployments reproducible from artifacts alone.

Feature `AUD-OPS-CD-001` – Continuous Delivery (CD) Environments¶

Feature Description Define automated deployment pipelines using the ConnectSoft standard release flow. Include environment segregation, approval gates, and rollback strategies.

Tasks¶

Task AUD-OPS-CD-T001 – Define Environment Deployment Stages

Create release stages: Dev → QA → Stage → Prod.
Automate deployments with Helm/Bicep manifests and environment variables.
✅ Acceptance Criteria
- Each environment deploys from pipeline YAML using parameterized templates.
- Deployment history logged with build IDs and timestamps.

Task AUD-OPS-CD-T002 – Implement Approval Gates & Rollback Policies

Require manual approval for Stage and Prod promotions.
Configure automatic rollback on deployment failure or health check timeout.
✅ Acceptance Criteria
- Manual approvals visible in DevOps release flow.
- Rollback restores previous stable artifact.

Task AUD-OPS-CD-T003 – Add Post-Deployment Validation (Smoke Tests)

Execute REST and gRPC smoke tests after each deployment.
Validate health checks, Swagger endpoints, and OpenTelemetry connectivity.
✅ Acceptance Criteria
- Post-deployment checks must pass for environment promotion.

Task AUD-OPS-CD-T004 – Enable Artifact Promotion Across Environments

Implement release pipeline linking Dev → Stage → Prod.
Promote container images and build artifacts based on successful validation.
✅ Acceptance Criteria
- Artifact promotion automated without rebuild.
- Traceability maintained via build number and tag.

Feature `AUD-OPS-IAC-001` – Infrastructure as Code (IaC)¶

Feature Description Provision and manage all environment infrastructure using declarative IaC templates. Ensure reproducible deployments with environment parity and secure parameterization.

Tasks¶

Task AUD-OPS-IAC-T001 – Develop Core Bicep/Pulumi Modules

Create reusable modules for:
- Virtual Network / Container Environment (ACA/AKS)
- Azure SQL / PostgreSQL
- Azure Service Bus
- Azure Key Vault
- Application Insights / Log Analytics
✅ Acceptance Criteria
- All modules deployed successfully in Dev environment.
- Configuration parameterized per tenant and environment.

Task AUD-OPS-IAC-T002 – Configure Secrets and Key Vault Integration

Use Azure Key Vault for storing connection strings and credentials.
Implement managed identity-based access for services.
✅ Acceptance Criteria
- All secrets removed from YAMLs and configuration files.
- Key Vault references resolved during deployment.

Task AUD-OPS-IAC-T003 – Provision Base Environments

Deploy shared infrastructure:
- API Gateway, Service Bus, Storage, Observability stack.
- Resource groups created via pipeline automation.
✅ Acceptance Criteria
- Dev, QA, Stage, and Prod environments provisioned.
- Output variables published for downstream pipeline use.

Task AUD-OPS-IAC-T004 – Implement Configuration Drift Detection

Integrate IaC validation step comparing deployed resources vs Git definitions.
Notify via Teams/Slack if drift detected.
✅ Acceptance Criteria
- Drift detection pipeline functional and alerting configured.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-OPS-001:

Reusable CI/CD templates committed under /build/.
Security and quality gates active across all microservices.
Automated environment deployments for Dev → Stage → Prod.
Key Vault–based secret management and IaC drift detection operational.
DevOps dashboards showing build, test, and release analytics.

Epic `AUD-TENANT-001` : Tenant & Edition Management Microservice¶

Epic Description¶

This epic delivers the Tenant & Edition Management Microservice, responsible for representing tenants, their assigned editions, and activated feature sets within the Audit Trail Platform (ATP). It ensures that every tenant is properly onboarded, isolated, and configured according to licensing and compliance rules. The service exposes APIs for tenant CRUD operations, onboarding workflows, edition assignment, and lifecycle events, and integrates with the Identity Service for authentication and claim propagation.

Epic Objectives¶

Implement the domain model for tenants, editions, and feature sets.
Expose REST/gRPC APIs for tenant creation, updates, activation, and offboarding.
Provide automated onboarding workflows for new SaaS customers.
Support tenant-specific configuration caching and context propagation across ATP microservices.
Publish tenant lifecycle events to the event bus for other services (e.g., Ingestion, Policy, Export).
Integrate with Identity Service for federated user/tenant linkage and role propagation.

Features¶

Feature `AUD-TENANT-DOM-001` – Tenant/Edition Domain Model¶

Feature Description Design and implement the domain model that represents a tenant’s structure, edition type, feature entitlements, and associated metadata. Ensure alignment with DDD practices and cross-service consistency.

Tasks¶

Task AUD-TENANT-DOM-T001 – Model Tenant, Edition, and FeatureSet Aggregates

Create aggregates and entities:
- Tenant (root)
- Edition (value object or entity linked to tenant)
- FeatureSet (collection of enabled platform features)
Define invariants:
- Tenant ID must be globally unique.
- Edition must correspond to predefined tiers (Free, Standard, Enterprise).
Map persistence using NHibernate with tenant-scoped tables.
✅ Acceptance Criteria
- Domain classes implemented and covered by unit tests.
- Database schema generated successfully via migrations.
- Tenant and Edition entities validated with test data.

Task AUD-TENANT-DOM-T002 – Implement Aggregate Invariants and Events

Add domain events:
- tenant.created
- tenant.updated
- edition.changed
Validate edition upgrade/downgrade rules through domain services.
✅ Acceptance Criteria
- Domain event handlers successfully publish messages to the bus.
- Business rules enforced by domain layer tests.

Feature `AUD-TENANT-API-001` – CRUD & Onboarding APIs¶

Feature Description Expose REST and gRPC endpoints to manage tenants and their editions. APIs must follow ConnectSoft conventions, include proper validation, and support automation workflows for new tenant creation.

Tasks¶

Task AUD-TENANT-API-T001 – Implement Tenant CRUD Endpoints

Endpoints:
- POST /api/tenants
- GET /api/tenants/{id}
- PUT /api/tenants/{id}
- DELETE /api/tenants/{id}
Implement validation filters (unique name, domain).
Add pagination for listing tenants.
✅ Acceptance Criteria
- CRUD endpoints functional with 100% integration test coverage.
- Swagger documentation generated automatically.

Task AUD-TENANT-API-T002 – Implement Onboarding Workflow

Orchestrate workflow:
- Validate input data.
- Create tenant → assign edition → generate default feature set.
- Send welcome / configuration email or webhook.
Integrate background job processor (Hangfire or Azure Functions).
✅ Acceptance Criteria
- Onboarding flow completes end-to-end via REST API.
- Tenants automatically activated post-creation.

Task AUD-TENANT-API-T003 – Add Tenant Context Middleware

Implement middleware that:
- Resolves TenantId from headers or JWT claims.
- Populates ITenantContext in request pipeline.
✅ Acceptance Criteria
- Tenant context available across controllers, gRPC services, and MassTransit consumers.
- Unit tests confirm tenant resolution in all entry points.

Task AUD-TENANT-API-T004 – Add Per-Tenant Configuration Caching

Cache frequently accessed configuration (edition, features, limits).
Use distributed cache (Redis / MemoryStore).
Implement cache invalidation upon edition change.
✅ Acceptance Criteria
- Tenant configuration cache hit rate ≥ 90%.
- Changes reflected within < 5 seconds after update.

Feature `AUD-TENANT-INT-001` – Integration with Identity Service¶

Feature Description Integrate with the ConnectSoft Identity microservice to synchronize tenant identities and enforce authentication/authorization boundaries.

Tasks¶

Task AUD-TENANT-INT-T001 – Link Tenants with Identity Service

Upon tenant creation, call Identity API to register tenant realm/organization.
Store returned identity realm ID in tenant entity.
✅ Acceptance Criteria
- Identity realm created automatically during onboarding.
- Cross-service correlation IDs consistent in both systems.

Task AUD-TENANT-INT-T002 – Propagate Claims and Roles

Extend JWT claims to include tenant_id, edition, feature_flags.
Update middleware to enforce tenant-based authorization.
✅ Acceptance Criteria
- Access control verified by integration tests.
- Tokens carry all required tenant attributes.

Task AUD-TENANT-INT-T003 – Publish Tenant Lifecycle Events

Emit messages:
- tenant.created
- tenant.activated
- tenant.deactivated
- tenant.deleted
Consumers: Ingestion, Policy, Export services.
✅ Acceptance Criteria
- Events visible in Service Bus topic with correct payload schema.
- Downstream consumers receive and log tenant changes.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-TENANT-001:

Domain model for Tenant, Edition, and FeatureSet implemented.
Fully functional Tenant Management API with onboarding workflow.
Middleware providing per-request tenant context.
Per-tenant configuration cache and lifecycle events operational.
Integration with Identity Service validated end-to-end.

Epic `AUD-INGEST-001` : Audit Ingestion Microservice¶

Epic Description¶

This epic delivers the Audit Ingestion Microservice, responsible for securely receiving, validating, and storing audit records from internal and external producers. The service provides append-only REST and gRPC APIs, guarantees idempotency, and integrates with the internal event bus for downstream delivery to the Storage and Query services. It represents the front door of the Audit Trail Platform (ATP) and enforces all integrity, tenant, and schema validation rules.

Epic Objectives¶

Implement append-only REST and gRPC endpoints for receiving audit records.
Support idempotent writes to prevent duplicate submissions.
Integrate with MassTransit and the outbox pattern for reliable event publishing.
Enforce strict schema validation and normalization of incoming payloads.
Emit validated records to the Audit Storage and Query microservices.

Features¶

Feature `AUD-INGEST-API-001` – Append-Only APIs¶

Feature Description Expose REST and gRPC endpoints that allow external and internal services to append audit records. Endpoints must guarantee immutability — once written, an audit record cannot be updated or deleted.

Tasks¶

Task AUD-INGEST-API-T001 – Implement REST/gRPC Append Endpoints

Endpoints:
- POST /api/audit-records
- POST /api/audit-records/batch
- grpc: AppendRecord(AuditRecordRequest)
Validate authentication and tenant context.
Support batch submission with transactional safety.
✅ Acceptance Criteria
- REST and gRPC APIs deployed and documented in Swagger/Proto files.
- Batch append operations transactional and atomic per request.

Task AUD-INGEST-API-T002 – Add Idempotency and Request Deduplication

Implement idempotency keys via X-Idempotency-Key header.
Persist request hash to ensure each unique record is stored once.
Return 200 OK for duplicates.
✅ Acceptance Criteria
- Duplicate submissions return consistent responses.
- Idempotency verified via unit and integration tests.

Task AUD-INGEST-API-T003 – Configure Authentication and Tenant Middleware

Reuse ConnectSoft Identity middleware for OAuth2 validation.
Extract tenant_id and actor_id from claims.
Reject cross-tenant access attempts.
✅ Acceptance Criteria
- Requests correctly scoped to authenticated tenant.
- Unauthorized or invalid tenants receive 403 Forbidden.

Feature `AUD-INGEST-BUS-001` – Event Bus Ingestion¶

Feature Description Integrate with MassTransit to publish validated audit records to the internal event bus, ensuring reliable and asynchronous propagation to storage and analytics components.

Tasks¶

Task AUD-INGEST-BUS-T001 – Integrate MassTransit Outbox Pattern

Configure outbox for atomic persistence and message dispatch.
Store events in local DB until confirmed published.
Enable retries and deduplication on publish.
✅ Acceptance Criteria
- Outbox messages reliably delivered to the Service Bus.
- Audit records persisted before publishing.

Task AUD-INGEST-BUS-T002 – Define and Register Message Contracts

Create canonical message contracts:
- AuditRecordAppended
- AuditBatchAppended
Store schemas in shared schema registry under /schemas/audit.
✅ Acceptance Criteria
- Contracts versioned and validated in CI.
- Consumers (Storage, Query) deserialize messages successfully.

Task AUD-INGEST-BUS-T003 – Implement Retry and DLQ Handling

Configure exponential backoff retry for publish failures.
Redirect dead messages to DLQ for later inspection.
✅ Acceptance Criteria
- Failed publishes retried up to 5 times with exponential backoff.
- DLQ monitoring metrics visible in Grafana.

Feature `AUD-INGEST-VAL-001` – Validation & Normalization¶

Feature Description Ensure all incoming audit records conform to expected schemas, contain mandatory metadata, and are normalized before persistence or event emission.

Tasks¶

Task AUD-INGEST-VAL-T001 – Define Record Validation Rules

Validate required fields:
- tenant_id
- timestamp
- actor
- resource
- action
Reject payloads missing mandatory metadata.
✅ Acceptance Criteria
- Validation layer unit-tested for 100% coverage.
- Invalid requests return standardized ProblemDetails responses.

Task AUD-INGEST-VAL-T002 – Implement Payload Normalization

Normalize case sensitivity, timestamps (UTC ISO-8601), and optional fields.
Auto-generate UUIDs for missing record IDs.
✅ Acceptance Criteria
- All stored records normalized to standard schema.
- Integration tests confirm consistent timestamp formatting.

Task AUD-INGEST-VAL-T003 – Add Contract Tests and Schema Validation

Use JSON Schema validation for incoming payloads.
Validate against the canonical event schema from the registry.
✅ Acceptance Criteria
- Contract tests pass for all registered producers.
- Schema evolution tracked with semantic versioning.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-INGEST-001:

Append-only REST and gRPC APIs operational and documented.
Idempotent ingestion logic verified by integration tests.
MassTransit outbox integration with reliable delivery to the Service Bus.
Schema validation and normalization enforced on all incoming records.
DLQ and retry mechanisms tested and observable via dashboards.

Epic `AUD-STORAGE-001` : Audit Storage Microservice¶

Epic Description¶

This epic introduces the Audit Storage Microservice, which acts as the core persistence layer of the Audit Trail Platform (ATP). It stores validated audit records in a multi-tenant, append-only database, supports time-based partitioning, manages hot and cold retention tiers, and exposes internal APIs for querying, archival, and cache management. The microservice ensures that audit data remains durable, immutable, query-optimized, and compliant with retention and residency requirements.

Epic Objectives¶

Design and implement a multi-tenant relational schema to store normalized audit records.
Introduce time-based and tenant-based partitions for scalability and efficient purging.
Implement retention policies for hot and cold data management.
Provide blob archival for long-term storage in cost-optimized tiers (Azure Blob or S3).
Introduce in-memory caching for frequently queried data (latest actions, metadata).
Optimize read/write throughput while maintaining transactional integrity and immutability.

Features¶

Feature `AUD-STO-SCHEMA-001` – Multi-Tenant Database Schema¶

Feature Description Create a relational database schema supporting logical and physical tenant separation. Define tables, keys, indexes, and constraints to enforce immutability and maintain performance at scale.

Tasks¶

Task AUD-STO-SCHEMA-T001 – Implement Time/Tenant Partition Strategy

Create partitioned tables using tenant_id and record_timestamp as keys.
Configure partition pruning for queries and storage engine optimization.
Validate support for both Azure SQL Hyperscale and PostgreSQL backends.
✅ Acceptance Criteria
- Partitions automatically created by time window (e.g., monthly).
- Query performance validated with ≥ 95% partition pruning efficiency.
- Migrations run successfully across all environments.

Task AUD-STO-SCHEMA-T002 – Optimize Indexes (Actor/Resource/Date)

Add composite indexes to support common queries:
- (tenant_id, actor_id, record_timestamp)
- (tenant_id, resource_id, record_timestamp)
Evaluate index size vs. read performance trade-offs.
✅ Acceptance Criteria
- Index coverage analysis shows ≥ 95% query hit ratio.
- Execution plans verified using database profiling tools.

Task AUD-STO-SCHEMA-T003 – Define Write and Read Stored Procedures

Implement stored procedures or ORM mappings for insert and read operations.
Enforce immutability by rejecting updates or deletes.
✅ Acceptance Criteria
- Inserts append-only; updates/deletes restricted.
- ORM mappings covered by integration tests.

Feature `AUD-STO-PART-001` – Partitioning & Retention Tiers¶

Feature Description Implement tiered storage architecture for efficient cost and performance balance. Older partitions transition automatically from hot (database) to cold (object storage) tiers based on retention rules.

Tasks¶

Task AUD-STO-PART-T001 – Implement Partition Lifecycle Management

Create background job to manage partition aging:
- Hot (0-90 days)
- Warm (90-365 days)
- Cold (> 365 days → archive)
✅ Acceptance Criteria
- Lifecycle scheduler moves partitions as expected.
- Partition metadata visible via admin query endpoint.

Task AUD-STO-PART-T002 – Add Blob Archival Support for Cold Data

Export expired partitions to blob storage (Azure Blob/S3).
Generate manifest (checksum, record count, partition key).
Store manifest metadata in audit_archive_manifest table.
✅ Acceptance Criteria
- Archived data validated against checksum and record count.
- Retrieval and re-hydration tested successfully.

Task AUD-STO-PART-T003 – Implement Automated Retention Policy Engine

Integrate with Policy Service for tenant-specific retention settings.
Purge partitions only after retention period expires.
✅ Acceptance Criteria
- Retention enforcement logs stored in system audit stream.
- Legal-hold tenants excluded from purge automatically.

Feature `AUD-STO-CACHE-001` – Hot Cache Layer¶

Feature Description Provide an in-memory cache to accelerate read performance for frequent queries, such as the latest records or recent actions per tenant.

Tasks¶

Task AUD-STO-CACHE-T001 – Configure Caching with Redis/MemoryStore

Set up distributed cache (Azure Redis).
Cache keys:
- tenant:{tenant_id}:recent-records
- tenant:{tenant_id}:actor:{actor_id}:latest
Define TTL based on query frequency (default: 5 minutes).
✅ Acceptance Criteria
- Cache hit rate ≥ 90% for repeated queries.
- Redis metrics exported to Prometheus/Grafana.

Task AUD-STO-CACHE-T002 – Implement Cache Invalidation and Refresh Policies

Invalidate cache entries upon new record insertion or partition rollover.
Support asynchronous refresh via background worker.
✅ Acceptance Criteria
- Cache reflects new records within < 10 seconds of ingestion.
- No stale data returned to query clients.

Task AUD-STO-CACHE-T003 – Integrate Cache Metrics and Alerts

Emit metrics: hit ratio, latency, eviction count.
Configure alerts when hit ratio < 80% for 15 minutes.
✅ Acceptance Criteria
- Metrics visible in Grafana dashboard.
- Alerts verified via simulated load test.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-STORAGE-001:

Multi-tenant database schema and migrations implemented.
Partitioning and retention tiers operational with lifecycle automation.
Cold-tier archival process to blob storage verified.
Redis cache integrated and monitored with high hit ratio.
All schema and caching configurations deployed via CI/CD pipelines.

Epic `AUD-QUERY-001` : Audit Query Microservice¶

Epic Description¶

This epic introduces the Audit Query Microservice, which provides the primary read interface to the Audit Trail Platform (ATP). It exposes optimized APIs and projections for retrieving audit records by tenant, actor, resource, or event type. The service consumes audit data from the Storage and Ingestion microservices, maintains efficient read models, and supports full-text and metadata search as well as streaming queries over gRPC.

Epic Objectives¶

Implement REST and gRPC APIs for retrieving and filtering audit records.
Support advanced query parameters (pagination, sorting, filtering, date range).
Maintain read-side projections for query-optimized data access.
Integrate optional full-text search via Elastic or Azure Cognitive Search.
Implement result caching and asynchronous refresh mechanisms.
Expose streaming endpoints for real-time monitoring of audit data.

Features¶

Feature `AUD-QUERY-API-001` – Read APIs¶

Feature Description Develop REST and gRPC endpoints to allow consumers to query audit data efficiently and securely. All queries must be tenant-scoped, support dynamic filters, and return normalized metadata for pagination and analytics.

Tasks¶

Task AUD-QUERY-API-T001 – Implement Query Filtering, Pagination, and Sorting

Endpoints:
- GET /api/audit-records
- GET /api/audit-records/{id}
Support query parameters:
- actor, resource, action, dateFrom, dateTo, sortBy, page, pageSize.
Implement pagination using X-Total-Count and Link headers for REST.
Apply security filters to ensure tenant isolation.
✅ Acceptance Criteria
- Queries return only tenant-owned data.
- Pagination and sorting verified via integration tests.
- Swagger documentation includes parameter descriptions.

Task AUD-QUERY-API-T002 – Expose gRPC Streaming Queries

Implement gRPC service:
- SubscribeAuditStream(FilterCriteria) → stream of AuditRecordView.
Support optional filters by actor/resource/date range.
Integrate backpressure for flow control.
✅ Acceptance Criteria
- Streaming queries deliver incremental results in real time.
- Tested under simulated high-throughput scenarios.

Feature `AUD-QUERY-PROJ-001` – Read Model Projections¶

Feature Description Design and maintain read-side projections to decouple query workloads from the write path. Projections transform normalized audit records into flattened, query-optimized views.

Tasks¶

Task AUD-QUERY-PROJ-T001 – Build Read Projections and Refresh Jobs

Create projection table audit_record_projection with indexed columns:
- tenant_id, actor_id, resource_id, action, timestamp.
Implement background scheduler to refresh projections asynchronously.
Handle late-arriving events with delta updates.
✅ Acceptance Criteria
- Projection refresh completes within SLA (< 60 seconds for new events).
- Projection accuracy validated against source data.

Task AUD-QUERY-PROJ-T002 – Implement Projection Rebuild Workflow

Add endpoint /admin/projections/rebuild for admin-triggered rebuilds.
Allow scoped rebuild (tenant-level or full system).
✅ Acceptance Criteria
- Rebuild process non-blocking for live reads.
- Metrics exposed for rebuild duration and lag.

Task AUD-QUERY-PROJ-T003 – Add Projection Changefeed Notifications

Notify downstream services (Search, Analytics) of projection updates.
Emit events via projection.updated topic.
✅ Acceptance Criteria
- Changefeed events published within < 5 seconds of projection update.
- Consumers confirm receipt via integration tests.

Feature `AUD-QUERY-CACHE-001` – Result Caching¶

Feature Description Introduce in-memory caching to reduce repetitive read load and improve latency for common query patterns (recent actions, last N records per actor).

Tasks¶

Task AUD-QUERY-CACHE-T001 – Implement Query Result Cache

Cache keys:
- tenant:{id}:recent-records
- tenant:{id}:actor:{actorId}:recent
Use Redis as distributed cache with TTL = 60 seconds.
✅ Acceptance Criteria
- Cache hit ratio ≥ 85% for repeated queries.
- Metrics captured under audit_query_cache_hits_total.

Task AUD-QUERY-CACHE-T002 – Add Cache Invalidation Hooks

Invalidate cache when new data arrives from Ingestion or projection refresh.
Support asynchronous refresh triggered by message bus.
✅ Acceptance Criteria
- Cache invalidated within < 10 seconds of new data.
- Consistent query results across cache and DB.

Task AUD-QUERY-CACHE-T003 – Monitor and Alert on Cache Performance

Expose metrics: latency, hit/miss ratio, refresh count.
Configure Grafana alerts for cache hit ratio < 80%.
✅ Acceptance Criteria
- Cache performance visible in dashboard.
- Alerts tested and validated in QA environment.

Feature `AUD-QUERY-SEARCH-001` – Full-Text Search Integration (Optional)¶

Feature Description Provide optional integration with ElasticSearch or Azure Cognitive Search for full-text and advanced query capabilities across large datasets.

Tasks¶

Task AUD-QUERY-SEARCH-T001 – Integrate Search Indexer

Build indexer pipeline consuming projection updates.
Map relevant fields: actor, resource, action, message, tags.
✅ Acceptance Criteria
- Indexes refreshed within < 1 minute after projection update.
- Search queries return consistent and ranked results.

Task AUD-QUERY-SEARCH-T002 – Expose Search API Endpoints

Add endpoints:
- GET /api/audit-records/search?q=term
- Support pagination, highlighting, and relevance scoring.
✅ Acceptance Criteria
- Search results validated against stored records.
- Average search latency < 200 ms on indexed data.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-QUERY-001:

REST and gRPC read APIs implemented and documented.
Query filters, pagination, and sorting operational.
Read-side projections with automated refresh jobs deployed.
Optional full-text search integration validated.
Redis-based result cache with performance metrics live.
Streaming queries available for real-time dashboards.

Epic `AUD-INTEGRITY-001` : Integrity Verification Microservice¶

Epic Description¶

This epic introduces the Integrity Verification Microservice, a cornerstone of the Audit Trail Platform (ATP) security model. Its primary role is to ensure cryptographic tamper evidence for all persisted audit records by maintaining rolling hash chains, digitally signing data blocks, and providing APIs to verify record integrity on demand. The microservice continuously validates stored audit data and provides independently verifiable proofs for compliance and forensics.

Epic Objectives¶

Implement rolling hash chains that cryptographically link every audit record.
Apply digital signatures to signed data batches using key rotation policies.
Expose a verification API allowing clients to confirm data authenticity.
Schedule background integrity audit jobs that regularly validate stored records.
Integrate with the Audit Storage Service and Compliance overlays to provide verifiable proofs.

Features¶

Feature `AUD-INT-HASH-001` – Hash Chain Computation¶

Feature Description Implement rolling hash chains that ensure each record in a tenant’s stream is linked to the previous one. Any alteration or deletion of data will break the hash chain, making tampering immediately detectable.

Tasks¶

Task AUD-INT-HASH-T001 – Implement Per-Stream Rolling Hashes

Compute hashes per AuditStream in insertion order.
Algorithm: SHA-256 or SHA3-512, configurable per tenant.
Each record stores:
- record_hash (hash of record payload)
- previous_hash (link to prior record)
- chain_hash (cumulative hash)
✅ Acceptance Criteria
- Hash chain correctly persisted and verified on append.
- Integrity breaks detected in test scenarios.

Task AUD-INT-HASH-T002 – Optimize Hash Calculation & Persistence

Use database-side computation for high-volume tenants (via UDF or stored procedure).
Batch compute for large ingestion flows to reduce latency.
✅ Acceptance Criteria
- Average hash compute time ≤ 5 ms per record under load.
- Unit tests verify identical hash output across environments.

Feature `AUD-INT-SIGN-001` – Digital Signatures¶

Feature Description Digitally sign audit data batches using asymmetric cryptography. Each batch or partition block is signed and the signature stored in a separate verification ledger table.

Tasks¶

Task AUD-INT-SIGN-T001 – Sign Batch Blocks with Rotating Keys

Define batch interval (e.g., every 10 000 records or every hour).
Use tenant-scoped signing keys stored in Azure Key Vault.
Rotate keys quarterly and store public keys for external verification.
✅ Acceptance Criteria
- Batch signatures successfully validated using public key.
- Old keys archived and rotated without downtime.

Task AUD-INT-SIGN-T002 – Maintain Signature Ledger

Create table audit_signature_ledger storing:
- batch_id, tenant_id, start_record, end_record, signature, public_key_id, timestamp.
Expose internal API to query signatures by tenant or batch.
✅ Acceptance Criteria
- Ledger entries append-only and immutable.
- Signature metadata queryable via REST/gRPC.

Feature `AUD-INT-VERIFY-001` – Verification API¶

Feature Description Provide an API that allows clients and auditors to verify the authenticity of stored audit records or batches. The service recomputes hashes and validates signatures to produce an integrity proof.

Tasks¶

Task AUD-INT-VERIFY-T001 – Expose Verify Endpoint Returning Proof

Endpoints:
- POST /api/integrity/verify-record
- POST /api/integrity/verify-batch
Input: record ID(s), tenant ID.
Output: verification result, proof hash chain, and signature reference.
✅ Acceptance Criteria
- API returns valid proof JSON structure including hash path and signature chain.
- Negative verification (tampered data) correctly detected and logged.

Task AUD-INT-VERIFY-T002 – Provide Cryptographic Proof Object

Structure proof response:
- record_id, expected_hash, actual_hash, verified, signature_ref, timestamp.
Sign proof payload using service’s internal key for traceability.
✅ Acceptance Criteria
- Proof objects verifiable independently via stored public key.
- All proof validations logged in integrity audit table.

Feature `AUD-INT-AUDIT-001` – Background Integrity Audit Jobs¶

Feature Description Continuously verify historical data by periodically scanning stored audit records, recalculating hash chains, and validating signatures. Detect corruption or missing records early and raise alerts.

Tasks¶

Task AUD-INT-AUDIT-T001 – Implement Background Integrity Audit Job

Run scheduled job daily per tenant stream.
Recalculate and compare cumulative hashes.
Log discrepancies in audit_integrity_anomalies table.
✅ Acceptance Criteria
- Job completes within defined maintenance window.
- Anomalies automatically trigger alerts in Grafana/Teams.

Task AUD-INT-AUDIT-T002 – Integrate with Observability Stack

Expose metrics:
- integrity_verified_total, integrity_failures_total, audit_duration_seconds.
Dashboard panels for verification rate and failure ratio.
✅ Acceptance Criteria
- Metrics available in Prometheus and visualized in Grafana.
- Alerts configured for integrity failure rate > 0.01 %.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-INTEGRITY-001:

Rolling hash-chain logic implemented and validated across all tenants.
Batch-level digital signatures with key rotation policies operational.
Verification API providing cryptographic proofs for single records and batches.
Background integrity audit process verifying historical data automatically.
Integrity metrics visible through observability dashboards and alerting systems.

Epic `AUD-EXPORT-001` : Export & eDiscovery Microservice¶

Epic Description¶

This epic implements the Audit Export & eDiscovery Microservice, enabling secure, compliant extraction of audit records for investigation, compliance audits, and data portability requests. The service manages asynchronous export jobs, supports multiple output formats (CSV, Parquet, JSONL), and provides signed URLs for controlled delivery via Azure Blob Storage or AWS S3. It integrates tightly with the Audit Query, Storage, and Policy microservices to respect tenant-specific retention and access control policies.

Epic Objectives¶

Implement a background export engine for large dataset extraction.
Provide configurable export formats suitable for analytics and compliance tools.
Deliver secure, time-limited download links with strong access validation.
Maintain full auditability of export operations via lifecycle events.
Support multi-tenant isolation and edition-based export limits.

Features¶

Feature `AUD-EXP-JOB-001` – Export Job Orchestration¶

Feature Description Design and implement a scalable, asynchronous job system to orchestrate export requests from creation to delivery. Jobs must be tenant-scoped, cancellable, resumable, and fully traceable.

Tasks¶

Task AUD-EXP-JOB-T001 – Implement Async Export Job Engine

Use background job processor (Hangfire / Azure Functions Durable Tasks).
Define job states: Pending, Running, Completed, Failed, Canceled.
Persist job metadata in audit_export_job table with correlation IDs.
Expose endpoints:
- POST /api/exports – create new job
- GET /api/exports/{jobId} – retrieve job status
✅ Acceptance Criteria
- Jobs execute asynchronously and survive service restarts.
- Job progress and completion status queryable via API.

Task AUD-EXP-JOB-T002 – Implement Job Scheduling and Concurrency Control

Limit concurrent exports per tenant (default = 3).
Queue additional jobs until resources free.
Include retry and exponential-backoff for transient failures.
✅ Acceptance Criteria
- No resource starvation between tenants.
- Failed jobs automatically retried up to 3 times.

Feature `AUD-EXP-FMT-001` – Export Formats (CSV, Parquet, JSONL)¶

Feature Description Provide multiple output formats optimized for interoperability and analytics. All exports must include headers, schema version, and metadata block for traceability.

Tasks¶

Task AUD-EXP-FMT-T001 – Implement CSV Exporter

Stream results from Audit Query service directly to CSV writer.
Escape special characters and enforce UTF-8 encoding.
✅ Acceptance Criteria
- CSV exports validated by schema tests.
- File readable by Excel / Google Sheets / ETL tools.

Task AUD-EXP-FMT-T002 – Implement Parquet Exporter

Use Parquet.NET or Arrow-based library for columnar output.
Optimize compression with Snappy or GZip codecs.
✅ Acceptance Criteria
- Parquet file schema aligns with AuditRecord model.
- Compression reduces file size ≥ 50 % vs CSV.

Task AUD-EXP-FMT-T003 – Implement JSONL Exporter

Write line-delimited JSON objects for ingestion by analytics pipelines.
Include _metadata block with tenant ID, export ID, and timestamp.
✅ Acceptance Criteria
- JSONL file passes JSON schema validation.
- Compatible with downstream data-lake consumers.

Task AUD-EXP-FMT-T004 – Add Manifest and Checksums

Generate .manifest.json per export: file names, size, hash (SHA256).
Store manifest alongside exported data in storage container.
✅ Acceptance Criteria
- Checksums validated during download verification.
- Manifest accessible via API and included in lifecycle event payload.

Feature `AUD-EXP-DEL-001` – Secure Delivery¶

Feature Description Ensure exported data is delivered through secure, auditable, and time-limited channels. Use signed URLs or direct download tokens bound to specific tenants and users.

Tasks¶

Task AUD-EXP-DEL-T001 – Add Signed URL Generator & Expiry Policy

Integrate with Azure Blob Storage / S3 pre-signed URL APIs.
Default expiry: 15 minutes (configurable per edition).
Embed SHA256 checksum and job ID in metadata.
✅ Acceptance Criteria
- Download URLs expire automatically after TTL.
- Attempts to reuse expired links rejected (403).

Task AUD-EXP-DEL-T002 – Integrate Azure Blob / S3 Delivery

Upload completed export packages to target storage backend.
Support multi-region delivery based on tenant residency.
✅ Acceptance Criteria
- Files uploaded to correct region bucket/container.
- Verified integrity via hash comparison.

Task AUD-EXP-DEL-T003 – Implement Download Authorization Endpoint

Endpoint: GET /api/exports/{jobId}/download
Validate JWT claims, tenant ownership, and export status = Completed.
Redirect to pre-signed URL if authorized.
✅ Acceptance Criteria
- Unauthorized access attempts return 403.
- Successful requests return single-use download URL.

Task AUD-EXP-DEL-T004 – Emit Export Lifecycle Audit Events

Emit events:
- export.job.created
- export.job.completed
- export.job.failed
- export.downloaded
Publish via MassTransit to internal audit stream.
✅ Acceptance Criteria
- Events consumed by Audit Trail itself for meta-auditing.
- Event payloads validated against schema registry.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-EXPORT-001:

Asynchronous export engine operational with job scheduling.
Support for CSV, Parquet, and JSONL formats with manifest generation.
Secure delivery via signed URLs integrated with Azure Blob / S3.
Complete audit of export lifecycle events (create → download).
Export performance, retention compliance, and access security verified end-to-end.

Epic `AUD-POLICY-001` : Retention & Policy Microservice¶

Epic Description¶

This epic implements the Audit Policy & Retention Microservice, which governs how audit records are stored, retained, and purged in compliance with regulatory and tenant-specific requirements. It provides a declarative policy DSL, automated purge job execution, and legal-hold capabilities to ensure records are never removed prematurely while still meeting data-minimization standards. The service integrates with the Storage, Compliance, and Integrity microservices to enforce retention at both logical and physical levels.

Epic Objectives¶

Define a Retention Policy DSL that allows configuration of time-based and event-based retention rules.
Implement a Policy Executor that periodically evaluates policies and performs purge or archival actions.
Add Legal Hold management to override purge rules for tenants under investigation or compliance review.
Log all retention actions and exceptions to the compliance stream.
Ensure every purge or hold event is auditable, reversible, and traceable.

Features¶

Feature `AUD-POL-DSL-001` – Retention DSL¶

Feature Description Create a domain-specific language (DSL) to define tenant and edition-specific data-retention policies. The DSL should express durations, conditions, and overrides in a human-readable format while compiling into machine-executable rules.

Tasks¶

Task AUD-POL-DSL-T001 – Define Policy Language & Presets per Edition

Syntax examples:
- retain for 365 days
- retain for 90 days where eventType = "login"
- retain forever if legal_hold = true
Provide edition-based defaults:
- Free → 90 days
- Standard → 365 days
- Enterprise → custom per tenant
✅ Acceptance Criteria
- DSL parser and validator implemented with test coverage ≥ 90 %.
- Edition presets stored in configuration and applied automatically.

Task AUD-POL-DSL-T002 – Implement Policy Compiler and Evaluator

Translate DSL into structured execution model (JSON/AST).
Validate conditions and actions before runtime.
✅ Acceptance Criteria
- Compiled policies executable by Policy Executor.
- Invalid syntax gracefully rejected with clear error messages.

Task AUD-POL-DSL-T003 – Publish Policy Registry and Versioning

Maintain policy versions in audit_policy_registry table.
Include metadata: tenant ID, edition, effective date, author, checksum.
✅ Acceptance Criteria
- All active policies versioned and traceable.
- Registry accessible via admin API /api/policies.

Feature `AUD-POL-EXEC-001` – Policy Executor¶

Feature Description Develop the engine responsible for executing compiled retention policies on schedule. It evaluates eligible records for purge or archival and triggers corresponding actions in the Storage Service.

Tasks¶

Task AUD-POL-EXEC-T001 – Implement Purge Job Scheduler

Use background scheduler (Hangfire / Azure Functions Timer).
Evaluate retention policies nightly by tenant.
Mark eligible partitions or records for purge, then delegate to Storage API.
✅ Acceptance Criteria
- Purge jobs complete within defined maintenance window.
- Purge logs stored in audit_policy_execution_log.

Task AUD-POL-EXEC-T002 – Integrate with Storage Partition Lifecycle

Call Storage API endpoints to remove or archive partitions.
Handle rollback on partial failure.
✅ Acceptance Criteria
- Partition deletion confirmed by checksum validation.
- Partial failures retried automatically.

Task AUD-POL-EXEC-T003 – Integrate Compliance Exception Logging

Log every purge or skip decision with reason code.
Stream logs to Compliance microservice topic compliance.policy.activity.
✅ Acceptance Criteria
- Each purge event accompanied by compliance log entry.
- Logs visible in compliance dashboard.

Task AUD-POL-EXEC-T004 – Expose Policy Evaluation Metrics

Metrics:
- records_purged_total
- policies_executed_total
- execution_duration_seconds
Export via OpenTelemetry → Prometheus.
✅ Acceptance Criteria
- Metrics collected and displayed in Grafana.
- Alerts trigger on failed executions > 1 %.

Feature `AUD-POL-HOLD-001` – Legal Hold Management¶

Feature Description Provide mechanisms to place tenants, partitions, or individual audit streams under legal hold, suspending all purge activity until released. Holds must override active retention policies.

Tasks¶

Task AUD-POL-HOLD-T001 – Implement Legal Hold API

Endpoints:
- POST /api/holds – create hold
- DELETE /api/holds/{id} – release hold
- GET /api/holds – list active holds
Include metadata: tenant_id, scope, reason, expires_on.
✅ Acceptance Criteria
- Legal holds applied instantly prevent scheduled purges.
- Holds auditable and reversible through API.

Task AUD-POL-HOLD-T002 – Enforce Hold During Policy Execution

Modify Policy Executor to skip any entity under active hold.
Log skipped actions as reason = "legal_hold".
✅ Acceptance Criteria
- No records deleted while hold active.
- Hold enforcement confirmed by integration tests.

Task AUD-POL-HOLD-T003 – Notify Compliance Service on Hold Creation/Release

Emit events:
- legalhold.created
- legalhold.released
Include tenant, scope, author, and timestamps.
✅ Acceptance Criteria
- Events delivered to Compliance queue within 5 seconds.
- Notifications visible in compliance audit log.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-POLICY-001:

Retention Policy DSL defined, versioned, and executed across tenants.
Purge job scheduler operational with compliance logging.
Legal Hold management APIs functioning and auditable.
Integration with Storage and Compliance services verified end-to-end.
Observability metrics available for policy execution performance and anomalies.

Epic `AUD-SEARCH-001` : Search Index Microservice¶

Epic Description¶

This epic implements the Search Index Microservice, responsible for enabling fast, full-text, and metadata-based search capabilities across all audit records. It indexes structured and unstructured fields (actor, resource, message, tags) to allow investigators, compliance officers, and internal systems to perform advanced queries efficiently. The service consumes projection updates from the Audit Query Microservice and maintains its own optimized search indexes in ElasticSearch or Azure Cognitive Search.

Epic Objectives¶

Implement metadata indexing pipelines that synchronize data from projections and audit streams.
Provide full-text search across audit message fields and contextual metadata.
Expose search query APIs with advanced filtering and relevance scoring.
Support reindexing jobs to rebuild or refresh indexes when schemas change.
Ensure multi-tenant isolation, query performance, and secure search operations.

Features¶

Feature `AUD-SRCH-META-001` – Metadata Indexing¶

Feature Description Develop data ingestion pipelines that index audit metadata and maintain search documents optimized for lookups and filters. Each indexed document should represent one normalized audit record, enriched with tenant, actor, and contextual fields.

Tasks¶

Task AUD-SRCH-META-T001 – Create Index Pipelines & Analyzers

Build ingestion pipeline subscribing to projection.updated and audit.record.appended events.
Map fields:
- tenant_id, actor_id, resource_id, action, timestamp, message, tags.
Define analyzers and tokenizers:
- Keyword analyzer for tenant_id and resource_id.
- Lowercase + stopword analyzer for message and tags.
✅ Acceptance Criteria
- Index creation automated via schema migration script.
- Ingestion latency < 5 seconds from event publish to index availability.

Task AUD-SRCH-META-T002 – Implement Incremental and Bulk Indexing

Support two modes:
- Incremental updates (real-time via message bus).
- Bulk reindex (full refresh from projection DB).
Store index offset checkpoints per tenant for resiliency.
✅ Acceptance Criteria
- Incremental indexing never skips or duplicates records.
- Bulk reindex completes without downtime.

Task AUD-SRCH-META-T003 – Configure Multi-Tenant Index Partitioning

Partition indexes by tenant or region using prefixes:
- tenant-{id}-audit-index
Enforce search isolation across tenants.
✅ Acceptance Criteria
- No cross-tenant data returned during queries.
- Partition list discoverable via admin API.

Feature `AUD-SRCH-FTS-001` – Full-Text Capabilities¶

Feature Description Add advanced search features such as keyword, phrase, wildcard, and relevance-based ranking. Support analytics filters for aggregation by actor, action type, and time window.

Tasks¶

Task AUD-SRCH-FTS-T001 – Expose Search Query API

Endpoints:
- GET /api/search?q={term}
- GET /api/search/advanced – for multi-field search
Query parameters:
- tenantId, actor, resource, from, to, sort, highlight.
Include pagination and total hit count metadata.
✅ Acceptance Criteria
- Search results ranked by relevance (TF-IDF / BM25).
- API returns consistent pagination and accurate hit counts.

Task AUD-SRCH-FTS-T002 – Implement Highlighting & Faceted Aggregation

Add highlighting for matched text snippets.
Enable facet aggregations for:
- actor, action, resource, date histogram.
✅ Acceptance Criteria
- Highlight sections correctly emphasize matching text.
- Facet results accurate within ±1 % aggregation error.

Task AUD-SRCH-FTS-T003 – Integrate Security Filters

Apply tenant-based query filters derived from JWT claims.
Enforce per-edition result limits (e.g., Standard = 30 days, Enterprise = 1 year).
✅ Acceptance Criteria
- Search restricted to authorized tenant scope.
- Unauthorized query attempts return 403 Forbidden.

Feature `AUD-SRCH-MAINT-001` – Reindex & Maintenance Jobs¶

Feature Description Implement automated and manual reindexing workflows for schema changes or data corruption recovery. Support monitoring and alerts for indexing latency or failure conditions.

Tasks¶

Task AUD-SRCH-MAINT-T001 – Implement Reindex Jobs

Endpoint:
- POST /api/search/reindex – triggers background rebuild.
Use job framework (Hangfire / Azure Functions Durable).
Store job progress and results in search_reindex_log.
✅ Acceptance Criteria
- Reindex job completes without affecting live queries.
- Progress trackable via API and dashboard.

Task AUD-SRCH-MAINT-T002 – Add Index Health & Metrics Monitoring

Expose metrics:
- indexing_latency_seconds
- documents_indexed_total
- reindex_failures_total
Integrate with Prometheus / Grafana for observability.
✅ Acceptance Criteria
- Indexing latency < 2 seconds average under normal load.
- Alerts configured for index lag > 10 seconds.

Task AUD-SRCH-MAINT-T003 – Implement Alerting and Retry for Failed Index Batches

Capture failed bulk inserts and retry in smaller batches.
Send notifications to DevOps channel upon persistent failure.
✅ Acceptance Criteria
- Failed batches retried up to 5 times before alert.
- Error details captured in diagnostic logs.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-SEARCH-001:

Real-time and bulk index pipelines operational.
Multi-tenant, partitioned indexes secured and query-optimized.
Full-text and faceted search APIs functional with highlighting.
Reindex and index maintenance jobs automated and monitored.
Search metrics visible in observability dashboards with alerting rules active.

Epic `AUD-GATEWAY-001` : API Gateway / Edge Service¶

Epic Description¶

This epic introduces the Audit Trail API Gateway, the secure and observable entry point for all external and internal consumers of the Audit Trail Platform (ATP). It unifies routing, authentication, rate limiting, and observability across all downstream microservices (Ingestion, Query, Export, Policy, etc.). The gateway simplifies API consumption, enforces cross-service consistency, and ensures all traffic adheres to ConnectSoft’s centralized identity and telemetry standards.

Epic Objectives¶

Implement centralized routing and request aggregation using YARP or Ocelot.
Integrate OAuth2 and API key authentication for service and external clients.
Apply rate limiting, request throttling, and quota enforcement at the edge.
Enable distributed tracing propagation for full request observability.
Collect edge-level metrics and logs for performance, latency, and errors.
Provide a single entry point for multi-tenant routing and onboarding.

Features¶

Feature `AUD-GW-ROUTE-001` – Central Routing & Aggregation¶

Feature Description Implement centralized routing configuration for all ATP services using YARP or Ocelot. Support dynamic route discovery, request transformation, and response aggregation for multi-service APIs.

Tasks¶

Task AUD-GW-ROUTE-T001 – Configure YARP or Ocelot Routing

Configure reverse proxy routes:
- /api/audit-ingest/* → Audit.IngestionService
- /api/audit-query/* → Audit.QueryService
- /api/audit-storage/* → Audit.StorageService
- /api/audit-export/* → Audit.ExportService
Implement route discovery via configuration file or service registry.
Enable retries and circuit breakers for downstream resilience.
✅ Acceptance Criteria
- All ATP services accessible through a unified gateway endpoint.
- Gateway recovers gracefully from service unavailability.

Task AUD-GW-ROUTE-T002 – Implement Request/Response Aggregation

Aggregate multiple downstream responses into single payloads where applicable.
Example:
- /api/audit/overview aggregates data from Query, Policy, and Integrity services.
✅ Acceptance Criteria
- Aggregated response delivered within < 500 ms at P95.
- Aggregation logic reusable via middleware or filters.

Task AUD-GW-ROUTE-T003 – Configure Route-Based Caching

Cache responses for common, non-sensitive routes (e.g., /api/audit/stats).
Use in-memory caching or Redis distributed cache for short TTLs (30–60 seconds).
✅ Acceptance Criteria
- Cache hit ratio ≥ 80 % for repeated requests.
- Cache invalidation triggered on data changes.

Feature `AUD-GW-SEC-001` – Auth & Rate Limiting¶

Feature Description Implement unified security policies at the edge layer, including OAuth2 authentication, API key support, and rate limiting. Ensure each request is authenticated, authorized, and tracked according to ConnectSoft security standards.

Tasks¶

Task AUD-GW-SEC-T001 – Add API Key & OAuth2 Flow

Configure authentication handlers for:
- External clients using API keys.
- Internal services and users using OAuth2 JWTs.
Integrate with ConnectSoft Identity and Access microservice.
✅ Acceptance Criteria
- API key and OAuth2 authentication both supported and validated.
- Unauthorized requests rejected with 401/403 responses.

Task AUD-GW-SEC-T002 – Implement Rate Limiting & Quotas

Apply per-tenant and per-route rate limits.
Default quotas (configurable):
- 100 requests/sec for Enterprise tenants.
- 20 requests/sec for Free tier tenants.
Add Retry-After header for throttled requests.
✅ Acceptance Criteria
- Excess requests receive 429 Too Many Requests.
- Limits configurable dynamically via External Configuration Service.

Task AUD-GW-SEC-T003 – Enforce Request Validation & Sanitization

Add global middleware to sanitize headers and payloads.
Reject malformed or oversized requests (> 1 MB).
✅ Acceptance Criteria
- All input sanitized; no unhandled exceptions logged at gateway level.
- OWASP Top 10 validation checks automated in pre-deployment tests.

Feature `AUD-GW-MON-001` – Edge Observability¶

Feature Description Add complete visibility into all inbound and outbound requests at the gateway layer. Enable distributed tracing, metrics, and logging for performance optimization and anomaly detection.

Tasks¶

Task AUD-GW-MON-T001 – Integrate Distributed Tracing Headers

Propagate and generate OpenTelemetry tracing headers:
- traceparent, baggage, correlation-id.
Configure context propagation across downstream microservices.
✅ Acceptance Criteria
- All downstream traces appear as part of a single distributed span.
- Trace data visible in Jaeger and Grafana Tempo.

Task AUD-GW-MON-T002 – Implement Request Logging and Metrics

Capture metrics:
- gateway_requests_total
- gateway_latency_seconds
- gateway_errors_total
Log request summaries with correlation IDs to Seq and Application Insights.
✅ Acceptance Criteria
- Metrics available in Prometheus and visualized in Grafana dashboards.
- Logs searchable by tenant and correlation ID.

Task AUD-GW-MON-T003 – Add Health, Status, and Diagnostic Endpoints

Expose endpoints:
- /healthz – readiness check
- /status – active routes, uptime, environment info
- /metrics – Prometheus-compatible metrics
✅ Acceptance Criteria
- Health endpoints integrated with Azure Health Probes.
- Gateway uptime ≥ 99.9 % validated by monitoring.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-GATEWAY-001:

Unified routing layer configured with retries, circuit breakers, and caching.
OAuth2 and API key authentication implemented and validated.
Rate limiting and quota enforcement functioning across all tenants.
Distributed tracing, logs, and metrics integrated with observability stack.
Gateway endpoints for health, status, and diagnostics live in all environments.

Epic `AUD-IDENTITY-001` : Integration with IAM¶

Epic Description¶

This epic focuses on integrating the Audit Trail Platform (ATP) with the centralized Identity and Access Management (IAM) system based on OpenIddict and OAuth2. The integration provides authentication and authorization for both human and service identities, ensuring secure and consistent access control across all ATP microservices. It also enables role- and claim-based access propagation, tenant-aware tokens, and secure service-to-service authentication within the platform.

Epic Objectives¶

Establish OAuth2/OpenID Connect integration across all ATP services.
Support multi-tenant token issuance and validation using ConnectSoft Identity Service.
Implement service-to-service authorization policies with least-privilege principles.
Propagate roles, claims, and tenant context across HTTP, gRPC, and message-bus communications.
Enforce standardized identity middleware for consistent security posture across the platform.

Features¶

Feature `AUD-ID-AUTH-001` – OAuth2/OpenIddict Integration¶

Feature Description Integrate all Audit Trail microservices with the ConnectSoft Identity Provider (IDP) for authentication and authorization. Ensure each service validates tokens, handles claim resolution, and supports both user and client credentials flows.

Tasks¶

Task AUD-ID-AUTH-T001 – Connect Microservices to IAM Tokens

Configure all services to use OpenIddict discovery endpoints (/.well-known/openid-configuration).
Register ATP clients (audit-gateway, audit-query, audit-export, etc.) in IAM.
Enable the following grant types per service:
- Client Credentials – for internal services.
- Authorization Code – for user-facing interfaces.
Implement JWT bearer authentication in each service using middleware.
✅ Acceptance Criteria
- All APIs require valid tokens; unauthorized requests return 401.
- Token discovery and validation tested for each environment.
- Services accept and validate both access and ID tokens correctly.

Task AUD-ID-AUTH-T002 – Implement Token Caching and Validation Optimization

Introduce in-memory and distributed caching of token validation results.
Validate signing keys automatically from JWKS endpoint.
Refresh JWKS every 24 hours or on signature mismatch.
✅ Acceptance Criteria
- Token validation performance improved by ≥ 30 %.
- No expired or revoked tokens accepted.

Task AUD-ID-AUTH-T003 – Configure Token Scopes and Audience Claims

Define standard scopes:
- audit.read, audit.write, audit.export, audit.manage.
Verify aud and scope claims match requested resources.
✅ Acceptance Criteria
- Tokens containing invalid or missing scopes rejected.
- Scope enforcement confirmed via integration tests.

Feature `AUD-ID-ROLES-001` – Roles & Claims Propagation¶

Feature Description Implement role- and claim-based access propagation across all ATP components. Ensure consistent enforcement of tenant, edition, and permission attributes derived from the IAM tokens.

Tasks¶

Task AUD-ID-ROLES-T001 – Propagate Roles and Claims Across Services

Extend tokens to include:
- tenant_id, edition, feature_flags, role, permissions.
Implement middleware to inject claims into:
- HTTP headers (x-tenant-id, x-user-role).
- gRPC metadata.
- MassTransit message headers.
✅ Acceptance Criteria
- All downstream calls include tenant and role context.
- Claims propagation verified end-to-end across gateway, ingestion, and query paths.

Task AUD-ID-ROLES-T002 – Implement Role-Based Authorization Policies

Define policies (e.g., RequireRole("ComplianceOfficer"), RequireScope("audit.manage")).
Apply policies to controller and gRPC endpoints.
✅ Acceptance Criteria
- Authorization attributes correctly restrict protected endpoints.
- Access logs include principal ID, tenant ID, and role.

Task AUD-ID-ROLES-T003 – Implement Service-to-Service Auth Policies

Issue managed service identities for internal ATP components.
Configure trust relationships using OAuth2 client credentials flow.
Restrict internal communication to trusted service principals only.
✅ Acceptance Criteria
- Inter-service requests authenticated via client credentials.
- Unauthorized internal requests rejected with 401/403 responses.
- Policies documented in /docs/security/service-auth.md.

Task AUD-ID-ROLES-T004 – Integrate Centralized Access Logging

Log every authentication and authorization event to a unified audit log.
Include metadata: subject, tenant, scope, decision, timestamp.
✅ Acceptance Criteria
- Access logs visible in central observability dashboard.
- Anomalous access attempts flagged for review.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-IDENTITY-001:

OAuth2/OpenID Connect integration active for all ATP services.
Role- and claim-based authorization consistently enforced.
Service-to-service authentication secured with least privilege.
Tokens include tenant, role, and edition claims for contextual access control.
Centralized logging and observability for all IAM-related events established.

Epic `AUD-SECURITY-001` : RBAC, ABAC & Redaction¶

Epic Description¶

This epic establishes the security enforcement layer across the Audit Trail Platform (ATP), providing fine-grained access control, dynamic policy evaluation, and runtime redaction of sensitive fields. It introduces Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and a Redaction Engine to ensure that users and services only see the data they are authorized to access. The implementation aligns with ConnectSoft’s enterprise security and privacy standards.

Epic Objectives¶

Define and enforce role-based access policies across all ATP services.
Introduce attribute-based policies that evaluate user, tenant, and resource attributes at runtime.
Implement a data redaction framework to protect PII and regulated fields in query and export results.
Integrate with IAM and Compliance microservices to record all authorization and redaction events.
Ensure every access decision is auditable, deterministic, and explainable.

Features¶

Feature `AUD-SEC-RBAC-001` – Role-Based Model¶

Feature Description Implement a standardized RBAC model defining platform-wide roles, their scopes, and associated permissions. Integrate the model into all API and gRPC entry points for uniform enforcement.

Tasks¶

Task AUD-SEC-RBAC-T001 – Build Permission Matrix per Microservice

Define roles and permissions such as:
- Admin – full access to all tenant data.
- ComplianceOfficer – read-only access with export rights.
- SupportAgent – limited view (masked sensitive fields).
- SystemService – internal service-to-service operations.
Map each permission to specific endpoints and service actions.
Document matrix in /docs/security/permissions-matrix.md.
✅ Acceptance Criteria
- Permission matrix reviewed and approved by Security Architect.
- All services reference centralized role constants from shared library.

Task AUD-SEC-RBAC-T002 – Implement Role Enforcement Middleware

Add middleware that inspects token roles and matches against required permissions.
Support both REST and gRPC interceptors.
✅ Acceptance Criteria
- Unauthorized users receive 403 Forbidden.
- Authorized users pass all RBAC policy checks.

Task AUD-SEC-RBAC-T003 – Centralize Role Configuration in IAM

Synchronize role definitions with ConnectSoft IAM.
Automate propagation of new or modified roles to microservices via configuration service.
✅ Acceptance Criteria
- Role changes reflected in microservices within < 5 minutes.
- Audit logs record every role update event.

Feature `AUD-SEC-ABAC-001` – Attribute Conditions¶

Feature Description Introduce an ABAC engine that evaluates dynamic attributes (tenant, edition, actor, resource sensitivity) at runtime. Policies determine whether access is granted based on contextual metadata.

Tasks¶

Task AUD-SEC-ABAC-T001 – Implement Attribute-Based Policy Engine

Create evaluation rules language supporting conditions like:
- tenant.region == user.region
- record.sensitivity <= user.clearance
- edition in ["Enterprise","CompliancePlus"]
Policies stored in centralized configuration repository.
✅ Acceptance Criteria
- ABAC engine integrated as middleware across services.
- All access decisions logged with evaluated attributes.

Task AUD-SEC-ABAC-T002 – Integrate Policy Evaluation with Query & Export

Extend Query and Export services to call ABAC evaluator before returning data.
Deny or redact results when policies fail.
✅ Acceptance Criteria
- Restricted data never exposed in API responses.
- Performance overhead ≤ 10 % vs. baseline queries.

Task AUD-SEC-ABAC-T003 – Implement Policy Administration API

Endpoints:
- POST /api/policies – create/update policy.
- GET /api/policies/{id} – retrieve.
- DELETE /api/policies/{id} – remove.
✅ Acceptance Criteria
- Administrators can manage attribute policies via authenticated API.
- All changes versioned and logged in audit_policy_change_log.

Feature `AUD-SEC-MASK-001` – Redaction Engine¶

Feature Description Develop a redaction framework that dynamically masks or removes sensitive fields (PII, PHI, secrets) in query, export, and webhook payloads based on user roles and policies.

Tasks¶

Task AUD-SEC-MASK-T001 – Enforce Field-Level Masking on Output

Identify sensitive fields (e.g., actor.email, ip_address, session_token).
Apply masking strategies:
- Replace → "******"
- Hash → SHA-256 truncated
- Remove → field omitted entirely
Implement via response filter middleware for REST/gRPC.
✅ Acceptance Criteria
- Masking applied consistently across all services.
- Logs confirm redaction events with trace IDs.

Task AUD-SEC-MASK-T002 – Implement Redaction Rules Configuration

Store redaction rules per tenant or edition in configuration service.
Allow runtime reload without restart.
✅ Acceptance Criteria
- Tenants can opt-in/out of specific redaction levels.
- Configuration changes propagate dynamically.

Task AUD-SEC-MASK-T003 – Integrate Redaction with Export and Webhook Payloads

Apply redaction pipeline before generating export files or webhook events.
Annotate metadata in exported manifest: fields_redacted: [list].
✅ Acceptance Criteria
- Sensitive fields removed before data leaves platform.
- Export manifests include redaction summary.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-SECURITY-001:

Unified RBAC and ABAC models operational across all microservices.
Role- and attribute-based enforcement verified by integration and security tests.
Field-level redaction active in API, export, and webhook outputs.
All access and redaction events logged and auditable.
Configuration and policies centrally managed and dynamically distributed.

Epic `AUD-OTEL-001` : Observability & Telemetry Framework¶

Epic Description¶

This epic establishes the Observability and Telemetry Framework for the Audit Trail Platform (ATP). It integrates OpenTelemetry (OTel) instrumentation across all microservices to provide unified traces, metrics, and logs. The framework ensures that every transaction—spanning ingestion, storage, query, and export—is fully traceable, measurable, and diagnosable within the platform’s observability stack (Prometheus, Grafana, Jaeger, and Seq).

Epic Objectives¶

Implement OpenTelemetry middleware across all ATP services for distributed tracing and correlation.
Standardize structured logging with correlation IDs, tenant context, and trace links.
Collect metrics on performance, latency, error rates, and throughput for each component.
Integrate with Prometheus for metric scraping and Grafana for visualization.
Provide unified observability dashboards and alerting for proactive monitoring.
Ensure observability coverage ≥ 95 % across all microservices.

Features¶

Feature `AUD-OTEL-TRC-001` – Traces & Spans¶

Feature Description Implement distributed tracing to visualize the flow of requests across all microservices (Gateway → Ingestion → Storage → Query → Export → Integrity). Ensure all trace spans include correlation metadata such as tenant_id, traceparent, and operation.

Tasks¶

Task AUD-OTEL-TRC-T001 – Add OTel Middleware to All Services

Add OpenTelemetry SDK to each ATP microservice.
Instrument:
- HTTP pipeline (incoming/outgoing requests).
- gRPC server and client interceptors.
- MassTransit message consumers/producers.
Ensure traceparent and baggage headers are propagated end-to-end.
✅ Acceptance Criteria
- Trace continuity maintained across all service boundaries.
- 100 % of inbound/outbound requests emit trace IDs.
- Traces visible in Jaeger and Grafana Tempo.

Task AUD-OTEL-TRC-T002 – Define Trace Naming & Span Conventions

Adopt consistent naming for spans:
- audit.ingest.append, audit.query.fetch, audit.policy.evaluate, etc.
Tag spans with:
- tenant.id, edition, user.role, operation.name.
✅ Acceptance Criteria
- All traces conform to standardized naming scheme.
- Span metadata available in query filters for analysis.

Task AUD-OTEL-TRC-T003 – Configure Trace Sampling & Exporters

Set default sampling rate: 10 % for production, 100 % for non-prod.
Export traces to:
- Jaeger (trace visualization).
- Grafana Tempo (long-term storage).
✅ Acceptance Criteria
- Sampling and exporter configurations environment-specific.
- Trace ingestion performance overhead ≤ 5 %.

Feature `AUD-OTEL-MET-001` – Metrics (Latency, Throughput)¶

Feature Description Expose quantitative metrics for performance and reliability, covering request latency, throughput, error rates, queue depth, and resource usage. All metrics must follow OpenTelemetry Metric Semantic Conventions and be consumable by Prometheus.

Tasks¶

Task AUD-OTEL-MET-T001 – Instrument Core Metrics per Service

Metrics examples:
- http_requests_total, http_request_duration_seconds, grpc_calls_total.
- bus_messages_published_total, bus_processing_latency_seconds.
- audit_records_ingested_total, audit_query_latency_seconds.
Implement via OTel Meter API.
✅ Acceptance Criteria
- All critical operations emit latency and count metrics.
- Metrics successfully scraped by Prometheus.

Task AUD-OTEL-MET-T002 – Configure Prometheus/Grafana Dashboards

Create dashboards per microservice showing:
- Request rate, error rate, latency histogram.
- Resource usage (CPU, memory).
- Business metrics (records ingested, exports completed).
✅ Acceptance Criteria
- Dashboards published in /docs/observability/dashboards.md.
- Visualization templates reusable across environments.

Task AUD-OTEL-MET-T003 – Define SLOs and Alerts

Define SLOs per service, e.g.:
- P95 latency < 300 ms.
- Error rate < 1 %.
- Uptime ≥ 99.9 %.
Create alerting rules in Prometheus and Grafana Alertmanager.
✅ Acceptance Criteria
- Alerts trigger on SLO violation.
- Alerts integrated with Teams/Slack channels.

Feature `AUD-OTEL-LOG-001` – Structured Logs¶

Feature Description Standardize logging format across all services using structured JSON logs compatible with Seq and Application Insights. Logs should correlate to traces via trace IDs and include contextual fields for tenants, requests, and exceptions.

Tasks¶

Task AUD-OTEL-LOG-T001 – Implement Structured Logging Format

Adopt standard schema:
- timestamp, level, tenant_id, trace_id, span_id, message, context.
Use Serilog with OpenTelemetry Log Exporter.
✅ Acceptance Criteria
- All logs JSON-formatted and contain trace correlation fields.
- Logging overhead ≤ 3 % CPU under load.

Task AUD-OTEL-LOG-T002 – Integrate Centralized Log Storage

Forward logs to:
- Seq (development & debugging).
- Azure Application Insights (production).
Include ingestion rules for error/warning aggregation.
✅ Acceptance Criteria
- Logs searchable by correlation ID or tenant.
- Storage retention policy validated for compliance.

Task AUD-OTEL-LOG-T003 – Add Contextual Logging Middleware

Enrich logs with contextual metadata:
- actor.id, request.method, endpoint.path, execution.time.
Capture unhandled exceptions globally.
✅ Acceptance Criteria
- Every log entry includes contextual data.
- Exceptions logged with stack trace and correlation ID.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-OTEL-001:

OpenTelemetry instrumentation active in all ATP services.
Distributed traces visible end-to-end in Jaeger and Grafana Tempo.
Prometheus and Grafana dashboards operational with live metrics.
Structured JSON logging integrated with Seq and Application Insights.
SLOs and alerts established for latency, throughput, and error rates.
Observability coverage validated ≥ 95 % of services.

Epic `AUD-RATE-001` : Quotas & Rate Limiting¶

Epic Description¶

This epic introduces the Quotas and Rate Limiting subsystem for the Audit Trail Platform (ATP). It ensures fair resource usage across tenants and editions, preventing service abuse while maintaining high availability. By combining tenant-based quotas, edition-aware scaling, and adaptive throttling, the system enforces contractual limits and safeguards shared infrastructure without compromising user experience.

Epic Objectives¶

Enforce tenant-level request quotas across all APIs (REST/gRPC).
Support edition-aware rate tiers (Free, Standard, Enterprise).
Provide token-bucket rate limiting for burst handling.
Include Retry-After headers and standardized 429 responses.
Centralize quota configuration in the External Configuration Service.
Expose metrics and alerts for quota consumption and throttling patterns.

Features¶

Feature `AUD-RATE-TEN-001` – Tenant-Based Quotas¶

Feature Description Implement tenant-scoped rate-limiting middleware to track request throughput per tenant, route, and authentication context. Persist usage metrics for observability and historical analysis.

Tasks¶

Task AUD-RATE-TEN-T001 – Implement Token-Bucket Limiter

Add distributed token-bucket algorithm (Redis or in-memory fallback).
Key structure: tenant:{tenant_id}:endpoint:{path}.
Configure tokens-per-second based on tenant edition.
Allow short bursts (up to 2× sustained rate).
✅ Acceptance Criteria
- Requests above quota receive HTTP 429 Too Many Requests.
- Limiter performance overhead < 5 %.
- Unit/integration tests validate burst and sustained behavior.

Task AUD-RATE-TEN-T002 – Persist Quota Usage Metrics

Record counters:
- requests_allowed_total, requests_blocked_total, tokens_remaining.
Expose metrics via OpenTelemetry → Prometheus.
✅ Acceptance Criteria
- Metrics visible in Grafana dashboards.
- Throttled request percentage < 2 % under normal load.

Task AUD-RATE-TEN-T003 – Add Retry-After Headers & Consistent Responses

For throttled responses, include:
- Retry-After header (seconds until next token).
- JSON ProblemDetails payload with tenant and quota context.
✅ Acceptance Criteria
- All 429 responses include Retry-After.
- Documentation updated in /docs/api/rate-limits.md.

Feature `AUD-RATE-EDT-001` – Edition Scaling¶

Feature Description Integrate rate and quota logic with the Edition Management system to scale limits dynamically by product edition and SLA tier.

Tasks¶

Task AUD-RATE-EDT-T001 – Configure Edition-Aware Quota Profiles

Define default quota profiles:
- Free: 20 req/sec, max 1000/day
- Standard: 100 req/sec, max 100 000/day
- Enterprise: 500 req/sec, max 1 000 000/day
Retrieve profiles from Tenant Service via internal API.
✅ Acceptance Criteria
- Edition quotas automatically applied to new tenants.
- Profile updates reflected within 5 minutes.

Task AUD-RATE-EDT-T002 – Implement Dynamic Scaling and Burst Allowance

Allow temporary burst scaling during off-peak hours or SLA upgrades.
Integrate scheduler to refresh rate limits periodically.
✅ Acceptance Criteria
- Quota scaling executed without service restart.
- Logs confirm policy updates and scaling actions.

Task AUD-RATE-EDT-T003 – Expose Admin API for Quota Inspection

Endpoints:
- GET /api/quotas/{tenantId} – current usage
- POST /api/quotas/reset/{tenantId} – admin reset
Require audit.manage scope.
✅ Acceptance Criteria
- Administrators can view and reset tenant quotas.
- Access logged and auditable.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-RATE-001:

Token-bucket rate limiter deployed platform-wide.
Tenant-based quota metrics collected and visualized.
Edition-aware scaling policies automatically enforced.
429 responses include Retry-After headers and contextual details.
Admin APIs and dashboards operational for quota inspection.
Rate-limiting performance validated under load and multi-tenant conditions.

Epic `AUD-SDK-001` : SDK & Developer Tooling¶

Epic Description¶

This epic delivers the Developer SDKs and tooling for integrating external systems and client applications with the Audit Trail Platform (ATP). It provides official SDKs for .NET and JavaScript/TypeScript, ensuring developers can easily send, query, and verify audit events through standardized APIs. The SDKs abstract authentication, serialization, and telemetry, while also including CI pipelines, documentation, and usage examples to streamline adoption.

Epic Objectives¶

Deliver official SDKs for .NET and JavaScript/TypeScript ecosystems.
Provide easy-to-use client libraries for sending and querying audit events.
Implement built-in retry, idempotency, and correlation header handling.
Support multi-tenant token management and telemetry propagation.
Publish SDKs to NuGet and npm with automated CI/CD release pipelines.
Provide developer samples, API reference docs, and integration tests.

Features¶

Feature `AUD-SDK-DOTNET-001` – .NET SDK¶

Feature Description Develop a lightweight, dependency-minimized .NET SDK that enables developers to interact with ATP’s APIs via a typed and strongly-validated client. It should provide out-of-the-box support for authentication, retries, telemetry, and serialization.

Tasks¶

Task AUD-SDK-DOTNET-T001 – Implement Core .NET Client Library

Create library ConnectSoft.AuditTrail.Client targeting .NET 8+.
Core client interfaces:
- IAuditIngestionClient
- IAuditQueryClient
- IAuditVerificationClient
Implement HTTP client with support for OAuth2 tokens and correlation headers.
✅ Acceptance Criteria
- SDK fully compatible with ATP Gateway endpoints.
- Includes retry, logging, and timeout policies using HttpClientFactory.

Task AUD-SDK-DOTNET-T002 – Add Strongly Typed Models & Validation

Generate models from OpenAPI specification using NSwag.
Implement validation via System.ComponentModel.DataAnnotations.
Include tenant context injection middleware.
✅ Acceptance Criteria
- All DTOs match server-side contract schemas.
- Validation errors surfaced with clear developer messages.

Task AUD-SDK-DOTNET-T003 – Publish NuGet Package

Automate build and publish using Azure DevOps pipeline:
- dotnet pack → dotnet nuget push
Semantic versioning: v1.x.y aligned with API release versions.
✅ Acceptance Criteria
- Package available on nuget.org and internal ConnectSoft feed.
- CI pipeline triggers on tagged releases.

Task AUD-SDK-DOTNET-T004 – Provide Samples & Unit Tests

Provide samples in /samples/dotnet/:
- Ingest audit record
- Query audit records by actor
- Verify record integrity proof
Add MSTest-based unit tests for API methods and error handling.
✅ Acceptance Criteria
- Sample code runnable out of the box with demo API keys.
- CI tests execute successfully during SDK pipeline run.

Feature `AUD-SDK-JS-001` – JS/TS SDK¶

Feature Description Deliver a TypeScript-based SDK compatible with Node.js and browser environments. The SDK simplifies integration for web apps, serverless functions, and admin dashboards by providing typed APIs and built-in token handling.

Tasks¶

Task AUD-SDK-JS-T001 – Implement Core TypeScript SDK

Package name: @connectsoft/audit-trail.
Use Axios or Fetch with retry + timeout.
Modules:
- AuditIngestionClient
- AuditQueryClient
- AuditVerificationClient
✅ Acceptance Criteria
- Fully typed client methods generated from OpenAPI spec.
- SDK usable both in Node.js and modern browsers (ESM).

Task AUD-SDK-JS-T002 – Add Authentication and Token Handling

Support bearer tokens and tenant headers automatically.
Provide configuration for API base URL, timeout, and retries.
✅ Acceptance Criteria
- SDK handles token injection seamlessly.
- Invalid tokens raise well-structured AuthError exceptions.

Task AUD-SDK-JS-T003 – Publish npm Package

Build with Rollup or tsup for ESM/CJS output.
Publish to npmjs.com and internal registry.
Version naming mirrors .NET SDK version (e.g., 1.0.0).
✅ Acceptance Criteria
- npm publish automated in CI pipeline.
- README includes installation and example snippets.

Task AUD-SDK-JS-T004 – Provide Usage Samples & Integration Tests

Include example apps in /examples/js/:
- Web ingestion form
- CLI for querying records
- Verification script using verifyProof()
Integration tests executed via Playwright or Jest.
✅ Acceptance Criteria
- Examples verified during build process.
- Test coverage ≥ 80 %.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-SDK-001:

Fully functional .NET and JS/TS SDKs published to NuGet and npm.
SDKs validated against live ATP Gateway APIs.
Authentication, retry, and correlation logic verified end-to-end.
CI/CD pipelines automate packaging and versioned releases.
Developer samples, documentation, and integration tests complete.
SDK telemetry integrated with OpenTelemetry and Application Insights.

Epic `AUD-WEBHOOK-001` : Webhooks Microservice¶

Epic Description¶

This epic introduces the Webhooks Microservice — a critical integration component of the Audit Trail Platform (ATP) that allows tenants and external systems to receive real-time notifications when key audit events occur. It provides subscription management APIs, a secure and resilient delivery engine, and guarantees message authenticity through HMAC signatures and retry/DLQ mechanisms. This service enables downstream workflows such as alerting, analytics, and synchronization with external systems like SIEM, compliance dashboards, or ticketing platforms.

Epic Objectives¶

Implement a multi-tenant webhook subscription system with event filtering and authentication.
Deliver real-time event notifications for audit lifecycle events (append, export, verify, etc.).
Guarantee secure delivery via signed requests using HMAC SHA-256.
Ensure idempotent, reliable message delivery with retries and dead-letter queues.
Provide observability, replay capabilities, and administrative control over subscription states.

Features¶

Feature `AUD-WH-SUB-001` – Subscription Management¶

Feature Description Provide APIs and storage mechanisms for managing webhook subscriptions per tenant. Subscriptions define event types, target URLs, authentication modes, and delivery preferences.

Tasks¶

Task AUD-WH-SUB-T001 – Create Subscription API

Endpoints:
- POST /api/webhooks/subscriptions – create new subscription
- GET /api/webhooks/subscriptions/{id} – retrieve subscription
- DELETE /api/webhooks/subscriptions/{id} – delete subscription
- GET /api/webhooks/subscriptions – list active subscriptions per tenant
Validate:
- Target URL format, authentication type (HMAC, OAuth2), event types, and retry policy.
✅ Acceptance Criteria
- Tenants can manage subscriptions via secure APIs.
- Subscriptions persisted in webhook_subscription table.
- Input validation errors return 400 Bad Request with structured problem details.

Task AUD-WH-SUB-T002 – Implement Event Type Registry

Maintain a registry of supported webhook event types:
- audit.record.appended
- audit.record.verified
- audit.export.completed
- audit.policy.executed
Provide endpoint /api/webhooks/events to retrieve available event types.
✅ Acceptance Criteria
- Registry dynamically updatable without redeployments.
- Event types documented in /docs/webhooks/events.md.

Task AUD-WH-SUB-T003 – Add Subscription Validation Workflow

On subscription creation, send a challenge handshake to verify endpoint ownership:
- Include a random token; endpoint must echo token to confirm registration.
✅ Acceptance Criteria
- Only validated endpoints become active.
- Validation failures marked with status = Unverified in DB.

Feature `AUD-WH-DEL-001` – Delivery Engine¶

Feature Description Implement a resilient, asynchronous delivery mechanism that dispatches webhook payloads to subscriber endpoints securely, efficiently, and with full observability.

Tasks¶

Task AUD-WH-DEL-T001 – Implement HMAC Signatures

Compute HMAC SHA-256 signature for each message using tenant’s secret key.
Include headers:
- X-Audit-Signature: sha256=<signature>
- X-Audit-Timestamp
Verify signature validity window (±5 min skew).
✅ Acceptance Criteria
- Signatures verified successfully by reference clients.
- Documentation includes example signature computation.

Task AUD-WH-DEL-T002 – Implement Delivery Worker and Retry Logic

Use background worker to dispatch events asynchronously.
Retry on network/timeouts (exponential backoff: 5s, 15s, 60s).
Mark message as failed after 5 unsuccessful attempts.
✅ Acceptance Criteria
- Delivery retries logged and visible in observability dashboards.
- Retry behavior verified via integration tests.

Task AUD-WH-DEL-T003 – Configure Dead-Letter Queue (DLQ) for Failed Deliveries

Persist permanently failed webhook deliveries in webhook_dlq table.
Include metadata: event ID, target URL, last response, timestamp.
Expose API:
- GET /api/webhooks/dlq – list dead letters
- POST /api/webhooks/replay/{eventId} – manual replay
✅ Acceptance Criteria
- Failed deliveries viewable and replayable via API.
- DLQ retention policy configurable (default 7 days).

Task AUD-WH-DEL-T004 – Add Delivery Observability & Metrics

Metrics:
- webhook_deliveries_total, webhook_failures_total, webhook_retry_count, webhook_latency_seconds.
Logs enriched with tenant_id, event_type, delivery_status.
✅ Acceptance Criteria
- Metrics and logs visible in Prometheus and Grafana.
- Alert triggers when failure rate > 5 %.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-WEBHOOK-001:

Multi-tenant webhook subscription APIs operational and documented.
HMAC-signed webhook messages securely delivered to subscribers.
Reliable delivery engine with retries, DLQ, and replay capability implemented.
Observability metrics and dashboards operational for webhook performance.
Event type registry and validation workflows functional across environments.

Epic `AUD-REPLAY-001` : Replay & Backfill Microservice¶

Epic Description¶

This epic introduces the Replay & Backfill Microservice, designed to restore, reprocess, or rebuild audit data streams for specific tenants or time periods. It enables selective replay of audit events to downstream consumers (such as Search, Integrity, or Analytics microservices) and controlled backfill operations from archived storage. This capability is essential for disaster recovery, schema migrations, and compliance verification scenarios, ensuring data integrity and completeness without introducing duplication.

Epic Objectives¶

Provide controlled replay of audit records by tenant, time range, or event type.
Support backfill loading from archival storage (Blob/S3).
Ensure idempotent event emission and protection against duplicate data.
Integrate with MassTransit and outbox patterns for reliable replays.
Log, monitor, and audit all replay and backfill operations for traceability.
Enable administrators to trigger and monitor replay jobs securely via API or UI.

Features¶

Feature `AUD-REP-CTL-001` – Replay Controller¶

Feature Description Provide APIs and orchestration logic to replay audit events selectively from the storage or archive layers to target microservices. Support scheduling, filtering, and progress tracking for long-running replay jobs.

Tasks¶

Task AUD-REP-CTL-T001 – Implement Selective Replay by Date/Tenant

Endpoints:
- POST /api/replay/start – initiate replay job
- GET /api/replay/{jobId} – retrieve status
- DELETE /api/replay/{jobId} – cancel running job
Replay filters:
- tenant_id, from_timestamp, to_timestamp, event_type.
Publish replayed events to configured internal topics (e.g., audit.record.appended.replay).
✅ Acceptance Criteria
- Replay initiates successfully per tenant and time range.
- Replayed records maintain original order and metadata.
- Replay progress and statistics queryable via API.

Task AUD-REP-CTL-T002 – Implement Replay Job Scheduler

Schedule replays as background jobs (Hangfire/Azure Durable Functions).
Store replay metadata: job ID, tenant, time window, target stream, status, and counters.
✅ Acceptance Criteria
- Multiple replay jobs execute concurrently without conflict.
- Replay job metadata persisted and recoverable after restart.

Task AUD-REP-CTL-T003 – Add Replay Observability

Metrics:
- replayed_records_total, replay_duration_seconds, replay_failures_total.
Expose Grafana dashboards to visualize replay throughput and duration.
✅ Acceptance Criteria
- Replay metrics visible in Grafana within 10 seconds of job execution.
- Alerts configured for failed or stalled replays.

Feature `AUD-REP-JOB-001` – Backfill Loader¶

Feature Description Implement background processing to backfill audit data from archived or external storage sources into the active audit pipeline. Ensure idempotent ingestion, deduplication, and integrity validation during restore operations.

Tasks¶

Task AUD-REP-JOB-T001 – Implement Backfill Loader for Archived Data

Load from archived sources (Azure Blob/S3) by manifest:
- audit_archive_manifest
- record_count, checksum, partition_date.
Validate each record against stored checksum before re-ingestion.
✅ Acceptance Criteria
- Backfill job restores archived partitions accurately.
- Manifest and checksum validation succeeds for all records.

Task AUD-REP-JOB-T002 – Guard Against Duplication

Implement deduplication checks based on composite key:
- (tenant_id, record_id, timestamp)
Maintain replay ledger in DB (audit_replay_log) to track previously replayed records.
✅ Acceptance Criteria
- No duplicate events emitted or stored during replay/backfill.
- Deduplication logic validated via integration tests.

Task AUD-REP-JOB-T003 – Support Replay to Target Microservice

Allow replay routing to one or more targets (e.g., Query, Search, Integrity).
Define payload contract versioning to ensure compatibility.
✅ Acceptance Criteria
- Target-specific replays successfully consumed by subscribers.
- Backward compatibility maintained across schema versions.

Task AUD-REP-JOB-T004 – Implement Replay Governance & Authorization

Restrict replay and backfill APIs to administrators (audit.manage scope).
Log all actions in compliance audit stream with correlation IDs.
✅ Acceptance Criteria
- Unauthorized users receive 403 responses.
- Replay and backfill actions fully auditable.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-REPLAY-001:

Replay controller with selective replay API, scheduling, and observability completed.
Backfill loader operational with checksum validation and deduplication safeguards.
Replays and backfills tracked, logged, and auditable through unified dashboards.
Secure governance enforced for replay execution and authorization.
Replay and backfill subsystems validated for performance, reliability, and integrity.

Epic `AUD-ADMIN-001` : Admin Console¶

Epic Description¶

This epic introduces the Audit Trail Platform Admin Console, a unified web-based control plane for administrators, support engineers, and compliance officers. The console provides both a web UI and administrative APIs for managing tenants, configurations, policies, exports, webhooks, and replay operations. It integrates with the platform’s Identity and Policy systems for secure, role-based visibility and control across all bounded contexts.

Epic Objectives¶

Deliver a centralized web portal for ATP administration and monitoring.
Expose administrative APIs for automation and integration with external management tools.
Provide role-based access to features (Audit Admin, Compliance Officer, Support Agent).
Surface operational insights—active tenants, system health, recent jobs, quota stats.
Support self-service for authorized users: replay, export management, and policy control.
Integrate OpenTelemetry, IAM, and configuration management into the admin layer.

Features¶

Feature `AUD-ADM-UI-001` – Web Portal¶

Feature Description Develop the web-based Admin Console UI using Blazor (for internal deployments) or React (for hosted SaaS environments). The portal provides secure dashboards, management panels, and search capabilities across all audit-related entities.

Tasks¶

Task AUD-ADM-UI-T001 – Implement Blazor/React UI Scaffold

Scaffold UI project ConnectSoft.AuditTrail.AdminPortal.
Core sections:
- Dashboard (system health, active tenants).
- Tenants & Editions.
- Audit Logs & Metrics.
- Policy, Export, Webhook, and Replay management.
Integrate with ATP Gateway for API calls using secure tokens.
✅ Acceptance Criteria
- UI scaffold compiles and deploys via CI/CD pipeline.
- Initial dashboard loads tenant and system statistics from APIs.

Task AUD-ADM-UI-T002 – Integrate Role-Based Sections

Roles and sections:
- Admin – full access (tenants, storage, replay).
- ComplianceOfficer – retention, integrity, export, and verification.
- SupportAgent – read-only for diagnostics.
Use role claims propagated via IAM tokens.
✅ Acceptance Criteria
- Users see only authorized navigation items and actions.
- Unauthorized sections hidden in UI and blocked server-side.

Task AUD-ADM-UI-T003 – Add Telemetry and Audit Integration

Integrate OpenTelemetry for UI-to-backend tracing.
Log user actions (login, configuration changes, replay triggers) to the audit stream.
✅ Acceptance Criteria
- All admin actions traceable to user identity and correlation ID.
- Frontend telemetry visible in Application Insights.

Task AUD-ADM-UI-T004 – Create Dashboard Visualizations

Add charts for:
- Active tenants and recent onboardings.
- Export and replay job status.
- Policy and retention activity trends.
Build using Chart.js or Recharts.
✅ Acceptance Criteria
- Dashboards render real-time data using live API calls.
- Visuals optimized for responsive display.

Feature `AUD-ADM-API-001` – Admin APIs¶

Feature Description Develop secure administrative APIs to expose internal system functions programmatically. APIs enable DevOps and compliance teams to automate configuration, monitoring, and maintenance tasks.

Tasks¶

Task AUD-ADM-API-T001 – Implement Admin API Endpoints

Endpoints:
- GET /api/admin/system/status – system metrics and uptime
- GET /api/admin/jobs – list active/recent jobs (export, replay, purge)
- POST /api/admin/policies/execute – force policy execution
- POST /api/admin/tenants/{id}/sync – refresh tenant metadata
Restrict access to audit.manage scope.
✅ Acceptance Criteria
- All endpoints secured by IAM and role claims.
- Results include correlation and trace headers.

Task AUD-ADM-API-T002 – Integrate with Configuration & Telemetry Services

Read/write configurations through External Configuration microservice.
Expose telemetry data from OpenTelemetry metrics endpoints.
✅ Acceptance Criteria
- API responses include live configuration and telemetry details.
- Performance impact < 3 % baseline latency.

Task AUD-ADM-API-T003 – Implement Pagination, Filtering, and Export

Support pagination for all list APIs (e.g., /api/admin/jobs).
Enable CSV/JSON export for compliance reviews.
✅ Acceptance Criteria
- APIs return paginated and filterable results.
- Exports match Admin Console UI views exactly.

Task AUD-ADM-API-T004 – Add Admin Observability and Audit Logging

Log all administrative API invocations with:
- User ID, tenant ID (if applicable), action type, duration, result.
Send logs to audit trail stream and Application Insights.
✅ Acceptance Criteria
- Every admin action appears in audit log within 5 seconds.
- Observability dashboards include admin activity breakdown.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-ADMIN-001:

Fully functional Admin Console UI (Blazor/React) deployed via CI/CD.
Role-based sections dynamically rendered based on IAM claims.
Administrative APIs operational with secured access and logging.
Integration with telemetry, configuration, and audit trail streams complete.
Dashboards provide live visibility into system and tenant-level operations.
Admin activity traceable end-to-end through observability stack.

Epic `AUD-NOTIFY-001` : Notification Service¶

Epic Description¶

This epic introduces the Notification Service for the Audit Trail Platform (ATP), responsible for alerting administrators, compliance officers, and tenant users about critical audit-related events. It centralizes the management of notification triggers, subscriptions, and multi-channel delivery (email, webhook, chat). The service integrates with the platform’s event bus, ensuring that key activities such as policy violations, failed exports, integrity anomalies, or replay completions generate actionable notifications.

Epic Objectives¶

Provide configurable notification triggers and subscription rules per tenant and role.
Support multiple delivery channels—email, webhook, Teams/Slack, or SMS (future-ready).
Integrate with external providers (SendGrid, Azure Communication Services, Twilio).
Guarantee reliable, deduplicated delivery with observability metrics.
Expose APIs for managing subscriptions, templates, and delivery status.
Ensure all notifications are logged and auditable via ATP streams.

Features¶

Feature `AUD-NTF-TRG-001` – Triggers & Subscriptions¶

Feature Description Allow tenants and system administrators to define notification triggers for specific audit events or system conditions (e.g., policy purge, replay complete, failed integrity check). Include subscription management APIs and internal event bus integration.

Tasks¶

Task AUD-NTF-TRG-T001 – Emit Notification Events

Subscribe to key event topics from other services:
- audit.policy.executed
- audit.export.failed
- audit.integrity.alert
- audit.replay.completed
Translate raw domain events into standardized notification envelopes.
Publish notification.created events to Notification Service bus.
✅ Acceptance Criteria
- Notification events emitted for all defined triggers.
- Event schema validated and versioned in /schemas/notifications.

Task AUD-NTF-TRG-T002 – Implement Subscription Management API

Endpoints:
- POST /api/notifications/subscriptions – create subscription
- GET /api/notifications/subscriptions – list by tenant
- DELETE /api/notifications/subscriptions/{id} – cancel
Subscription attributes: tenant_id, event_type, channel, recipients, filters.
✅ Acceptance Criteria
- Tenants can manage notification rules via secure APIs.
- Subscriptions persisted and enforced per tenant.

Task AUD-NTF-TRG-T003 – Add Trigger Evaluation Logic

Implement condition checks for notification rules:
- Example: if (event_type == 'audit.export.failed' && tenant.edition == 'Enterprise').
Support custom filters by metadata (e.g., resource type, location).
✅ Acceptance Criteria
- Trigger logic accurately filters and routes eligible events.
- Evaluation latency < 200 ms per rule under load.

Feature `AUD-NTF-CHAN-001` – Email/Webhook Channels¶

Feature Description Implement modular delivery channels for notifications. Initial channels: email (via external provider) and webhook (custom endpoints). Future versions can add chat or SMS integrations.

Tasks¶

Task AUD-NTF-CHAN-T001 – Integrate with External Providers

Providers:
- Email – SendGrid / Azure Communication Services.
- Webhook – signed HTTPS delivery with HMAC verification.
Use provider adapters for extensibility.
✅ Acceptance Criteria
- Provider integration tested end-to-end in sandbox mode.
- Failures logged and retried according to policy.

Task AUD-NTF-CHAN-T002 – Implement Email Delivery Templates

Templates for common events:
- Policy Executed Summary
- Export Completed
- Integrity Failure Alert
- Replay Job Finished
Support dynamic variables (tenant name, date, count, link).
✅ Acceptance Criteria
- Emails localized and templated using Razor or Handlebars.
- Template rendering covered by unit and visual tests.

Task AUD-NTF-CHAN-T003 – Implement Delivery Worker & Retry Policy

Deliver notifications asynchronously via background workers.
Retries: exponential backoff (5s, 15s, 60s).
Dead-letter queue for failed notifications after 5 attempts.
✅ Acceptance Criteria
- Delivery success rate ≥ 99 %.
- Failed notifications appear in /api/notifications/dlq.

Task AUD-NTF-CHAN-T004 – Add Observability & Metrics

Metrics:
- notifications_sent_total, notifications_failed_total, notifications_latency_seconds.
Integrate with Grafana dashboards.
✅ Acceptance Criteria
- Metrics and failure alerts visible in observability stack.
- Dashboards display delivery success rate per channel.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-NOTIFY-001:

Multi-tenant notification subsystem operational across ATP.
Configurable triggers and subscription management APIs functional.
Email and webhook channels integrated with retries and DLQ.
Event schemas versioned and documented in /schemas/notifications.
Metrics, dashboards, and alerting pipelines operational.
Notification delivery validated via end-to-end integration tests.

Epic `AUD-CFG-001` : Dynamic Configuration Service¶

Epic Description¶

This epic introduces the Dynamic Configuration Service for the Audit Trail Platform (ATP), enabling centralized and tenant-aware runtime configuration management across all audit microservices. It provides APIs and integrations for managing feature flags, service parameters, and operational policies in real time—without redeployment. The service builds upon the existing ConnectSoft External Configuration Platform, extending it with multi-tenant and edition-aware configuration overrides for audit-specific modules.

Epic Objectives¶

Centralize configuration management for all ATP microservices (Ingestion, Query, Storage, etc.).
Provide feature flags and dynamic settings controllable per environment and tenant.
Support tenant- and edition-based overrides for custom behaviors.
Ensure all configuration changes are auditable, versioned, and propagated in real time.
Integrate with the ConnectSoft External Configuration Service (ECS) for consistency across the SaaS ecosystem.

Features¶

Feature `AUD-CFG-FLAG-001` – Feature Flags for Audit Components¶

Feature Description Implement audit-domain feature flags to enable or disable functionality dynamically (e.g., query caching, policy auto-execution, webhook broadcasting). Feature flags allow controlled rollouts, safe experimentation, and environment-specific toggles.

Tasks¶

Task AUD-CFG-FLAG-T001 – Use External Configuration Platform Integration

Integrate with ConnectSoft ECS SDK for distributed configuration storage and flag evaluation.
Register audit-specific feature namespaces:
- Audit.Ingestion.*
- Audit.Query.*
- Audit.Export.*
Implement configuration refresh middleware for all services.
✅ Acceptance Criteria
- All audit microservices read configuration via ECS.
- Flag changes applied dynamically without restarts.
- ECS synchronization latency < 10 seconds.

Task AUD-CFG-FLAG-T002 – Implement Feature Flag Evaluation API

Endpoint:
- GET /api/config/features – list current flag states.
- POST /api/config/features/evaluate – check flag value by service or tenant.
✅ Acceptance Criteria
- Evaluation API returns accurate and consistent values.
- API covered by integration tests across all environments.

Task AUD-CFG-FLAG-T003 – Implement Safe Rollout & Kill-Switch Support

Support percentage-based rollouts (e.g., 10 % tenants) and immediate disable.
Enable emergency rollback through ECS UI or Admin Console.
✅ Acceptance Criteria
- Partial rollout tested and validated via simulation.
- Emergency flag toggle propagates in < 10 seconds platform-wide.

Feature `AUD-CFG-PROP-001` – Runtime Configuration API¶

Feature Description Provide APIs for reading, overriding, and auditing configuration values at runtime. This feature allows both platform operators and tenant administrators (depending on permissions) to adjust settings dynamically.

Tasks¶

Task AUD-CFG-PROP-T001 – Implement Tenant-Aware Overrides

Allow per-tenant configuration overrides for keys such as:
- RetentionPeriod, WebhookRetryCount, MaxExportSize, etc.
Configuration hierarchy:
- Global defaults → Edition overrides → Tenant overrides.
✅ Acceptance Criteria
- Tenant-specific configuration resolution verified via tests.
- Overrides persisted and reloaded correctly across service restarts.

Task AUD-CFG-PROP-T002 – Expose Runtime Configuration Management API

Endpoints:
- GET /api/config – retrieve current effective configuration.
- PUT /api/config/{key} – update specific property (requires audit.manage scope).
- GET /api/config/history/{key} – view configuration change history.
✅ Acceptance Criteria
- Authorized administrators can modify runtime configurations securely.
- Change history includes author, timestamp, old/new values, and tenant context.

Task AUD-CFG-PROP-T003 – Implement Configuration Change Events

Publish events:
- config.value.changed
- config.flag.toggled
Consumers (microservices) subscribe and apply changes in-memory.
✅ Acceptance Criteria
- Configuration updates propagated instantly across services.
- No manual restarts required after configuration updates.

Task AUD-CFG-PROP-T004 – Integrate Configuration with Observability & Audit Trail

Emit metrics:
- config_updates_total, config_errors_total, config_latency_seconds.
Record all configuration changes into the audit stream as audit.config.changed events.
✅ Acceptance Criteria
- All configuration updates traceable in audit logs and Grafana dashboards.
- Configuration observability integrated with OpenTelemetry stack.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-CFG-001:

Dynamic configuration service fully integrated with ECS and ATP microservices.
Tenant- and edition-aware configuration overrides operational.
Real-time configuration propagation verified across all services.
APIs for feature flag management and runtime configuration adjustments deployed.
Configuration changes versioned, audited, and observable through dashboards.
System validated for security, reliability, and dynamic consistency.

Epic `AUD-COMPLIANCE-001` : Compliance Profiles¶

Epic Description¶

This epic introduces Compliance Profiles for the Audit Trail Platform (ATP), providing pre-configured overlays that enforce audit, retention, and access rules aligned with major regulatory frameworks such as SOC 2, GDPR, and HIPAA. These profiles serve as compliance templates that can be applied per tenant, edition, or region — automatically configuring default retention periods, encryption requirements, access control rules, and breach notification workflows. The Compliance Profiles ensure that ATP deployments across industries meet mandatory security and data governance standards.

Epic Objectives¶

Provide standardized compliance overlays (SOC2, GDPR, HIPAA) for ATP tenants.
Define default retention, redaction, and access rules per compliance framework.
Implement a policy enforcement engine that validates configurations and runtime behaviors against active profiles.
Integrate compliance logs and policy checks into the platform’s audit stream.
Enable administrators to assign and switch compliance profiles dynamically per tenant.

Features¶

Feature `AUD-CMP-SOC2-001` – SOC2 Overlay¶

Feature Description Define a compliance overlay ensuring auditability, availability, and integrity as required by SOC 2 Type II controls. This profile enforces stricter observability, access logging, and data retention rules for enterprise tenants.

Tasks¶

Task AUD-CMP-SOC2-T001 – Define Retention & Access Defaults per Profile

Default retention: 12–24 months (configurable).
Require multi-factor admin authentication for export/replay actions.
Enforce immutability for stored audit records (append-only).
✅ Acceptance Criteria
- SOC2 tenants automatically inherit longer retention and stronger access requirements.
- Configuration verified by compliance tests in CI pipeline.

Task AUD-CMP-SOC2-T002 – Implement Policy Enforcement Engine

Create compliance ruleset evaluating key categories:
- Logging completeness, storage encryption, admin access tracking.
Run periodic compliance audits with results published as compliance.soc2.report.generated events.
✅ Acceptance Criteria
- Noncompliance detected and reported automatically.
- Reports exportable via Admin Console or API.

Feature Description Define and enforce General Data Protection Regulation (GDPR) requirements for EU tenants, focusing on data minimization, consent, erasure, and residency controls.

Tasks¶

Task AUD-CMP-GDPR-T001 – Define GDPR Policy Presets

Default retention: 180 days.
Enable right-to-be-forgotten operations (subject record removal tokens).
Enforce EU data residency for audit record storage.
✅ Acceptance Criteria
- Tenants under GDPR automatically restricted to EU-located partitions.
- Erasure requests correctly invalidate associated records.

Task AUD-CMP-GDPR-T002 – Implement Access Request Workflow

Endpoint:
- POST /api/compliance/gdpr/access-request
Generate access logs for requested data and expiration after 30 days.
✅ Acceptance Criteria
- GDPR access and erasure workflows tested for completeness.
- All actions logged to compliance.audit stream.

Task AUD-CMP-GDPR-T003 – Add Consent & Breach Notification Logic

Record consent grant/revoke events in compliance registry.
Configure notification engine to alert admins within 72 hours of detected breach.
✅ Acceptance Criteria
- Breach notifications automatically triggered from Security service.
- Consent logs queryable by tenant and subject ID.

Feature `AUD-CMP-HIPAA-001` – HIPAA Overlay¶

Feature Description Define the Health Insurance Portability and Accountability Act (HIPAA) compliance overlay for healthcare-related tenants, ensuring secure handling of PHI (Protected Health Information) in audit data.

Tasks¶

Task AUD-CMP-HIPAA-T001 – Define HIPAA Security and Retention Defaults

Default retention: 6 years (per 45 CFR §164.316(b)(2)(i)).
Require encryption in transit and at rest for all PHI.
Enforce restricted role-based access for PHI-related events.
✅ Acceptance Criteria
- HIPAA-compliant encryption verified via automated checks.
- PHI access events logged and auditable.

Task AUD-CMP-HIPAA-T002 – Implement PHI Data Handling Rules

Mask PHI fields in query/export results (e.g., patient names, identifiers).
Integrate with Redaction Engine (AUD-SEC-MASK-001).
✅ Acceptance Criteria
- PHI never visible to unauthorized users.
- Redaction policy enforced automatically at runtime.

Task AUD-CMP-HIPAA-T003 – Integrate Compliance Monitoring and Alerts

Create dashboard panels for compliance health: SOC2 / GDPR / HIPAA coverage status.
Emit compliance.violation.detected events for alerting systems.
✅ Acceptance Criteria
- Violations appear within observability dashboard in near real time.
- Alerts dispatched via Notification Service when compliance breaches occur.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-COMPLIANCE-001:

SOC2, GDPR, and HIPAA compliance profiles implemented and assignable per tenant.
Policy enforcement engine operational with periodic compliance checks.
Retention, access, and encryption defaults auto-applied by active profile.
Compliance logs and alerts integrated into Notification and Admin systems.
Dashboards and audit reports available to compliance officers via Admin Console.

Epic `AUD-CHAOS-001` : Performance & Chaos Engineering¶

Epic Description¶

This epic establishes the Performance and Chaos Engineering practices for the Audit Trail Platform (ATP). It introduces automated load testing, resiliency validation, and chaos experimentation to ensure that the platform remains stable, performant, and fault-tolerant under heavy traffic and failure conditions. Through systematic stress, endurance, and fault injection testing, this initiative validates the robustness of ingestion, storage, and query pipelines while providing quantitative metrics for scalability and reliability SLAs.

Epic Objectives¶

Develop an automated load testing suite for high-throughput ingestion and query workloads.
Simulate real-world tenant traffic patterns with mixed read/write ratios.
Implement chaos scenarios to test recovery from network, infrastructure, and dependency failures.
Measure latency, throughput, and failure recovery times under controlled experiments.
Integrate load and chaos tests into CI/CD pipelines for continuous performance validation.
Use telemetry to identify bottlenecks and optimize scaling strategies.

Features¶

Feature `AUD-PERF-LOAD-001` – Load Testing Suite¶

Feature Description Build a comprehensive load testing suite to validate the scalability and performance of the ATP microservices under realistic and extreme workloads. The suite must simulate multi-tenant traffic, distributed ingestion, concurrent queries, and event-driven backpressure across service boundaries.

Tasks¶

Task AUD-PERF-LOAD-T001 – Create K6 Load Tests

Develop K6-based scripts for:
- Ingestion API: append 10k–100k audit records/sec across tenants.
- Query API: filter/sort/paginate under load with 100 concurrent users.
- Storage service: batch persistence performance and partition rollover timing.
Configure test data generation (tenant IDs, random events, timestamps).
Integrate thresholds:
- p95 < 300ms, error_rate < 1%, throughput >= target.
✅ Acceptance Criteria
- Load test suite runs via CLI and CI/CD pipeline (k6 run).
- Reports export to Grafana dashboards (via InfluxDB or Prometheus).

Task AUD-PERF-LOAD-T002 – Implement Endurance and Stress Scenarios

Schedule long-running (12–24h) tests to detect memory leaks, deadlocks, or connection exhaustion.
Include burst traffic simulation and scale-in/out transitions for containers.
✅ Acceptance Criteria
- System sustains continuous load without degradation.
- Metrics confirm horizontal scaling behaves predictably under spikes.

Task AUD-PERF-LOAD-T003 – Automate Load Test Reports & Baselines

Export test results as structured JSON for baseline comparison.
Store baseline results in /reports/performance/ per service.
Generate visual regression dashboards (Grafana + k6 Cloud optional).
✅ Acceptance Criteria
- Performance trends measurable across releases.
- Baseline threshold deviations automatically flagged in CI.

Feature `AUD-PERF-CHAOS-001` – Chaos Automation¶

Feature Description Integrate Azure Chaos Studio experiments and synthetic fault injection to validate ATP’s fault tolerance and recovery mechanisms. Chaos experiments simulate dependency failures (SQL, Service Bus, Redis, Key Vault), network disruptions, and pod restarts to ensure system resilience.

Tasks¶

Task AUD-PERF-CHAOS-T001 – Integrate Azure Chaos Studio Scenarios

Configure chaos experiments targeting:
- Audit Ingestion Service – simulate SQL throttling.
- Audit Storage Service – inject blob latency faults.
- Audit Gateway – simulate Service Bus unavailability.
Automate experiment orchestration via Azure DevOps pipeline stages.
✅ Acceptance Criteria
- Chaos experiments reproducible and safe (using defined blast radius).
- Service health automatically validated post-injection.

Task AUD-PERF-CHAOS-T002 – Implement Recovery & Self-Healing Validation

Monitor health probes and retry policies during fault injection.
Validate automatic recovery of background jobs and message processors.
✅ Acceptance Criteria
- System auto-recovers within defined SLA (< 60s).
- No data loss or duplicate audit records observed post-failure.

Task AUD-PERF-CHAOS-T003 – Establish Resilience Scorecards

Define resilience KPIs:
- Recovery Time Objective (RTO)
- Recovery Point Objective (RPO)
- Failure rate, retry success ratio
Automate scorecard generation after each chaos session.
✅ Acceptance Criteria
- Scorecards available in /reports/chaos/ and Grafana dashboards.
- SLA conformance validated per service release.

Task AUD-PERF-CHAOS-T004 – Integrate Chaos Testing in CI/CD

Add nightly chaos and load validation stages:
- performance-test
- chaos-validation
Publish artifacts (reports, screenshots, metrics).
✅ Acceptance Criteria
- CI/CD pipeline automatically executes chaos experiments.
- Build fails if recovery time exceeds SLA threshold.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-CHAOS-001:

Full K6-based load testing suite deployed and automated in CI/CD.
Endurance and stress testing validated across ingestion, query, and storage paths.
Azure Chaos Studio scenarios operational for controlled fault injection.
Recovery and self-healing behavior validated against defined SLAs.
Performance baselines and resilience scorecards integrated into observability stack.
Continuous performance and chaos testing embedded in platform release lifecycle.

Epic `AUD-OPS-002` : Operations & Monitoring¶

Epic Description¶

This epic introduces the Operations and Monitoring foundation for the Audit Trail Platform (ATP). It focuses on the creation of standardized runbooks, playbooks, and monitoring workflows to support platform operations, reduce incident resolution time, and ensure system reliability in production. These operational artifacts will serve DevOps, SRE, and support teams as part of the platform’s day-2 operational maturity model.

Epic Objectives¶

Deliver detailed runbooks for deployment, rollback, recovery, and backup/restore.
Define incident response and escalation playbooks for all critical ATP components.
Implement alert routing, severity classification, and on-call escalation rules.
Integrate observability tools (Grafana, Application Insights, Azure Monitor) with actionable alert pipelines.
Maintain operational readiness through automated checklists and scheduled validation tests.
Align all operations documentation with SOC2 and ISO 27001 compliance standards.

Features¶

Feature `AUD-OPS-RUN-001` – Runbooks¶

Feature Description Provide comprehensive runbooks describing operational procedures for all ATP services. These guides document how to deploy, monitor, recover, and roll back components in different environments (Dev, Stage, Prod).

Tasks¶

Task AUD-OPS-RUN-T001 – Deployment, Rollback, Backup/Restore Guides

Create markdown-based runbooks in /docs/ops/runbooks/ covering:
- Deployment (manual + automated via CI/CD pipelines).
- Rollback process for failed releases.
- Backup/restore for databases, blob archives, and configuration states.
Include automation scripts (Bash/PowerShell) for one-click execution.
✅ Acceptance Criteria
- All runbooks peer-reviewed by DevOps and QA teams.
- Procedures tested successfully in non-prod environments.

Task AUD-OPS-RUN-T002 – Service Health Validation Scripts

Implement diagnostic scripts to verify service health:
- API Gateway connectivity.
- Message bus latency and queue depth.
- DB partition and storage capacity thresholds.
Integrate checks into pre-deployment and post-deployment pipeline steps.
✅ Acceptance Criteria
- Validation scripts return clear pass/fail summary.
- All services meet defined operational health KPIs before release.

Task AUD-OPS-RUN-T003 – Disaster Recovery & Failover Procedures

Document failover process between Azure regions.
Include data restoration workflow for archived audit logs.
Simulate DR test at least once per quarter.
✅ Acceptance Criteria
- DR runbook validated during mock failover.
- RTO < 30 minutes, RPO < 5 minutes confirmed.

Feature `AUD-OPS-MON-001` – Monitoring Playbooks¶

Feature Description Develop operational playbooks detailing how to interpret alerts, triage incidents, and escalate to responsible teams. Provide alert routing and on-call management structure for 24/7 coverage.

Tasks¶

Task AUD-OPS-MON-T001 – Alert Routing & Escalation Matrix

Define alert severities (P1–P4) and routing logic:
- P1: Major outage – Notify on-call + Teams channel + SMS.
- P2: Partial service degradation – Notify Teams/Email.
- P3: Warning threshold – Ticket creation in Azure DevOps.
- P4: Info – Logged only.
Document escalation policy by role: DevOps → SRE → Platform Owner → CTO.
✅ Acceptance Criteria
- Escalation matrix documented in /docs/ops/alerts-matrix.md.
- Alert routing configured in Grafana Alertmanager and Azure Monitor.

Task AUD-OPS-MON-T002 – Define Monitoring Dashboards and KPIs

Core dashboards:
- System Health (CPU, memory, network latency).
- Queue and Job Processing (MassTransit, Hangfire).
- Audit Throughput and Error Rate (Ingestion/Storage).
KPIs:
- P95 latency < 300 ms, error rate < 1 %.
✅ Acceptance Criteria
- Dashboards shared with all support and DevOps teams.
- Alert thresholds configured and validated in test environment.

Task AUD-OPS-MON-T003 – Implement Runbook Links in Alerts

Add runbook_url field in alert annotations for each monitored component.
Alerts automatically include troubleshooting links.
✅ Acceptance Criteria
- Each alert links to corresponding runbook section.
- Engineers can resolve issues without manual lookup.

Task AUD-OPS-MON-T004 – Postmortem & Continuous Improvement Workflow

Implement post-incident analysis template (/docs/ops/postmortem-template.md).
Schedule review sessions for critical incidents (P1/P2).
✅ Acceptance Criteria
- Each major incident produces a postmortem document.
- Identified improvements tracked in Azure DevOps backlog.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-OPS-002:

Complete operational runbooks covering deployment, rollback, and recovery.
Automated service health validation integrated into CI/CD.
Monitoring playbooks and escalation matrix published and tested.
Grafana dashboards and alert routing fully configured.
DR and failover procedures validated under real-world simulation.
Postmortem process operationalized and linked to backlog improvements.

Epic `AUD-DATA-001` : Data Migration & Seeding¶

Epic Description¶

This epic establishes the Data Migration and Seeding mechanisms for the Audit Trail Platform (ATP). It ensures that initial and ongoing data setup across environments (Dev, Stage, Prod) is consistent, reproducible, and compliant with multi-tenant architecture. The epic includes tooling for schema migration, initial data seeding (test tenants, compliance profiles, feature flags), and versioned upgrades across microservices. These capabilities guarantee that all environments can be provisioned, upgraded, and tested automatically using standardized scripts.

Epic Objectives¶

Provide automated database schema migration tooling for all ATP microservices.
Support bootstrap seeding of tenants, editions, compliance profiles, and features.
Maintain environment consistency with versioned migration history.
Implement safe, idempotent migration scripts for multi-tenant systems.
Integrate migrations into CI/CD pipelines for automatic deployment.
Provide rollback and verification utilities to validate data integrity post-migration.

Features¶

Feature `AUD-DATA-INIT-001` – Bootstrap Data¶

Feature Description Create initial data setup required to initialize an environment, including baseline tenants, editions, feature flags, and compliance defaults. This ensures developers, testers, and operators can instantly bring up a working environment with realistic but synthetic data.

Tasks¶

Task AUD-DATA-INIT-T001 – Add Seeding for Test Tenants

Create seed data for:
- Tenants – DemoTenant1, ComplianceTestTenant, EnterpriseTenant.
- Editions – Free, Standard, Enterprise.
- Default compliance profiles – SOC2, GDPR, HIPAA.
Add optional mock audit data for testing ingestion and query flows.
✅ Acceptance Criteria
- Environments automatically populated with baseline tenants.
- Seeded data verified via API smoke tests post-deployment.

Task AUD-DATA-INIT-T002 – Implement Configurable Seeding Profiles

Allow environment-based seeding via configuration:
- seedMode = minimal | full | compliance-test.
Implement CLI command:
- dotnet run -- seed --profile full.
✅ Acceptance Criteria
- Seeding adaptable for CI, local dev, or staging scenarios.
- Repeat executions are idempotent (no duplicates).

Task AUD-DATA-INIT-T003 – Integrate Seeding with CI/CD

Add seeding as a post-deployment pipeline stage.
Automate rollback on seeding failure.
✅ Acceptance Criteria
- CI pipeline completes with seeded data for all test tenants.
- Failures logged and visible in deployment summary.

Feature `AUD-DATA-MIG-001` – Migration Tooling¶

Feature Description Develop standardized, version-controlled migration tooling for managing schema and data evolution across ATP’s distributed databases. The tooling ensures safe upgrades, rollbacks, and consistent structure across tenants and services.

Tasks¶

Task AUD-DATA-MIG-T001 – Implement Migration Scripts

Use NHibernate or FluentMigrator per microservice schema.
Maintain migration version table: schema_version.
Define naming convention: V{version}__{description}.sql.
Include both schema and data migrations for:
- Tenant, AuditRecord, Policy, and Export entities.
✅ Acceptance Criteria
- Migrations applied automatically at service startup.
- Migration history persisted and validated in each environment.

Task AUD-DATA-MIG-T002 – Add Migration CLI Utility

Create CLI tool audit-migrator supporting commands:
- migrate up – apply all pending migrations
- migrate down – rollback last migration
- migrate list – show applied versions
✅ Acceptance Criteria
- CLI utility packaged as .NET tool or Docker image.
- Commands logged to stdout and exported as artifacts in CI.

Task AUD-DATA-MIG-T003 – Validate Cross-Microservice Schema Consistency

Compare entity mappings across Ingestion, Storage, and Query schemas.
Verify consistent field naming, data types, and constraints.
✅ Acceptance Criteria
- Schema diff tool reports 0 inconsistencies across services.
- Validation included in nightly CI pipeline.

Task AUD-DATA-MIG-T004 – Implement Migration Observability

Emit metrics:
- migrations_applied_total, migration_duration_seconds, migration_failures_total.
Send migration audit logs to audit.config.changed stream.
✅ Acceptance Criteria
- Migration activity visible in observability dashboards.
- All migrations auditable and traceable by version and author.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-DATA-001:

Fully automated schema migration system implemented across ATP microservices.
Configurable seeding framework operational for test and staging environments.
Migrations integrated into CI/CD pipelines with rollback and observability.
Consistency validation ensures all service schemas remain synchronized.
Data seeding and migration actions logged to the audit trail for compliance.
Environments reproducible and consistent across Dev, Stage, and Prod.

Epic `AUD-SECOPS-001` : Security Operations¶

Epic Description¶

This epic implements the Security Operations (SecOps) foundation for the Audit Trail Platform (ATP), ensuring continuous protection of sensitive data, cryptographic assets, and operational integrity. It introduces automated key and secret rotation, incident response procedures, and security monitoring aligned with enterprise SOC2 and ISO 27001 standards. The initiative ensures that ATP maintains a strong security posture, rapid incident containment, and full auditability of security-related actions.

Epic Objectives¶

Automate key and secret rotation across all ATP environments using Azure Key Vault.
Define and document incident response playbooks for security events.
Establish monitoring, detection, and response workflows for compromised keys or suspicious access.
Log all SecOps activities to the centralized audit stream.
Ensure compliance with ConnectSoft’s enterprise security and governance policies.

Features¶

Feature `AUD-SECOPS-ROT-001` – Secret/Key Rotation¶

Feature Description Automate key and secret rotation processes to prevent credential reuse, reduce exposure risk, and meet compliance obligations. Integrate tightly with Azure Key Vault and enforce least-privilege access for all managed identities and service principals.

Tasks¶

Task AUD-SECOPS-ROT-T001 – Automate Key Rotation via Key Vault

Configure automatic key rotation policies in Azure Key Vault for:
- Service Bus SAS keys
- Storage Account access keys
- Database connection strings
- HMAC signing keys for Webhooks and Integrity Service
Rotation frequency:
- Critical secrets – 30 days
- Application keys – 90 days
✅ Acceptance Criteria
- All managed secrets enrolled in Key Vault rotation.
- Rotation completed without downtime or invalid credentials.
- Validation scripts confirm updated credentials across microservices.

Task AUD-SECOPS-ROT-T002 – Implement Key Rotation Pipeline Stage

Add pipeline stage security-rotate-keys to Azure DevOps release pipeline.
Rotate and verify secrets automatically during scheduled maintenance windows.
Notify Security and Ops channels upon rotation completion.
✅ Acceptance Criteria
- Key rotation pipeline runs automatically per schedule.
- Post-rotation validation passes successfully in all environments.

Task AUD-SECOPS-ROT-T003 – Log and Audit Rotation Events

Log rotation activities to centralized audit stream as security.key.rotated events.
Include metadata: key ID, rotation time, issuer, and target service.
✅ Acceptance Criteria
- Rotation events visible in audit trail and compliance dashboard.
- Audit data stored immutably for ≥ 12 months.

Feature `AUD-SECOPS-INC-001` – Incident Response¶

Feature Description Define the full incident response lifecycle—detection, triage, containment, eradication, and recovery—for security events affecting ATP services or data. Include procedural documentation, tooling integration, and post-incident review workflows.

Tasks¶

Task AUD-SECOPS-INC-T001 – Document Incident Handling

Create /docs/security/incident-response-playbook.md covering:
- Detection & triage workflows.
- Severity classification (SEV-1 to SEV-4).
- Containment and communication protocols.
- Evidence collection and root-cause analysis.
- Post-mortem and corrective-action tracking.
✅ Acceptance Criteria
- Playbook reviewed by Security and Compliance teams.
- All ATP engineers trained on SEV-1/SEV-2 response process.

Task AUD-SECOPS-INC-T002 – Integrate Security Monitoring & Alerts

Configure Azure Defender and Microsoft Sentinel alerts for:
- Failed authentication or excessive login attempts.
- Key Vault access anomalies.
- Suspicious data-access patterns or privilege escalation.
Link alerts to ticketing and on-call escalation workflows.
✅ Acceptance Criteria
- Alerts routed automatically to Security Operations channel.
- False-positive rate < 5 % confirmed through testing.

Task AUD-SECOPS-INC-T003 – Automate Post-Incident Reporting

Template: /docs/security/post-incident-report.md.
Automatically generate report when incident closes.
Include summary, timeline, impacted systems, and corrective actions.
✅ Acceptance Criteria
- Reports automatically attached to corresponding Azure DevOps work item.
- Security team approval required before closure.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-SECOPS-001:

Key and secret rotation automated via Azure Key Vault and DevOps pipelines.
All rotation and access events auditable in the centralized security stream.
Incident response playbooks documented, approved, and integrated into operations.
Security monitoring active through Azure Defender + Sentinel with actionable alerts.
Post-incident automation and compliance reports functional across all environments.

Epic `AUD-DOC-001` : Documentation & ADRs¶

Epic Description¶

This epic establishes the Documentation and Architecture Decision Records (ADRs) framework for the Audit Trail Platform (ATP). It formalizes all design, architecture, and operational documentation into a structured, version-controlled system powered by MkDocs. The goal is to ensure full transparency, traceability, and knowledge continuity across all teams working on ATP—spanning engineering, DevOps, security, and compliance.

Epic Objectives¶

Build and publish a central MkDocs documentation portal for ATP.
Maintain a living catalog of Architecture Decision Records (ADRs).
Automate documentation generation and publishing through CI/CD pipelines.
Keep docs aligned with each microservice’s lifecycle, configuration, and APIs.
Ensure that ADRs are discoverable, categorized, and version-controlled.
Comply with ConnectSoft’s internal “Documentation as Code” standards.

Features¶

Feature `AUD-DOC-MD-001` – MkDocs Site¶

Feature Description Create a MkDocs-based documentation portal consolidating technical guides, architecture overviews, API references, and operational procedures. The site serves as the single source of truth for all ATP microservices and shared components.

Tasks¶

Task AUD-DOC-MD-T001 – Publish Docs Pipeline

Create a pipeline (docs-publish.yml) to build and deploy MkDocs content automatically:
- Build on every main branch merge.
- Deploy static site to Azure Static Web Apps or GitHub Pages.
Integrate MkDocs Material theme with navigation and search.
✅ Acceptance Criteria
- Docs site automatically updated on commit to main.
- Version badge and build status visible in footer.

Task AUD-DOC-MD-T002 – Organize Documentation Structure

Structure folders:
- /docs/architecture/ – HLDs, C4 diagrams, blueprints.
- /docs/microservices/ – per-service API docs.
- /docs/ops/ – runbooks, DR, monitoring.
- /docs/security/ – IAM, key rotation, compliance overlays.
- /docs/adr/ – Architecture Decision Records.
✅ Acceptance Criteria
- Documentation site structured and consistent across all domains.
- Internal navigation verified by build check.

Task AUD-DOC-MD-T003 – Integrate API Reference Generation

Use OpenAPI/Swagger export for each microservice.
Generate API references with mkdocs-swagger-ui plugin.
✅ Acceptance Criteria
- REST/gRPC API documentation available in live MkDocs site.
- Generated docs synchronized with main branch automatically.

Feature `AUD-DOC-ADR-001` – Architecture Decision Records¶

Feature Description Introduce a standardized ADR workflow to capture and version key architectural decisions. Each ADR should follow a consistent markdown template and be automatically indexed within the documentation portal.

Tasks¶

Task AUD-DOC-ADR-T001 – Maintain ADR Catalog

Directory: /docs/adr/
ADR naming convention:
- ADR-001-use-of-nhibernate.md
- ADR-002-masstransit-for-eventing.md
Template includes:
- Context → Decision → Alternatives → Consequences → Status.
✅ Acceptance Criteria
- ADR catalog accessible via MkDocs sidebar navigation.
- All major design decisions have corresponding ADR entries.

Task AUD-DOC-ADR-T002 – Automate ADR Index Generation

Add script to generate /docs/adr/index.md automatically from filenames.
Include metadata such as date, author, and status (Accepted, Superseded).
✅ Acceptance Criteria
- ADR index updated automatically in pipeline.
- ADR search available in documentation site.

Task AUD-DOC-ADR-T003 – Implement ADR Governance Workflow

Enforce PR-based ADR submission with peer review and approval.
Add ADR review checklist in .github/pull_request_template.md.
✅ Acceptance Criteria
- ADRs require review from Architecture Guild before merge.
- Review history traceable in Git version control.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-DOC-001:

MkDocs documentation portal built, themed, and deployed automatically.
Full set of ADRs cataloged and version-controlled under /docs/adr.
API references generated dynamically from OpenAPI/Swagger definitions.
Documentation structure standardized across architecture, operations, and compliance.
ADR governance process established with peer review and CI validation.
Documentation as Code pipeline integrated into platform DevOps lifecycle.

Epic `AUD-QA-001` : Automated Testing Framework¶

Epic Description¶

This epic establishes a unified Automated Testing Framework for the Audit Trail Platform (ATP). It defines a consistent structure for unit, integration, and acceptance (SpecFlow) testing across all microservices. The goal is to ensure test automation, reproducibility, and confidence in every build pipeline, using shared test libraries and infrastructure templates from the ConnectSoft Microservice Template.

Epic Objectives¶

Standardize unit testing libraries and conventions across all bounded contexts.
Implement SpecFlow-based acceptance tests for business-level verification.
Integrate tests into CI/CD pipelines with full code coverage reporting.
Enforce quality gates for pull requests and production readiness.
Support containerized test execution for consistent results.

Features¶

Feature `AUD-QA-UNIT-001` — Unit Test Libraries¶

Feature Description Develop a shared test foundation for domain, application, and infrastructure components. Adopt MSTest for consistency and apply FluentAssertions and NSubstitute for expressive and maintainable test logic.

Tasks¶

Task AUD-QA-UNIT-T001 – Implement Unit Test Coverage

Create unit test projects for all microservices:
- DomainModel.UnitTests
- ApplicationModel.UnitTests
- InfrastructureModel.UnitTests
Integrate FluentAssertions for readability and NSubstitute for mocking.
Implement minimum coverage thresholds:
- 80% for core domain logic.
- 70% for application layer.
- 60% for infrastructure layer.
Configure coverage analysis via Coverlet and publish reports to Azure DevOps.
✅ Acceptance Criteria
- Unit test projects built and executed in CI.
- Coverage report visible in DevOps pipeline summary.
- Failing tests block PR merges.

Task AUD-QA-UNIT-T002 – Create Shared Test Utilities Library

Implement shared helpers under ConnectSoft.AuditTrail.Testing.Common:
- Entity builders and fixture factories.
- FakeClock, FakeBus, and InMemoryRepository utilities.
- Assertion extensions for aggregates and domain events.
Add as NuGet package dependency for all microservice test projects.
✅ Acceptance Criteria
- Shared utilities reusable across ≥ 3 microservices.
- Unit tests refactored to use helpers consistently.

Feature `AUD-QA-ACPT-001` — SpecFlow Acceptance Tests¶

Feature Description Build SpecFlow BDD scenarios covering key end-to-end workflows (e.g., event ingestion, hashing, verification, export). Acceptance tests run inside CI/CD and validate system behavior from the outside, across microservice boundaries.

Tasks¶

Task AUD-QA-ACPT-T001 – Automate Acceptance & Integration Pipelines

Setup project ConnectSoft.AuditTrail.AcceptanceTests:
- BDD scenarios (.feature files).
- Step definitions invoking REST/gRPC APIs.
- Shared hooks for setup/teardown and dependency injection.
Configure Docker Compose Test Environment containing all core microservices.
Integrate acceptance suite into Azure DevOps CI/CD pipeline (run-acceptance-tests.yml).
✅ Acceptance Criteria
- All SpecFlow scenarios execute successfully in CI.
- Test results published as Gherkin-style HTML reports.
- Pipeline gates block deployments if acceptance suite fails.

Task AUD-QA-ACPT-T002 – Implement Integration Test Harness

Use WebApplicationFactory and TestServer for REST APIs.
Leverage MassTransit Test Harness for event-driven validation.
Define environment variables for external services (Redis, SQL, Blob).
✅ Acceptance Criteria
- Integration harness allows tests to run locally and in CI.
- All key flows tested end-to-end (ingest → storage → verify → query).

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-QA-001:

Shared testing framework published and referenced by all microservices.
Full suite of unit, integration, and acceptance tests automated in pipelines.
Coverage and quality metrics integrated into Azure DevOps dashboards.
SpecFlow acceptance tests executed as part of continuous delivery pipeline.
Failures automatically prevent promotion to higher environments.
Consistent test structure (UnitTests, AcceptanceTests, ArchitectureTests) across repositories.

Epic `AUD-FINOPS-001` : Cost & Usage Analytics¶

Epic Description¶

This epic introduces FinOps (Financial Operations) capabilities to the Audit Trail Platform (ATP), enabling real-time visibility into cost, usage, and resource efficiency. It focuses on implementing cost attribution per tenant, usage-based metrics, and optimization dashboards that allow platform administrators to monitor and reduce infrastructure expenses. The feature aligns with ConnectSoft’s FinOps governance framework for transparency, accountability, and cost-aware engineering practices.

Epic Objectives¶

Implement tenant-based cost tagging and tracking for all cloud resources.
Collect and visualize usage and cost metrics per service and tenant.
Provide monthly and cumulative cost dashboards using Azure Cost Management APIs.
Enable resource optimization recommendations for compute, storage, and messaging workloads.
Establish automated alerts and budget thresholds for cost anomalies.
Ensure cost governance compliance with ConnectSoft FinOps policies.

Features¶

Feature `AUD-FIN-BILL-001` – Cost Tracking per Tenant¶

Feature Description Introduce tagging, metering, and reporting logic to attribute compute, storage, and network costs to specific tenants and editions. Integrate with Azure Cost Management APIs and internal telemetry data to calculate and visualize per-tenant cost breakdowns.

Tasks¶

Task AUD-FIN-BILL-T001 – Tag Resources per Tenant

Apply standardized tags to all resource groups and services:
- tenant_id, environment, edition, service_name, cost_center.
Configure Azure Policy to enforce tagging at resource creation time.
Enable tag inheritance via Infrastructure as Code (Bicep/Pulumi).
✅ Acceptance Criteria
- All deployed resources include tenant and cost tags.
- Missing tags flagged automatically in CI/CD validation step.

Task AUD-FIN-BILL-T002 – Implement Cost Aggregation Job

Scheduled job to aggregate cost metrics daily:
- CPU hours, DB storage, blob access, queue messages, network egress.
Pull raw data from Azure Consumption and Monitor APIs.
Store summaries in tenant_cost_usage table (partitioned by month).
✅ Acceptance Criteria
- Daily job executes successfully and populates aggregated cost table.
- Historical data retained for ≥ 12 months.

Task AUD-FIN-BILL-T003 – Generate Monthly Cost Dashboards

Build Grafana/Power BI dashboards showing:
- Cost by tenant, service, and environment.
- Trends vs budget thresholds.
- Forecast next month’s cost based on growth rate.
Include drilldown by microservice (Ingestion, Storage, Query, etc.).
✅ Acceptance Criteria
- Dashboards updated automatically from cost data store.
- Exportable PDF/CSV reports available for Finance and Ops teams.

Task AUD-FIN-BILL-T004 – Implement Budget Threshold Alerts

Configure Azure Monitor and Grafana alerts for:
- Monthly spend > 90 % of budget.
- Sudden 25 % cost increase in 24 hours.
Notify via Teams and email.
✅ Acceptance Criteria
- Alerts trigger correctly and notify appropriate FinOps group.
- Alert logs visible in Security & Operations dashboard.

Feature `AUD-FIN-OPT-001` – Resource Optimization¶

Feature Description Provide visibility into underutilized or over-provisioned resources and recommend optimization actions. Incorporate cost anomaly detection and right-sizing automation through integration with Azure Advisor and ATP telemetry.

Tasks¶

Task AUD-FIN-OPT-T001 – Analyze Resource Utilization

Collect telemetry from Application Insights and Azure Monitor for:
- CPU/memory utilization, DB DTUs, message bus throughput.
Correlate utilization with cost data to identify inefficiencies.
✅ Acceptance Criteria
- Weekly utilization reports generated automatically.
- Reports highlight top 10 underutilized resources.

Task AUD-FIN-OPT-T002 – Integrate Azure Advisor Recommendations

Fetch cost-saving suggestions (reserved instance, autoscaling, idle resource cleanup).
Store recommendations in resource_optimization_suggestions table.
✅ Acceptance Criteria
- Advisor integration automated with API polling job.
- Recommendations displayed in Admin Console.

Task AUD-FIN-OPT-T003 – Implement Auto-Scaling and Scheduling Policies

Configure autoscale rules for CPU, memory, and queue depth metrics.
Enable scheduled scale-down during off-peak hours.
✅ Acceptance Criteria
- Resource scaling validated in staging environment.
- Monthly savings ≥ 10 % confirmed via report comparison.

Task AUD-FIN-OPT-T004 – Add Cost Optimization Dashboards

Dashboards for:
- Efficiency ratio (usage vs cost).
- Optimization savings trend.
- Cost anomalies flagged by date/service.
✅ Acceptance Criteria
- Dashboards available in Grafana/Power BI with live data.
- Cost trends align with Azure billing and internal telemetry.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-FINOPS-001:

Tenant-level tagging and cost tracking implemented across all resources.
Automated aggregation and reporting of cost and usage data.
Monthly dashboards and alerts operational for FinOps and management teams.
Optimization recommendations and autoscaling policies implemented.
Integration with Azure Cost Management, Monitor, and Advisor validated.
Financial transparency and governance achieved for all ATP tenants and environments.

Epic `AUD-EVOLVE-001` : Future Enhancements & AI Insights¶

Epic Description¶

This epic explores next-generation enhancements for the Audit Trail Platform (ATP), focusing on the integration of AI-powered analytics and predictive intelligence. It introduces anomaly detection and intelligent audit correlation models to identify unusual behavior, forecast compliance risks, and surface actionable insights for administrators. The objective is to evolve ATP from a passive logging system into a proactive intelligence platform, capable of recognizing trends, anomalies, and potential violations before they occur.

Epic Objectives¶

Develop a proof of concept (PoC) using Azure AI Inference and OpenAI models to analyze audit event streams.
Detect behavioral anomalies and compliance drift in near real time.
Introduce predictive intelligence that correlates multi-service audit data for risk scoring.
Define the roadmap for Audit Trail Platform v2, integrating AI insights directly into dashboards and policies.
Ensure all AI models comply with data privacy, security, and explainability requirements.

Features¶

Feature `AUD-AI-ANOM-001` – Anomaly Detection¶

Feature Description Leverage Azure AI and machine learning to detect anomalies across audit events such as access spikes, policy violations, or unusual data modifications. Anomaly detection enhances operational visibility and enables early detection of potential threats or system misconfigurations.

Tasks¶

Task AUD-AI-ANOM-T001 – PoC Using Azure AI Inference

Implement an experimental pipeline using Azure Machine Learning or Azure AI Inference endpoints.
Train anomaly-detection model on aggregated audit event data (tenant, actor, event_type, frequency, time pattern).
Generate anomaly scores and flag high-risk events for investigation.
✅ Acceptance Criteria
- PoC successfully identifies at least 90 % of simulated anomalies.
- Results visualized in Grafana or Admin Console prototype dashboard.

Task AUD-AI-ANOM-T002 – Integrate Event Stream with AI Model

Subscribe to audit.record.appended and audit.policy.executed streams.
Batch events and feed into model inference endpoint in near real time.
Publish results as audit.anomaly.detected events for notification and analysis.
✅ Acceptance Criteria
- Anomaly results consumed by Notification and Compliance microservices.
- End-to-end latency < 10 seconds between detection and alert.

Task AUD-AI-ANOM-T003 – Evaluate Model Performance & Explainability

Validate model precision/recall using historical audit datasets.
Add explainability layer using SHAP or LIME to identify key contributing features.
✅ Acceptance Criteria
- Explainable AI output available for each anomaly.
- Model retraining workflow documented for continuous improvement.

Feature `AUD-AI-INS-001` – Predictive Audit Intelligence¶

Feature Description Develop predictive analytics to correlate audit trails, system usage, and compliance profiles. This feature aims to forecast upcoming risks (e.g., policy violations, capacity exhaustion) and recommend preventive actions.

Tasks¶

Task AUD-AI-INS-T001 – Roadmap for ATP v2 with AI Correlation

Define architecture blueprint for Audit Trail Platform v2, integrating AI insights into:
- Compliance Engine (predictive policy evaluation).
- Admin Console (risk-score dashboard).
- Notification Service (AI-driven alert prioritization).
Include planned technologies: Azure AI Search, Azure OpenAI Service, and Vector Database (pgvector/Qdrant).
✅ Acceptance Criteria
- ATP v2 roadmap approved and published in /docs/roadmap/ai-insights.md.
- Dependencies and milestones identified for multi-phase rollout.

Task AUD-AI-INS-T002 – Prototype Risk Scoring Engine

Develop prototype model that assigns risk score (0–100) to each tenant or user based on activity patterns.
Factors: anomaly count, policy violations, unusual access times, export frequency.
Expose GET /api/insights/risk/{tenantId} endpoint.
✅ Acceptance Criteria
- Risk scores correlated with historical incidents ≥ 85 % accuracy.
- Endpoint returns responses under 500 ms average latency.

Task AUD-AI-INS-T003 – Integrate Predictive Insights into Admin UI

Extend Admin Console dashboards with new widgets:
- “Top 10 High-Risk Tenants”
- “Predicted Policy Violations”
- “Anomaly Trend Timeline”
Add color-coded severity visualization and drill-through to audit detail view.
✅ Acceptance Criteria
- Insights rendered dynamically via AI Inference APIs.
- Dashboard validated by Security & Compliance teams.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-EVOLVE-001:

Azure AI–powered anomaly detection pipeline operational in PoC environment.
Predictive audit intelligence roadmap defined for ATP v2.
AI insights integrated with Compliance, Notification, and Admin modules.
Risk scoring and anomaly trend visualization available in dashboards.
Explainable AI outputs and retraining procedures documented.
Demonstrated measurable improvement in proactive compliance awareness.

Epic `AUD-DEVEX-001` : Developer Experience & Portal¶

Epic Description¶

This epic introduces the Developer Experience (DevEx) and Portal foundation for the Audit Trail Platform (ATP), providing developers and integrators with the tools, environments, and documentation required for rapid onboarding and consistent development workflows. It establishes a self-service developer portal, CLI tooling, and local emulation environments that mirror production systems, allowing contributors to build, test, and debug ATP services with minimal setup time.

Epic Objectives¶

Create a centralized developer portal for all ATP APIs, SDKs, documentation, and samples.
Provide a local emulation stack (via Docker Compose) replicating essential ATP services for offline testing.
Deliver a ConnectSoft CLI extension to scaffold, test, and manage Audit Trail microservices locally.
Enable automated onboarding flows with preconfigured developer credentials and sandbox data.
Improve productivity, reduce friction, and standardize the inner-loop development experience.

Features¶

Feature `AUD-DEV-PORTAL-001` – Developer Portal & API Explorer¶

Feature Description Develop an internal portal aggregating API documentation, sample payloads, SDK links, and environment onboarding tools. The portal enhances collaboration between developers, QA engineers, and platform integrators by providing unified access to all developer-facing resources.

Tasks¶

Task AUD-DEV-PORTAL-T001 – Implement Developer Portal with Live API Explorer

Build a React/Next.js–based portal or extend existing ConnectSoft Developer Hub.
Integrate with OpenAPI definitions from each ATP microservice.
Include sections for:
- API reference (REST/gRPC).
- SDK & sample library.
- Live API testing (Swagger UI integration).
- Environment setup guides and CI/CD templates.
✅ Acceptance Criteria
- Developer portal deployed at /developer/audit.
- APIs browsable interactively via live Swagger interface.
- SDK download and documentation sections operational.

Task AUD-DEV-PORTAL-T002 – Add Sandbox Environment and Test Data

Create dedicated sandbox tenants with anonymized sample data.
Automate token issuance for sandbox users via IAM integration.
Preload demo audit records, policies, and webhooks for hands-on testing.
✅ Acceptance Criteria
- Sandbox API accessible through portal login.
- Sample tenants reset nightly with clean data.

Task AUD-DEV-PORTAL-T003 – Integrate Portal Analytics & Feedback

Add developer activity tracking (page visits, API test frequency).
Provide feedback widget for documentation improvements.
✅ Acceptance Criteria
- Analytics dashboard shows usage trends.
- Feedback routed automatically to documentation backlog.

Feature `AUD-DEV-CLI-001` – CLI & Local Emulation Toolkit¶

Feature Description Introduce a command-line interface and local environment tooling to simplify developer workflows such as service scaffolding, local deployment, and integration testing. The CLI mirrors the ConnectSoft Microservice Template tooling standards and ensures consistency across microservices.

Tasks¶

Task AUD-DEV-CLI-T001 – Create Local Emulation Stack via Docker Compose

Define docker-compose.dev.yml containing:
- Core dependencies – SQL, Redis, RabbitMQ/Service Bus, Jaeger, Grafana.
- Lightweight mock services for IAM and Configuration.
Add Makefile or PowerShell scripts:
- make up – start stack.
- make down – stop and clean up.
✅ Acceptance Criteria
- Local ATP stack runs via single command.
- All core APIs reachable on standard localhost ports.

Task AUD-DEV-CLI-T002 – Add connectsoft audit CLI for Service Scaffolding and Local Testing

Extend connectsoft CLI with new commands:
- connectsoft audit new-service – scaffold new ATP microservice.
- connectsoft audit test – run tests using local emulation.
- connectsoft audit logs – view structured logs from running services.
Implement using .NET Tool or Node CLI (depending on template ecosystem).
✅ Acceptance Criteria
- CLI operational and published as internal package.
- Scaffolding aligns with Microservice Template conventions.

Task AUD-DEV-CLI-T003 – Implement Developer Onboarding Script

Script automated setup for:
- Git repo clone and environment variable setup.
- Secret retrieval from Azure Key Vault.
- Initial data seeding via CLI.
✅ Acceptance Criteria
- Developer onboarding time reduced to <15 minutes.
- Onboarding tested across Windows, Linux, and MacOS.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-DEVEX-001:

Developer portal operational with live API explorer, sandbox tenants, and SDK documentation.
Local emulation stack runnable via Docker Compose with all key dependencies.
ConnectSoft CLI (connectsoft audit) published and supporting scaffold/test workflows.
Full developer onboarding automated with scripts and preseeded environments.
Feedback and analytics integrated into portal to track usage and improve experience.
Documentation updated with DevEx workflows under /docs/developer/guide.md.

Epic `AUD-RESID-001` : Data Residency & Regional Governance¶

Epic Description¶

This epic establishes Data Residency and Regional Governance for the Audit Trail Platform (ATP). It ensures compliance with global regulations such as GDPR, HIPAA, and regional data-sovereignty mandates by segregating storage and compute resources per region (EU, US, APAC). The solution defines regional data zones, enforces residency through policy controls, and introduces breach detection and monitoring to guarantee that tenant data never crosses authorized geographic boundaries.

Epic Objectives¶

Define multi-region architecture with isolated storage and database partitions.
Automatically assign tenants to regional zones based on compliance and residency metadata.
Implement residency enforcement policies at ingestion, query, and export layers.
Detect and alert on any data or API activity violating residency constraints.
Provide observability dashboards and compliance reports for regional data distribution.
Integrate residency compliance into onboarding, configuration, and operational workflows.

Features¶

Feature `AUD-RES-ZONE-001` – Multi-Region Storage Zoning¶

Feature Description Design and implement a regional data zoning model for all audit-related storage components. Each zone (EU, US, APAC) contains isolated data stores, compute clusters, and blob storage containers managed under independent compliance boundaries.

Tasks¶

Task AUD-RES-ZONE-T001 – Configure Storage and DB Partitions for EU, US, APAC Regions

Create dedicated database instances and blob containers per region:
- audit-db-eu, audit-db-us, audit-db-apac.
- audit-blob-eu, audit-blob-us, audit-blob-apac.
Replicate necessary metadata tables globally (tenants, editions, policies).
Use Azure SQL geo-partitioning and blob container access policies.
✅ Acceptance Criteria
- All tenant data resides only in its assigned regional partition.
- Cross-region reads/writes explicitly denied by configuration.

Task AUD-RES-ZONE-T002 – Implement Region Routing Logic in Gateway

Extend Audit Gateway to route requests based on tenant.region metadata.
Configure automatic service discovery for region-specific microservices.
Include failover policies to secondary region (read-only) when applicable.
✅ Acceptance Criteria
- Requests routed automatically to correct regional cluster.
- Region misconfiguration detected and logged.

Task AUD-RES-ZONE-T003 – Integrate Residency Metadata into Tenant Onboarding

Add region field to Tenant aggregate and onboarding workflow.
Validate selected region against allowed compliance profiles.
✅ Acceptance Criteria
- New tenants provisioned in correct region automatically.
- Region metadata immutable post-creation except by admin override.

Feature `AUD-RES-POLICY-001` – Residency Enforcement Policies¶

Feature Description Introduce policy-driven enforcement ensuring data residency rules are respected across services and events. Policies prevent accidental replication, export, or data flow across regions and log violations for audit and compliance purposes.

Tasks¶

Task AUD-RES-POLICY-T001 – Enforce Residency via Tenant Metadata and Policy Engine

Define residency rules in Policy microservice (e.g., tenant.region == data.region).
Apply enforcement at:
- Ingestion – reject cross-region writes.
- Query – deny access to non-local data.
- Export – restrict exports to tenant region only.
✅ Acceptance Criteria
- Violations blocked automatically with clear error message.
- Policy logs contain actor, tenant, attempted region, and timestamp.

Task AUD-RES-POLICY-T002 – Implement Residency-Breach Alerts and Dashboards

Collect residency-violation metrics:
- violations_total, last_violation_timestamp, affected_tenants.
Create Grafana dashboards showing regional data distribution and policy compliance.
Trigger alerts on any violation event via Notification Service.
✅ Acceptance Criteria
- Dashboards display real-time residency metrics.
- Alerts sent automatically to compliance and ops channels.

Task AUD-RES-POLICY-T003 – Generate Residency Compliance Reports

Produce monthly reports for each region summarizing:
- Tenant count, data volume, and compliance posture.
- Violations or anomalies detected.
Publish reports to /reports/compliance/residency/.
✅ Acceptance Criteria
- Reports downloadable via Admin Console.
- Data validated against current tenant registry.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-RESID-001:

Fully functional multi-region data zoning (EU, US, APAC) with enforced segregation.
Tenant onboarding extended to include region assignment and validation.
Residency policies active across ingestion, query, and export workflows.
Real-time dashboards and alerts for residency violations operational.
Compliance reports generated monthly for regulatory review.
Verified alignment with GDPR, HIPAA, and data-sovereignty obligations.

Epic `AUD-EXT-001` : Integration Marketplace & Partner SDKs¶

Epic Description¶

This epic delivers the Integration Marketplace and Partner SDK Program for the Audit Trail Platform (ATP). It expands ATP’s ecosystem by enabling seamless integration with third-party systems such as SIEM, monitoring, ticketing, and compliance platforms (e.g., Splunk, Datadog, ServiceNow). The goal is to make ATP an extensible, integration-friendly platform, where certified connectors, APIs, and SDKs can be distributed via the Azure Marketplace or internal ConnectSoft catalog.

Epic Objectives¶

Build certified, production-grade integrations with top enterprise tools (Splunk, Datadog, ServiceNow).
Provide a Partner SDK and open connector registry for third-party developers.
Enable external systems to securely consume audit events and metadata.
Establish certification and governance workflows for partner-developed integrations.
Increase ATP adoption by making it plug-and-play within common enterprise ecosystems.

Features¶

Feature `AUD-EXT-SIEM-001` – Certified Integrations (Splunk, Datadog, ServiceNow)¶

Feature Description Develop out-of-the-box integrations for leading SIEM and monitoring platforms, enabling ATP audit data and alerts to be visualized, correlated, and automated across the enterprise’s security and IT operations stack.

Tasks¶

Task AUD-EXT-SIEM-T001 – Build Integration Adapters for SIEM and Monitoring Platforms

Build and publish adapters for:
- Splunk — using HTTP Event Collector (HEC) or Kafka integration.
- Datadog — forward ATP metrics and audit logs via Datadog API.
- ServiceNow — create tickets automatically for compliance or integrity violations.
Define mapping schemas and transformation logic (AuditRecord → SIEM format).
✅ Acceptance Criteria
- Audit data successfully ingested by all three platforms.
- Events tagged with tenant_id, region, and compliance_profile.
- Integration latency ≤ 5 seconds end-to-end.

Task AUD-EXT-SIEM-T002 – Implement Secure Integration Channel

Provide outbound-only HTTPS communication with HMAC or OAuth2 authentication.
Support message encryption for sensitive event data.
Add rate limiting and retry logic for external connectors.
✅ Acceptance Criteria
- All connector calls use secure auth and TLS 1.3.
- Retry/backoff implemented for temporary outages.

Task AUD-EXT-SIEM-T003 – Provide Integration Configuration APIs

Endpoints:
- POST /api/integrations – register new external integration.
- GET /api/integrations – list active connectors.
- DELETE /api/integrations/{id} – remove connector.
✅ Acceptance Criteria
- Tenants can manage connectors through Admin Console or API.
- Configuration persisted and audited.

Feature `AUD-EXT-APP-001` – Partner SDK and Connector Registry¶

Feature Description Introduce a Partner SDK for external developers and a Connector Registry to distribute integrations. This framework allows partners to build, test, and publish their own ATP-compatible connectors within a governed lifecycle.

Tasks¶

Task AUD-EXT-APP-T001 – Publish Connector Templates to Azure Marketplace

Package connectors for Splunk, Datadog, and ServiceNow as deployable Azure apps.
Add metadata, pricing, and setup instructions in Azure Marketplace listings.
Include automated ARM templates for quick deployment.
✅ Acceptance Criteria
- Marketplace listings approved and published successfully.
- Templates verified for installation and integration accuracy.

Task AUD-EXT-APP-T002 – Develop Partner SDK & CLI Extension

Provide SDK utilities and CLI commands for connector creation:
- Event schema validation.
- Webhook signature verification helpers.
- Testing stubs for offline connector simulation.
Package as ConnectSoft.AuditTrail.SDK (NuGet & npm).
✅ Acceptance Criteria
- Partner SDKs published and accessible from Developer Portal.
- SDK includes documentation, templates, and code samples.

Task AUD-EXT-APP-T003 – Add Partner SDK Governance and Certification Workflow

Define governance workflow for partner submissions:
- Security and performance validation.
- Code review and sandbox testing.
- Certification and version signing.
Integrate with internal ConnectSoft Partner Portal.
✅ Acceptance Criteria
- Partner connectors reviewed and certified prior to publication.
- Certification metadata (version, author, approval date) stored in registry.

Task AUD-EXT-APP-T004 – Implement Connector Registry APIs

Endpoints:
- GET /api/connectors – list certified connectors.
- POST /api/connectors/register – partner registration.
- GET /api/connectors/{id} – retrieve connector details.
✅ Acceptance Criteria
- Connectors queryable from Developer Portal.
- Registry supports versioning and deprecation notices.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-EXT-001:

Certified Splunk, Datadog, and ServiceNow connectors operational and validated.
Partner SDK and CLI available for external developers.
Integration Marketplace listings published on Azure Marketplace.
Connector Registry APIs and governance process implemented.
End-to-end integration metrics and logs visible in observability dashboards.
ATP ecosystem officially extensible through certified third-party connectors.

Epic `AUD-KNW-001` : Knowledge & Training Enablement¶

Epic Description¶

This epic introduces the Knowledge & Training Enablement program for the Audit Trail Platform (ATP). It focuses on equipping developers, operators, and compliance users with hands-on learning resources, sandbox environments, and structured certification paths. The goal is to build institutional knowledge, accelerate onboarding, and maintain a continuous feedback loop between documentation, training, and platform evolution.

Epic Objectives¶

Deliver guided, interactive sandbox labs with seeded demo tenants and realistic scenarios.
Create structured training paths and internal certifications for developers, DevOps, and compliance officers.
Integrate all materials into the ATP Documentation Portal (MkDocs).
Encourage community participation through monthly Q&A and feedback sessions.
Continuously update platform documentation based on real training insights.

Features¶

Feature `AUD-KNW-LABS-001` – Sandbox Lab Environments¶

Feature Description Provide a suite of sandbox environments where users can explore ATP functionality, run test scenarios, and perform guided labs safely without affecting production data. These labs demonstrate ingestion, querying, policy configuration, compliance checks, and AI insight flows end-to-end.

Tasks¶

Task AUD-KNW-LABS-T001 – Provide Guided Operator/Developer Labs with Seeded Tenants

Create sandbox tenants pre-populated with:
- Audit data, webhook events, and retention policies.
- Sample users and roles (Admin, ComplianceOfficer, Support).
Build guided lab scripts covering:
- Ingest → Query → Verify → Export workflow.
- Policy creation and enforcement testing.
✅ Acceptance Criteria
- Sandbox available via Admin Console login.
- Labs executed successfully with no access to production systems.

Task AUD-KNW-LABS-T002 – Automate Sandbox Provisioning & Reset

Implement Azure Function or pipeline to re-provision sandboxes daily.
Support different profiles (developer, operator, compliance).
✅ Acceptance Criteria
- Sandboxes reset on schedule with fresh seed data.
- Provisioning time < 10 minutes per sandbox.

Task AUD-KNW-LABS-T003 – Integrate Labs into Documentation Portal

Add /docs/training/labs/ section in MkDocs.
Include interactive code snippets and video walkthroughs.
✅ Acceptance Criteria
- Labs accessible directly from portal.
- Documentation and labs remain in sync after each release.

Feature `AUD-KNW-TRAIN-001` – Certification & Training Tracks¶

Feature Description Develop structured learning paths for all ATP personas, including engineers, operators, auditors, and support staff. Training materials include self-paced modules, exams, and certification badges issued internally via ConnectSoft Academy.

Tasks¶

Task AUD-KNW-TRAIN-T001 – Publish Learning Paths and Internal Certification Modules

Create role-specific courses:
- Developer Track: Microservice design, API usage, DevEx tools.
- Ops Track: Deployment, monitoring, incident response.
- Compliance Track: Retention and policy management.
Integrate quizzes and badge issuance via Learning Management System (LMS).
✅ Acceptance Criteria
- All courses published in ConnectSoft Academy.
- Completion data synced with HR and Ops systems.

Task AUD-KNW-TRAIN-T002 – Schedule Monthly Q&A Sessions Feeding Doc Updates

Host live sessions with architects and product owners.
Collect frequent questions and add answers to documentation FAQ.
Record and archive sessions in portal.
✅ Acceptance Criteria
- Monthly Q&A calendar published for all ATP teams.
- Documentation updated within 5 days post-session.

Task AUD-KNW-TRAIN-T003 – Launch Quarterly Knowledge Assessments

Conduct short assessments to measure understanding of recent changes and features.
Provide feedback reports to team leads for skill gaps.
✅ Acceptance Criteria
- ≥ 80 % of participants achieve passing score.
- Identified gaps logged as training improvement tickets.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-KNW-001:

Fully operational sandbox lab environment with guided scenarios.
Training and certification tracks published in ConnectSoft Academy.
Monthly Q&A and feedback loop actively maintained.
Documentation portal integrated with labs and learning modules.
Knowledge retention measured and improvement plan tracked via DevOps backlog.
Institutional training framework embedded in ATP lifecycle.

Epic `AUD-ZTR-001` : Zero-Trust & Quantum-Safe Security¶

Epic Description¶

This epic strengthens the security architecture of the Audit Trail Platform (ATP) by introducing Zero-Trust principles and Quantum-Safe Cryptography (PQC). It aims to protect inter-service communication, ensure workload authenticity, and future-proof the platform against emerging cryptographic threats. By combining SPIFFE/SPIRE workload identities with quantum-resilient signature algorithms, ATP achieves verifiable, identity-based trust across all microservices and tenants.

Epic Objectives¶

Adopt a Zero-Trust architecture across all ATP services — “never trust, always verify.”
Use SPIFFE/SPIRE to manage workload identities and mTLS authentication automatically.
Transition to quantum-safe signature algorithms for audit integrity verification.
Extend compliance overlays (SOC2, HIPAA, GDPR) to reflect Zero-Trust requirements.
Enhance the policy engine and observability stack with Zero-Trust telemetry and enforcement rules.

Features¶

Feature `AUD-ZTR-ID-001` – Workload Identity via SPIFFE/SPIRE¶

Feature Description Implement workload identity for all ATP microservices using SPIFFE/SPIRE. Each service receives a verifiable, short-lived SPIFFE ID and certificate, ensuring mutual TLS authentication and eliminating static secrets or long-lived keys.

Tasks¶

Task AUD-ZTR-ID-T001 – Integrate Workload Identity for Inter-Service Authentication

Deploy SPIRE Server and SPIRE Agents within each Kubernetes or ACA node.
Issue identities for core services (Gateway, Ingestion, Query, Integrity, Policy, etc.).
Replace static client certificates with SPIFFE-based dynamic identities.
✅ Acceptance Criteria
- All inter-service communication secured via mTLS with SPIFFE IDs.
- Static certificates deprecated and rotated out of configuration.

Task AUD-ZTR-ID-T002 – Update Gateway and Messaging Authentication

Extend API Gateway and MassTransit configurations to use SPIFFE-issued credentials.
Apply mTLS for message publishing and subscription endpoints.
✅ Acceptance Criteria
- All message bus traffic authenticated with workload identities.
- Gateway enforces certificate-based mutual trust before forwarding.

Task AUD-ZTR-ID-T003 – Implement Identity Auditing and Policy Enforcement

Integrate SPIRE with Policy microservice to validate:
- Identity claims (spiffe://connectsoft/audit/{service})
- Allowed service-to-service communication paths.
Add observability rules to detect unauthorized identity use.
✅ Acceptance Criteria
- Unauthorized service requests blocked automatically.
- SPIFFE identity logs visible in compliance dashboards.

Feature `AUD-ZTR-PQC-001` – Quantum-Safe Signature Evaluation¶

Feature Description Future-proof ATP’s integrity and verification pipelines against quantum threats by evaluating and adopting Post-Quantum Cryptography (PQC) algorithms. This ensures audit chains remain secure even after the advent of quantum-capable adversaries.

Tasks¶

Task AUD-ZTR-PQC-T001 – Evaluate PQC Algorithms for Chain-of-Hash Verification

Research NIST-approved PQC algorithms (e.g., CRYSTALS-Dilithium, Falcon, SPHINCS+).
Benchmark signature generation and verification latency within Integrity microservice.
Add experimental support for dual-signature (RSA + PQC hybrid).
✅ Acceptance Criteria
- PQC performance validated with <20% latency overhead.
- Hybrid signature mode operational for select tenants.

Task AUD-ZTR-PQC-T002 – Update Signature Validation and Key Rotation

Modify verification pipeline to support multi-key (legacy + PQC) rotation.
Ensure backward compatibility for existing records.
✅ Acceptance Criteria
- New signatures verifiable alongside older RSA ones.
- Key rotation fully automated via Key Vault.

Task AUD-ZTR-PQC-T003 – Integrate PQC Algorithm Selection into Configuration Service

Add tenant-level configuration for cryptographic policy:
- signature_algorithm = rsa | pqc | hybrid
Reflect settings in configuration API and Admin Console.
✅ Acceptance Criteria
- Administrators can select preferred signature algorithm.
- Settings audited and propagated dynamically to services.

Feature `AUD-ZTR-CMP-001` – Compliance Overlay Extension for Zero-Trust¶

Feature Description Enhance compliance overlays (SOC2, GDPR, HIPAA) with Zero-Trust controls to ensure workloads comply with modern security frameworks and identity validation standards.

Tasks¶

Task AUD-ZTR-CMP-T001 – Extend Compliance Overlays for Zero-Trust Posture

Update SOC2 overlay to include workload identity attestation requirements.
Add Zero-Trust validation rules to Policy Engine (e.g., per-call identity check).
Incorporate SPIFFE identity logs into compliance evidence exports.
✅ Acceptance Criteria
- Zero-Trust requirements documented in all compliance profiles.
- Audit exports include workload identity evidence.

Task AUD-ZTR-CMP-T002 – Develop Zero-Trust Dashboard

Visualize service identity validation, mTLS traffic rates, and PQC adoption.
Create Grafana panels:
- “Identity Auth Success/Failure Rate”
- “PQC Signature Usage Trend”
✅ Acceptance Criteria
- Dashboard operational and integrated with observability stack.
- Identity and cryptography KPIs updated in real time.

Epic-Level Acceptance Criteria¶

✅ Deliverables by End of Epic AUD-ZTR-001:

SPIFFE/SPIRE-based workload identity and mTLS implemented across services.
Quantum-safe hybrid signature validation integrated into Integrity service.
Zero-Trust enforcement and telemetry policies active platform-wide.
Compliance overlays updated to include Zero-Trust controls.
Dashboards visualizing identity and PQC metrics deployed in production.
Platform security posture validated against Zero-Trust maturity benchmarks.

ConnectSoft Audit Trail Platform – 30-Cycle Development Plan¶

Introduction¶

Purpose of This Plan¶

Objectives¶

Scope¶

Deliverables¶

Outcomes¶

Epic AUD-ARC-001 : Platform Architecture & Vision¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-ARC-HLD-001 – High-Level Architecture Blueprint¶

Tasks¶

Feature AUD-ARC-DDD-001 – Domain Model & Context Map¶

Tasks¶

Feature AUD-ARC-STD-001 – Coding & Repository Standards¶

Tasks¶

Feature AUD-ARC-GOV-001 – Architecture Governance & Principles¶

Tasks¶

Feature AUD-ARC-REF-001 – Reference Microservice Initialization¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-OPS-001 : DevOps & CI/CD Foundation¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-OPS-CI-001 – Continuous Integration (CI) Pipelines¶

Tasks¶

Feature AUD-OPS-CD-001 – Continuous Delivery (CD) Environments¶

Tasks¶

Feature AUD-OPS-IAC-001 – Infrastructure as Code (IaC)¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-TENANT-001 : Tenant & Edition Management Microservice¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-TENANT-DOM-001 – Tenant/Edition Domain Model¶

Tasks¶

Feature AUD-TENANT-API-001 – CRUD & Onboarding APIs¶

Tasks¶

Feature AUD-TENANT-INT-001 – Integration with Identity Service¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-INGEST-001 : Audit Ingestion Microservice¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-INGEST-API-001 – Append-Only APIs¶

Tasks¶

Feature AUD-INGEST-BUS-001 – Event Bus Ingestion¶

Tasks¶

Feature AUD-INGEST-VAL-001 – Validation & Normalization¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-STORAGE-001 : Audit Storage Microservice¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-STO-SCHEMA-001 – Multi-Tenant Database Schema¶

Tasks¶

Feature AUD-STO-PART-001 – Partitioning & Retention Tiers¶

Tasks¶

Feature AUD-STO-CACHE-001 – Hot Cache Layer¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-QUERY-001 : Audit Query Microservice¶

Epic Description¶

Epic Objectives¶

Features¶

Feature AUD-QUERY-API-001 – Read APIs¶

Tasks¶

Feature AUD-QUERY-PROJ-001 – Read Model Projections¶

Tasks¶

Feature AUD-QUERY-CACHE-001 – Result Caching¶

Tasks¶

Feature AUD-QUERY-SEARCH-001 – Full-Text Search Integration (Optional)¶

Tasks¶

Epic-Level Acceptance Criteria¶

Epic AUD-INTEGRITY-001 : Integrity Verification Microservice¶

Epic `AUD-ARC-001` : Platform Architecture & Vision¶

Feature `AUD-ARC-HLD-001` – High-Level Architecture Blueprint¶

Feature `AUD-ARC-DDD-001` – Domain Model & Context Map¶

Feature `AUD-ARC-STD-001` – Coding & Repository Standards¶

Feature `AUD-ARC-GOV-001` – Architecture Governance & Principles¶

Feature `AUD-ARC-REF-001` – Reference Microservice Initialization¶

Epic `AUD-OPS-001` : DevOps & CI/CD Foundation¶

Feature `AUD-OPS-CI-001` – Continuous Integration (CI) Pipelines¶

Feature `AUD-OPS-CD-001` – Continuous Delivery (CD) Environments¶

Feature `AUD-OPS-IAC-001` – Infrastructure as Code (IaC)¶

Epic `AUD-TENANT-001` : Tenant & Edition Management Microservice¶

Feature `AUD-TENANT-DOM-001` – Tenant/Edition Domain Model¶

Feature `AUD-TENANT-API-001` – CRUD & Onboarding APIs¶

Feature `AUD-TENANT-INT-001` – Integration with Identity Service¶

Epic `AUD-INGEST-001` : Audit Ingestion Microservice¶

Feature `AUD-INGEST-API-001` – Append-Only APIs¶

Feature `AUD-INGEST-BUS-001` – Event Bus Ingestion¶

Feature `AUD-INGEST-VAL-001` – Validation & Normalization¶

Epic `AUD-STORAGE-001` : Audit Storage Microservice¶

Feature `AUD-STO-SCHEMA-001` – Multi-Tenant Database Schema¶

Feature `AUD-STO-PART-001` – Partitioning & Retention Tiers¶

Feature `AUD-STO-CACHE-001` – Hot Cache Layer¶

Epic `AUD-QUERY-001` : Audit Query Microservice¶

Feature `AUD-QUERY-API-001` – Read APIs¶

Feature `AUD-QUERY-PROJ-001` – Read Model Projections¶

Feature `AUD-QUERY-CACHE-001` – Result Caching¶

Feature `AUD-QUERY-SEARCH-001` – Full-Text Search Integration (Optional)¶

Epic `AUD-INTEGRITY-001` : Integrity Verification Microservice¶

Feature `AUD-INT-HASH-001` – Hash Chain Computation¶

Feature `AUD-INT-SIGN-001` – Digital Signatures¶

Feature `AUD-INT-VERIFY-001` – Verification API¶

Feature `AUD-INT-AUDIT-001` – Background Integrity Audit Jobs¶

Epic `AUD-EXPORT-001` : Export & eDiscovery Microservice¶

Feature `AUD-EXP-JOB-001` – Export Job Orchestration¶

Feature `AUD-EXP-FMT-001` – Export Formats (CSV, Parquet, JSONL)¶

Feature `AUD-EXP-DEL-001` – Secure Delivery¶

Epic `AUD-POLICY-001` : Retention & Policy Microservice¶

Feature `AUD-POL-DSL-001` – Retention DSL¶

Feature `AUD-POL-EXEC-001` – Policy Executor¶

Feature `AUD-POL-HOLD-001` – Legal Hold Management¶

Epic `AUD-SEARCH-001` : Search Index Microservice¶

Feature `AUD-SRCH-META-001` – Metadata Indexing¶

Feature `AUD-SRCH-FTS-001` – Full-Text Capabilities¶

Feature `AUD-SRCH-MAINT-001` – Reindex & Maintenance Jobs¶

Epic `AUD-GATEWAY-001` : API Gateway / Edge Service¶

Feature `AUD-GW-ROUTE-001` – Central Routing & Aggregation¶

Feature `AUD-GW-SEC-001` – Auth & Rate Limiting¶

Feature `AUD-GW-MON-001` – Edge Observability¶

Epic `AUD-IDENTITY-001` : Integration with IAM¶

Feature `AUD-ID-AUTH-001` – OAuth2/OpenIddict Integration¶

Feature `AUD-ID-ROLES-001` – Roles & Claims Propagation¶

Epic `AUD-SECURITY-001` : RBAC, ABAC & Redaction¶

Feature `AUD-SEC-RBAC-001` – Role-Based Model¶