Limits & Quotas Reference - Audit Trail Platform (ATP)¶

Fair, predictable, auditable — ATP enforces resource quotas per tenant/edition, rate limits to prevent abuse, and capacity guardrails to maintain SLOs while optimizing costs across all environments.

📋 Documentation Generation Plan¶

This document will be generated in 14 cycles. Current progress:

Cycle	Topics	Estimated Lines	Status
Cycle 1	Limits & Quotas Philosophy (1-2)	~3,000	⏳ Not Started
Cycle 2	API Rate Limiting (3-4)	~3,500	⏳ Not Started
Cycle 3	Ingestion Limits & Quotas (5-6)	~4,000	⏳ Not Started
Cycle 4	Storage Limits & Capacity (7-8)	~3,500	⏳ Not Started
Cycle 5	Query & Export Limits (9-10)	~3,500	⏳ Not Started
Cycle 6	Messaging Limits (11-12)	~3,000	⏳ Not Started
Cycle 7	Compute & Memory Limits (13-14)	~3,000	⏳ Not Started
Cycle 8	Azure Service Limits (15-16)	~4,000	⏳ Not Started
Cycle 9	Per-Tenant Quotas by Edition (17-18)	~4,000	⏳ Not Started
Cycle 10	Monitoring & Alerting (19-20)	~3,000	⏳ Not Started
Cycle 11	Scaling Strategies (21-22)	~3,000	⏳ Not Started
Cycle 12	Cost Optimization (23-24)	~3,000	⏳ Not Started
Cycle 13	Quota Management & Governance (25-26)	~2,500	⏳ Not Started
Cycle 14	Troubleshooting & Best Practices (27-28)	~3,000	⏳ Not Started

Total Estimated Lines: ~47,000

Purpose & Scope¶

This document provides the complete reference for all limits, quotas, and resource constraints within the Audit Trail Platform (ATP), covering API rate limits, storage capacity, compute resources, messaging throughput, per-tenant quotas, and Azure service limits that govern system behavior, performance, and cost.

Why Limits & Quotas Matter for ATP

Fair Resource Allocation: Prevent any single tenant from monopolizing shared resources
Cost Predictability: Enforce usage boundaries aligned with subscription tiers (Free, Pro, Enterprise)
SLO Protection: Maintain performance and availability targets across all tenants
Capacity Planning: Understand growth trajectories and trigger scaling thresholds
Abuse Prevention: Block malicious or accidental resource exhaustion attacks
Compliance Boundaries: Honor data residency, retention, and export restrictions
Operational Safety: Prevent cascading failures from runaway processes

Limit Categories in ATP

Rate Limits: Requests per second/minute (API, ingestion, export)
Throughput Limits: Events/messages per second, bytes per day
Storage Quotas: Total GB per tenant, retention period maximums
Compute Limits: CPU/memory per workload, concurrent jobs
Message Limits: Message size, batch size, queue depth
Concurrency Limits: Parallel operations, connections, sessions
Resource Limits: Database connections, cache size, network bandwidth

Detailed Cycle Plan¶

CYCLE 1: Limits & Quotas Philosophy (~3,000 lines)¶

Topic 1: ATP Limits & Quotas Philosophy¶

What will be covered: - Why Enforce Limits? - Fair Use: Multi-tenant fairness (noisy neighbor prevention) - Predictable Costs: Cost containment and budget adherence - System Stability: Protect service SLOs (99.9% availability) - Capacity Planning: Forecasting and scaling triggers - Compliance: Honor regulatory constraints (data residency, retention)

Limit Types

1. Hard Limits (Rejections)
   - API returns 429 Too Many Requests
   - Export job fails with "Quota Exceeded"
   - Cannot exceed under any circumstances

2. Soft Limits (Throttling)
   - Requests queued, not rejected
   - Gradual degradation (slower processing)
   - Burst tolerance with sustained limit

3. Guidance Limits (Warnings)
   - Notifications at 80%, 90% usage
   - No enforcement, informational only
   - Helps tenants plan upgrades

Limit Enforcement Points
API Gateway: Rate limiting (requests/minute)
Ingestion Service: Event throughput (events/second)
Storage: Retention policies, total GB per tenant
Query Service: Result pagination, query complexity
Export Service: Export windows, bytes/day, concurrent jobs
Messaging: Message size, prefetch count, concurrency
Edition-Based Quotas | Resource | Free | Pro | Enterprise | |---------------------------|-----------|-----------|------------| | API Rate (req/min) | 60 | 600 | 3,000 | | Ingestion (events/sec) | 10 | 100 | 500 | | Storage (GB) | 10 | 500 | 5,000+ | | Query Rate (req/min) | 30 | 300 | 1,500 | | Concurrent Exports | 1 | 3 | 10 | | Export Bytes/Day (GB) | 10 | 100 | 1,000+ | | Retention (days) | 30 | 365 | 2,555+ | | Webhook Subscriptions | 1 | 5 | 20 |
Quota Inheritance & Overrides
Base quotas from edition
Per-tenant overrides (contract-based)
Temporary quota increases (support tickets)
Permanent upgrades (edition changes)

Code Examples: - Quota enforcement architecture - Edition-based quota matrix - Quota override mechanisms

Diagrams: - Limit enforcement points - Edition quota hierarchy - Hard vs. soft limit behavior

Deliverables: - Limits & quotas philosophy document - Edition quota matrix (complete) - Enforcement architecture

Topic 2: Quota Management Architecture¶

What will be covered: - Quota Storage & Resolution

public interface IQuotaService
{
    Task<TenantQuotas> GetQuotasAsync(string tenantId);
    Task<QuotaUsage> GetUsageAsync(string tenantId, QuotaType quotaType);
    Task<bool> CheckQuotaAsync(string tenantId, QuotaType quotaType, long requestedAmount);
    Task IncrementUsageAsync(string tenantId, QuotaType quotaType, long amount);
}

public class TenantQuotas
{
    public string TenantId { get; set; }
    public string Edition { get; set; }
    public long ApiRateLimit { get; set; }          // req/min
    public long IngestionRateLimit { get; set; }    // events/sec
    public long StorageQuotaGB { get; set; }
    public long ExportBytesPerDayGB { get; set; }
    public int ConcurrentExports { get; set; }
    public int RetentionDays { get; set; }
    public Dictionary<string, long> Overrides { get; set; }
}

public class QuotaUsage
{
    public string TenantId { get; set; }
    public QuotaType Type { get; set; }
    public long CurrentUsage { get; set; }
    public long Limit { get; set; }
    public double PercentageUsed => (CurrentUsage * 100.0) / Limit;
    public DateTime ResetAt { get; set; }
}

Quota Storage Options
Redis: Fast, distributed counters (rate limiting)
SQL: Persistent quotas and historical usage
Cosmos DB: Global distribution for multi-region quotas
In-Memory: Cache for frequently accessed quotas
Quota Reset Strategies
Time-Based: Reset every minute/hour/day (sliding window)
Token Bucket: Tokens replenish over time (burst tolerance)
Leaky Bucket: Constant output rate (smooth traffic)
Fixed Window: Reset at interval boundaries (simple)
Quota Monitoring
Real-time usage tracking (Application Insights metrics)
Threshold alerts (80%, 90%, 100%)
Historical usage trends
Anomaly detection (sudden spikes)

Code Examples: - IQuotaService implementation - Redis-based rate limiter - Token bucket algorithm - Usage tracking middleware

Diagrams: - Quota service architecture - Token bucket vs. leaky bucket - Quota resolution flow

Deliverables: - Quota service implementation - Rate limiting algorithms - Monitoring integration

CYCLE 2: API Rate Limiting (~3,500 lines)¶

Topic 3: API Gateway Rate Limiting¶

What will be covered: - ASP.NET Core Rate Limiting Middleware

services.AddRateLimiter(options =>
{
    options.RejectionStatusCode = StatusCodes.Status429TooManyRequests;

    // Global limiter (per-tenant)
    options.GlobalLimiter = PartitionedRateLimiter.Create<HttpContext, string>(context =>
    {
        var tenantId = context.GetTenantId();
        var edition = context.GetTenantEdition();

        // Get rate limit from edition
        var permitLimit = GetPermitLimit(edition);  // Free: 60/min, Pro: 600/min, Enterprise: 3000/min

        return RateLimitPartition.GetFixedWindowLimiter(tenantId, _ => new FixedWindowRateLimiterOptions
        {
            PermitLimit = permitLimit,
            Window = TimeSpan.FromMinutes(1),
            AutoReplenishment = true,
            QueueLimit = 0  // No queuing, reject immediately
        });
    });

    // Endpoint-specific policies
    options.AddFixedWindowLimiter("ingestion", options =>
    {
        options.PermitLimit = 100;
        options.Window = TimeSpan.FromSeconds(1);
    });

    options.AddTokenBucketLimiter("export", options =>
    {
        options.TokenLimit = 10;
        options.ReplenishmentPeriod = TimeSpan.FromMinutes(1);
        options.TokensPerPeriod = 1;
        options.AutoReplenishment = true;
    });
});

// Apply rate limiting
app.UseRateLimiter();

// Endpoint configuration
[EnableRateLimiting("ingestion")]
[HttpPost("events")]
public async Task<IActionResult> IngestEvent([FromBody] AuditEvent auditEvent) { ... }

Rate Limit Response Headers

HTTP/1.1 429 Too Many Requests
X-RateLimit-Limit: 600
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1699920000
Retry-After: 60
Content-Type: application/json

{
  "error": "RateLimitExceeded",
  "message": "API rate limit of 600 requests/minute exceeded. Retry after 60 seconds.",
  "limit": 600,
  "remaining": 0,
  "resetAt": "2025-11-01T12:00:00Z",
  "upgradeUrl": "https://audit.connectsoft.io/pricing"
}

Rate Limiting Strategies
Fixed Window: Simple, predictable (60 req/min resets at :00)
Sliding Window: Smoother (rolling 60-second window)
Token Bucket: Burst tolerance (burst 10, refill 1/sec)
Leaky Bucket: Constant rate (queue excess requests)
Per-Tenant Rate Limiting
Extract tenant ID from JWT claims or header
Lookup tenant edition (Free, Pro, Enterprise)
Apply edition-specific rate limits
Track usage per tenant in Redis
Rate Limit Bypass
Internal service-to-service calls (no rate limit)
Admin API keys (elevated limits)
Health check endpoints (exempt)
Webhook delivery retries (separate quota)

Code Examples: - Complete rate limiting middleware setup - All rate limiting strategies (Fixed Window, Sliding, Token Bucket) - Per-tenant rate limit configuration - Rate limit response headers

Diagrams: - Rate limiting middleware flow - Fixed vs. sliding window comparison - Token bucket visualization - Rate limit enforcement architecture

Deliverables: - Rate limiting middleware configuration - All rate limiting strategies (code + config) - Response header standards - Bypass rules

Topic 4: Rate Limit Monitoring & Alerting¶

What will be covered: - Telemetry for Rate Limiting

href="#__codelineno-4-1">public class RateLimitTelemetryMiddleware pan> public async Task InvokeAsync(HttpContext context, RequestDelegate next) { var tenantId = context.GetTenantId(); var endpoint = context.Request.Path; // Track rate limit check _telemetry.TrackEvent("RateLimitCheck", new Dictionary<string, string> { ["TenantId"] = tenantId, ["Endpoint"] = endpoint, ["Edition"] = context.GetTenantEdition() }); await next(context); if (context.Response.StatusCode == 429) { // Track rate limit exceeded _telemetry.TrackMetric("RateLimitExceeded", 1, new Dictionary<string, string> { ["TenantId"] = tenantId, ["Endpoint"] = endpoint, ["Edition"] = context.GetTenantEdition() }); } } }

Application Insights Queries

// Top 10 tenants hitting rate limits
customMetrics
| where name == "RateLimitExceeded"
| extend TenantId = tostring(customDimensions.TenantId)
| extend Edition = tostring(customDimensions.Edition)
| summarize Count = sum(value) by TenantId, Edition
| top 10 by Count desc

// Rate limit usage by edition
customEvents
| where name == "RateLimitCheck"
| extend Edition = tostring(customDimensions.Edition)
| extend IsExceeded = (customDimensions.StatusCode == "429")
| summarize 
    TotalRequests = count(),
    Exceeded = countif(IsExceeded)
    by Edition
| extend ExceededPercentage = (Exceeded * 100.0) / TotalRequests

Alerting Rules
High Rate Limit Rejection Rate: Alert if >10% of requests hit 429
Tenant Consistently Over Limit: Alert if same tenant exceeds 5 times in 1 hour
Edition Upgrade Opportunity: Notify sales if tenant hits 80% of limit frequently
Dashboard Metrics
Rate limit usage by tenant
429 responses over time
Edition-wise rate limit distribution
Top rejected endpoints

Code Examples: - Rate limit telemetry middleware - Application Insights queries (complete) - Alert rule configurations - Dashboard JSON (Azure Monitor)

Diagrams: - Telemetry flow - Dashboard layout (mockup) - Alert notification flow

Deliverables: - Telemetry middleware - Monitoring query library - Alert rules - Dashboard templates

CYCLE 3: Ingestion Limits & Quotas (~4,000 lines)¶

Topic 5: Event Ingestion Rate Limits¶

What will be covered: - Ingestion Throughput Limits | Edition | Events/Second | Events/Minute | Events/Day | Burst Capacity | |------------|---------------|---------------|-------------|----------------| | Free | 10 | 600 | 864,000 | 20 (1 sec) | | Pro | 100 | 6,000 | 8,640,000 | 200 (1 sec) | | Enterprise | 500 | 30,000 | 43,200,000 | 1,000 (1 sec) |

Ingestion Enforcement

[EnableRateLimiting("ingestion")]
[HttpPost("api/v1/events")]
public async Task<IActionResult> IngestEvent([FromBody] AuditEvent auditEvent)
{
    var tenantId = HttpContext.GetTenantId();

    // Check tenant-specific ingestion quota
    if (!await _quotaService.CheckQuotaAsync(tenantId, QuotaType.IngestionRate, 1))
    {
        return StatusCode(429, new
        {
            Error = "IngestionRateLimitExceeded",
            Message = "Event ingestion rate limit exceeded. Current limit: 10 events/second.",
            RetryAfter = 1
        });
    }

    // Increment usage counter
    await _quotaService.IncrementUsageAsync(tenantId, QuotaType.IngestionRate, 1);

    // Process event
    await _ingestionService.IngestAsync(auditEvent);

    return Accepted();
}

Batch Ingestion Limits

{
  "BatchIngestion": {
    "MaxBatchSize": 1000,           // Max events per batch
    "MaxBatchSizeBytes": 10485760,  // 10 MB max payload
    "MaxEventSizeBytes": 262144,    // 256 KB max per event
    "TimeoutSeconds": 30
  }
}

Ingestion Back-Pressure
Queue depth monitoring (Azure Service Bus)
Throttle ingestion if queue > 10,000 messages
Return 503 Service Unavailable (not 429)
Retry-After header with backoff
Burst Tolerance
Token bucket: 100 tokens, refill 10/sec
Allows brief spikes (e.g., 100 events in 1 second)
Sustained rate must average to limit (10/sec for Free)

Code Examples: - Ingestion rate limit enforcement - Batch ingestion validation - Back-pressure handling - Token bucket burst implementation

Diagrams: - Ingestion rate limit flow - Burst tolerance timeline - Back-pressure architecture

Deliverables: - Ingestion rate limiting guide - Batch ingestion limits - Back-pressure implementation

Topic 6: Event Size & Payload Limits¶

What will be covered: - Event Size Limits

Component                | Limit       | Enforcement
-------------------------|-------------|-------------
Single Event Size        | 256 KB      | API Gateway rejects >256KB
Batch Payload Size       | 10 MB       | API Gateway rejects >10MB
Event Field Value Size   | 64 KB       | Per-field maximum
Total Event Fields       | 1,000       | Maximum field count
Nested Depth             | 10 levels   | Max JSON nesting
String Field Length      | 32,768 chars| Individual string max
Binary Attachment Size   | 5 MB        | Per-attachment limit
Total Attachments/Event  | 10          | Maximum count

Payload Validation

public class EventSizeValidator
{
    private const int MaxEventSizeBytes = 256 * 1024;  // 256 KB
    private const int MaxFieldCount = 1000;
    private const int MaxStringLength = 32768;

    public ValidationResult Validate(AuditEvent auditEvent)
    {
        var errors = new List<string>();

        // Check total event size
        var eventSize = JsonSerializer.Serialize(auditEvent).Length;
        if (eventSize > MaxEventSizeBytes)
        {
            errors.Add($"Event size ({eventSize} bytes) exceeds maximum ({MaxEventSizeBytes} bytes)");
        }

        // Check field count
        var fieldCount = CountFields(auditEvent);
        if (fieldCount > MaxFieldCount)
        {
            errors.Add($"Event has {fieldCount} fields, maximum is {MaxFieldCount}");
        }

        // Check string lengths
        CheckStringLengths(auditEvent, errors);

        return errors.Any() 
            ? ValidationResult.Failure(errors) 
            : ValidationResult.Success();
    }
}

Size Limit Error Responses

{
  "error": "EventTooLarge",
  "message": "Event size (300KB) exceeds maximum allowed size (256KB)",
  "eventSize": 307200,
  "maxSize": 262144,
  "suggestions": [
    "Remove unnecessary fields",
    "Compress large payloads",
    "Move attachments to external storage with references",
    "Split into multiple smaller events"
  ]
}

Code Examples: - Event size validation (complete) - Payload size enforcement - Error response formatting - Size optimization suggestions

Diagrams: - Event size validation flow - Nested depth checking

Deliverables: - Event size validator - Payload limits reference - Error handling guide

CYCLE 4: Storage Limits & Capacity (~3,500 lines)¶

Topic 7: Storage Quotas by Tier¶

What will be covered: - Storage Tier Limits | Tier | Storage Type | Per-Tenant Quota | Retention Max | Cost/GB/Month | |------|--------------|------------------|---------------|---------------| | HOT | Azure Blob (WORM) | Free: 10GB, Pro: 500GB, Enterprise: 5TB+ | 7-90 days | $0.018 | | WARM | Azure SQL/Cosmos DB | Free: 5GB, Pro: 250GB, Enterprise: 2.5TB+ | 30-365 days | $0.005 | | COLD | Azure Blob Archive | Free: 10GB, Pro: 1TB, Enterprise: 50TB+ | 1-7 years | $0.001 |

Storage Quota Enforcement

public class StorageQuotaMiddleware
{
    public async Task<bool> CheckStorageQuota(string tenantId, long sizeBytes)
    {
        var quota = await _quotaService.GetQuotasAsync(tenantId);
        var currentUsage = await _storageMetrics.GetCurrentStorageGB(tenantId);
        var requestedGB = sizeBytes / (1024.0 * 1024.0 * 1024.0);

        if (currentUsage + requestedGB > quota.StorageQuotaGB)
        {
            _logger.LogWarning("Storage quota exceeded for tenant {TenantId}. Current: {Current}GB, Quota: {Quota}GB",
                tenantId, currentUsage, quota.StorageQuotaGB);

            return false;  // Reject ingestion
        }

        return true;
    }
}

Retention Policy Limits
Minimum Retention: 7 days (compliance requirement)
Maximum Retention: 2,555 days (7 years for Enterprise)
Default Retention: 30 days (Free), 365 days (Pro), 730 days (Enterprise)
Lifecycle Automation: HOT → WARM (30 days), WARM → COLD (365 days)
Storage Growth Projections
Average event size: 2 KB
Free: 10 events/sec × 2KB × 86,400 sec = ~1.7 GB/day
Pro: 100 events/sec = ~17 GB/day
Enterprise: 500 events/sec = ~86 GB/day
Storage Quota Warnings
80% usage: Email notification to tenant admin
90% usage: Dashboard warning banner
95% usage: Daily email + dashboard alert
100% usage: Ingestion blocked, upgrade prompt

Code Examples: - Storage quota enforcement - Retention policy configuration - Growth projection calculator - Quota warning system

Diagrams: - Storage tier architecture - Lifecycle policy flow - Growth projection chart - Warning notification flow

Deliverables: - Storage quota enforcement - Retention policy engine - Growth calculators - Warning/alert system

Topic 8: Storage Performance & IOPS Limits¶

What will be covered: - Azure Blob Storage Limits

Metric                          | Free Tier        | Pro Tier         | Enterprise Tier
--------------------------------|------------------|------------------|------------------
Max Storage Account Size        | 10 TB            | 50 TB            | 500 TB
Max Blob Size                   | 5 GB (per blob)  | 5 GB             | 5 GB
Max IOPS (Premium Block Blob)   | N/A              | 100,000          | 250,000
Max Throughput (GB/sec)         | 60               | 120              | 200
Max Containers per Account      | 1,000            | 5,000            | 50,000
Max Blobs per Container         | Unlimited        | Unlimited        | Unlimited

Azure SQL Database Limits

DTU Tier | Max DB Size | Max IOPS | Max Log Rate | Max Concurrent Workers
---------|-------------|----------|--------------|------------------------
S0 (10)  | 250 GB      | 300      | 2.5 MB/s     | 60
S3 (100) | 1 TB        | 2,000    | 25 MB/s      | 200
P2 (250) | 4 TB        | 5,000    | 48 MB/s      | 400

Cosmos DB Limits

Free: 1,000 RU/s max, 25 GB storage
Pro: 10,000 RU/s default, 1 TB storage
Enterprise: Autoscale 100,000 RU/s, 50 TB storage

Code Examples: - IOPS monitoring queries - Storage performance metrics - Autoscaling configurations

Diagrams: - Storage performance tiers - IOPS scaling strategy

Deliverables: - Storage performance guide - IOPS monitoring - Scaling triggers

CYCLE 5: Query & Export Limits (~3,500 lines)¶

Topic 9: Query Limits & Pagination¶

What will be covered: - Query Rate Limits | Edition | Queries/Minute | Concurrent Queries | Max Query Duration | |------------|----------------|--------------------|--------------------| | Free | 30 | 2 | 30 seconds | | Pro | 300 | 10 | 60 seconds | | Enterprise | 1,500 | 50 | 120 seconds |

Query Result Limits

public class QueryLimits
{
    public const int MaxResultsPerPage = 1000;
    public const int DefaultPageSize = 100;
    public const int MaxResponseSizeBytes = 25 * 1024 * 1024;  // 25 MB
    public const int MaxQueryComplexity = 100;  // Query cost units
    public const int MaxFilterFields = 50;
    public const int MaxSortFields = 10;
}

Pagination Enforcement

[HttpGet("api/v1/events")]
public async Task<IActionResult> QueryEvents(
    [FromQuery] int page = 1,
    [FromQuery] int pageSize = 100)
{
    // Enforce page size limit
    if (pageSize > QueryLimits.MaxResultsPerPage)
    {
        return BadRequest(new
        {
            Error = "PageSizeExceeded",
            Message = $"Page size ({pageSize}) exceeds maximum ({QueryLimits.MaxResultsPerPage})",
            MaxPageSize = QueryLimits.MaxResultsPerPage
        });
    }

    var results = await _queryService.QueryEventsAsync(page, pageSize);

    return Ok(new
    {
        Data = results.Items,
        Page = page,
        PageSize = pageSize,
        TotalResults = results.Total,
        TotalPages = (int)Math.Ceiling(results.Total / (double)pageSize)
    });
}

Query Complexity Scoring
Base cost: 1 unit
Filter per field: +1 unit
Sort per field: +2 units
Full-text search: +10 units
Date range filter: +5 units
Aggregation: +20 units
Reject if total > MaxQueryComplexity

Code Examples: - Query rate limiting - Pagination implementation - Query complexity calculator - Response size enforcement

Diagrams: - Query rate limit flow - Pagination architecture - Complexity scoring algorithm

Deliverables: - Query limits enforcement - Pagination standards - Complexity scoring engine

Topic 10: Export Limits & Windows¶

What will be covered: - Export Quotas | Edition | Concurrent Exports | Export Bytes/Day | Max Export Size | Export Window | |------------|--------------------|------------------|-----------------|------------------| | Free | 1 | 10 GB | 5 GB | 24/7 (throttled) | | Pro | 3 | 100 GB | 50 GB | 24/7 | | Enterprise | 10 | 1 TB | 500 GB | 24/7 (priority) |

Export Window Enforcement

public class ExportScheduler
{
    private readonly ExportWindowConfig _config;

    public async Task<ExportJobResult> ScheduleExportAsync(ExportRequest request)
    {
        var tenantId = request.TenantId;

        // Check concurrent export limit
        var activeExports = await _exportRepo.GetActiveExportsAsync(tenantId);
        if (activeExports.Count >= GetConcurrentExportLimit(tenantId))
        {
            return ExportJobResult.Rejected("Concurrent export limit reached");
        }

        // Check daily export quota
        var todayUsage = await _exportMetrics.GetTodayExportBytesAsync(tenantId);
        var quota = await _quotaService.GetQuotasAsync(tenantId);

        if (todayUsage + request.EstimatedSizeBytes > quota.ExportBytesPerDayGB * 1024 * 1024 * 1024)
        {
            return ExportJobResult.Deferred("Daily export quota exceeded, try tomorrow");
        }

        // Check if in export window (2-6 AM local time for cost optimization)
        if (!IsInExportWindow() && !IsPriorityTenant(tenantId))
        {
            var nextWindow = GetNextExportWindowStart();
            return ExportJobResult.Deferred($"Export scheduled for next window at {nextWindow}");
        }

        // Schedule export
        var job = await _exportService.CreateExportJobAsync(request);
        return ExportJobResult.Scheduled(job);
    }
}

Export Compression & Optimization
Compress exports with gzip (70-80% size reduction)
Delta exports (only changed records)
Filtered exports (specific date ranges, classifications)
Streaming exports (avoid full-file buffering)

Code Examples: - Export quota enforcement - Export window scheduling - Concurrent export management - Compression strategies

Diagrams: - Export scheduling flow - Export window timeline - Quota management

Deliverables: - Export scheduler - Quota enforcement - Optimization guide

CYCLE 6: Messaging Limits (~3,000 lines)¶

Topic 11: Azure Service Bus Limits¶

What will be covered: - Service Bus Quotas

Tier               | Max Message Size | Max Queue Size | Max Throughput | Max Connections
-------------------|------------------|----------------|----------------|------------------
Standard           | 256 KB           | 80 GB          | Limited        | 1,000
Premium (1 MU)     | 1 MB             | 1 TB           | High           | 10,000
Premium (4 MU)     | 1 MB             | 4 TB           | Very High      | 40,000

MassTransit Configuration

{
  "MassTransit": {
    "AzureServiceBusTransport": {
      "AzureServiceBusHost": {
        "FullyQualifiedNamespace": "atp-prod.servicebus.windows.net",
        "UseManagedIdentity": true,
        "OperationTimeoutSeconds": 60,
        "RetryMinBackoff": 1,
        "RetryMaxBackoff": 30
      },
      "AzureServiceBusReceiveEndpoint": {
        "PrefetchCount": 256,           // Free: 8, Pro: 64, Enterprise: 256
        "ConcurrentMessageLimit": 512,  // Free: 16, Pro: 128, Enterprise: 512
        "MaxAutoLockRenewalDuration": "00:05:00",
        "LockDuration": "00:05:00"
      },
      "MaxMessageSize": 262144,         // 256 KB Standard, 1 MB Premium
      "RetryLimit": 5
    }
  }
}

Message Size Limits
Standard Tier: 256 KB max (header + body)
Premium Tier: 1 MB max (header + body)
Batched messages: Sum of all messages < tier limit
Large payloads: Use claim-check pattern (store in Blob, reference in message)

Code Examples: - Service Bus configuration (all tiers) - Message size validation - Claim-check pattern implementation - Prefetch tuning

Diagrams: - Service Bus tiers comparison - Claim-check pattern flow - Message processing limits

Deliverables: - Service Bus configuration guide - Message size enforcement - Claim-check implementation

Topic 12: Message Throughput & Concurrency¶

What will be covered: - Throughput Limits

Tenant Edition | Messages/Second (Publish) | Messages/Second (Consume) | Queue Depth Warning
---------------|---------------------------|---------------------------|---------------------
Free           | 100                       | 50                        | 1,000
Pro            | 1,000                     | 500                       | 10,000
Enterprise     | 10,000                    | 5,000                     | 100,000

Concurrency Configuration
PrefetchCount: Messages fetched from broker ahead of consumption
ConcurrentMessageLimit: Max parallel message handlers
KEDA Autoscaling: Scale pods based on queue depth

Back-Pressure Handling

public class MessageBackPressureHandler
{
    public async Task<bool> CanPublishAsync(string tenantId)
    {
        var queueDepth = await _serviceBusMetrics.GetQueueDepthAsync(tenantId);
        var threshold = GetQueueDepthThreshold(tenantId);  // Free: 1K, Pro: 10K, Enterprise: 100K

        if (queueDepth > threshold)
        {
            _logger.LogWarning("Queue depth ({Depth}) exceeds threshold ({Threshold}) for tenant {TenantId}",
                queueDepth, threshold, tenantId);

            // Throttle publisher
            return false;
        }

        return true;
    }
}

Code Examples: - Throughput monitoring - Concurrency tuning - Back-pressure implementation - KEDA autoscaling configuration

Diagrams: - Message throughput flow - Concurrency vs. throughput - KEDA scaling behavior

Deliverables: - Throughput limits guide - Concurrency tuning - Back-pressure handling - Autoscaling config

CYCLE 7: Compute & Memory Limits (~3,000 lines)¶

Topic 13: Kubernetes Resource Limits¶

What will be covered: - Pod Resource Requests & Limits

apiVersion: v1
kind: Pod
metadata:
  name: atp-ingestion
spec:
  containers:
  - name: ingestion
    image: acr-atp-prod.azurecr.io/ingestion:1.0.0
    resources:
      requests:
        memory: "512Mi"
        cpu: "500m"
      limits:
        memory: "2Gi"
        cpu: "2000m"

Resource Quotas by Edition | Service | Free (requests/limits) | Pro (requests/limits) | Enterprise (requests/limits) | |-------------|------------------------|-----------------------|------------------------------| | Ingestion | 256Mi/1Gi, 250m/1 | 512Mi/2Gi, 500m/2 | 1Gi/4Gi, ¼ | | Query | 256Mi/1Gi, 250m/1 | 512Mi/2Gi, 500m/2 | 1Gi/4Gi, ¼ | | Projection | 512Mi/2Gi, 500m/2 | 1Gi/4Gi, ½ | 2Gi/8Gi, 2/8 | | Export | 1Gi/4Gi, 500m/2 | 2Gi/8Gi, ¼ | 4Gi/16Gi, 2/8 | | Integrity | 256Mi/1Gi, 250m/1 | 512Mi/2Gi, 500m/2 | 1Gi/4Gi, ¼ |

Namespace Resource Quotas

apiVersion: v1
kind: ResourceQuota
metadata:
  name: tenant-quota
  namespace: atp-tenant-acme
spec:
  hard:
    requests.cpu: "10"
    requests.memory: "20Gi"
    limits.cpu: "20"
    limits.memory: "40Gi"
    pods: "50"
    services: "10"

Code Examples: - Pod resource specifications - Namespace quotas - Resource monitoring - OOMKilled handling

Diagrams: - Resource request/limit hierarchy - Namespace quota enforcement - Pod eviction flow

Deliverables: - Resource specifications (all services) - Namespace quota templates - Monitoring dashboards

Topic 14: Concurrency & Connection Limits¶

What will be covered: - Database Connection Pools

{
  "ConnectionStrings": {
    "AuditDb": "Server=...;Max Pool Size=100;Min Pool Size=10;Connect Timeout=30;"
  }
}

Edition	Max DB Connections	Connection Timeout	Command Timeout
Free	10	30 sec	30 sec
Pro	50	60 sec	60 sec
Enterprise	200	90 sec	120 sec

HTTP Client Limits
Max connections per endpoint: 100 (Free), 500 (Pro), 2000 (Enterprise)
Connection timeout: 30 seconds
Request timeout: 60 seconds
Retry policy: 3 retries with exponential backoff

Code Examples: - Connection pool configuration - HTTP client setup - Timeout handling - Retry policies

Diagrams: - Connection pool architecture - Timeout cascade prevention

Deliverables: - Connection pool guide - HTTP client configuration - Timeout strategies

CYCLE 8: Azure Service Limits (~4,000 lines)¶

Topic 15: Azure SQL & Cosmos DB Limits¶

What will be covered: - Azure SQL Database Limits

Service Tier    | Max DB Size | Max DTU/vCore | Max IOPS | Max Log Rate | Max Sessions
----------------|-------------|---------------|----------|--------------|---------------
Basic           | 2 GB        | 5 DTU         | 300      | 2.5 MB/s     | 30
Standard S3     | 1 TB        | 100 DTU       | 2,000    | 25 MB/s      | 200
Premium P2      | 4 TB        | 250 DTU       | 5,000    | 48 MB/s      | 400
Hyperscale      | 100 TB      | Variable      | Variable | Variable     | 1,600

Cosmos DB Limits

Metric                     | Limit
---------------------------|------------------
Max RU/s per container     | 1,000,000 (manual), unlimited (autoscale)
Max storage per container  | Unlimited
Max item size              | 2 MB
Max items per query        | Unlimited (paginated)
Max query complexity       | No hard limit (timeout-based)
Max indexing paths         | 500

Code Examples: - DTU monitoring - RU consumption tracking - Autoscaling configuration - Partition key design

Diagrams: - SQL DTU tiers - Cosmos DB RU model - Autoscaling behavior

Deliverables: - Azure SQL limits reference - Cosmos DB limits reference - Monitoring queries

Topic 16: Azure Storage & Networking Limits¶

What will be covered: - Blob Storage Limits

Metric                          | Standard | Premium
--------------------------------|----------|----------
Max storage account size        | 5 PB     | 35 TB
Max blob size (block blob)      | ~4.75 TB | ~4.75 TB
Max block size                  | 4,000 MB | 4,000 MB
Max IOPS per blob               | 500      | 100,000
Max throughput per blob         | 60 MB/s  | 200 GB/s
Max request rate (per account)  | 20,000   | 100,000

Azure Front Door Limits

Resource                    | Limit
----------------------------|----------
Max rules per Front Door    | 100
Max origins per origin group| 100
Max routes                  | 100
Max requests/second         | 250,000 (Standard), 1,000,000 (Premium)
Max bandwidth               | 100 Gbps

Code Examples: - Storage performance monitoring - AFD configuration - Throttling detection

Diagrams: - Storage tier comparison - AFD architecture

Deliverables: - Complete Azure service limits catalog - Monitoring dashboards - Throttling handlers

CYCLE 9: Per-Tenant Quotas by Edition (~4,000 lines)¶

Topic 17: Complete Edition Quota Matrix¶

What will be covered: - Comprehensive Quota Table | Resource Category | Metric | Free | Pro | Enterprise | |--------------------------|----------------------------|------------|------------|-------------| | API Access | Requests/minute | 60 | 600 | 3,000 | | | Concurrent requests | 5 | 50 | 200 | | | Request timeout | 30 sec | 60 sec | 120 sec | | Ingestion | Events/second | 10 | 100 | 500 | | | Events/day | 864,000 | 8,640,000 | 43,200,000 | | | Batch size (events) | 100 | 1,000 | 10,000 | | | Event size | 256 KB | 256 KB | 1 MB | | Storage | Total storage (GB) | 10 | 500 | 5,000+ | | | HOT retention (days) | 7-30 | 7-90 | 7-365 | | | WARM retention (days) | 30 | 365 | 730 | | | COLD retention (days) | N/A | 365-730 | 730-2,555 | | Query | Queries/minute | 30 | 300 | 1,500 | | | Result page size | 100 | 1,000 | 10,000 | | | Max query duration | 30 sec | 60 sec | 120 sec | | | Concurrent queries | 2 | 10 | 50 | | Export | Concurrent exports | 1 | 3 | 10 | | | Export bytes/day (GB) | 10 | 100 | 1,000+ | | | Max export size (GB) | 5 | 50 | 500 | | | Export compression | gzip | gzip | gzip/brotli | | Webhooks | Active subscriptions | 1 | 5 | 20 | | | Delivery attempts | 3 | 5 | 10 | | | Webhook log retention | 7 days | 30 days | 90 days | | | Webhooks/hour | 60 | 600 | 3,000 | | Search | Full-text search | ❌ | ✅ | ✅ | | | Advanced search | ❌ | ✅ | ✅ | | | Semantic search | ❌ | ❌ | ✅ | | Integrity | Integrity verification | ❌ | ❌ | ✅ | | | Merkle tree proofs | ❌ | ❌ | ✅ | | | Timestamp anchoring | ❌ | ❌ | ✅ | | Observability | Log retention | 7 days | 30 days | 90 days | | | Metrics retention | 30 days | 90 days | 365 days | | | Trace sampling | 0% | 10% | 100% | | Support | Support tier | Community | Business | Premium | | | SLA | Best-effort| 99.5% | 99.9% | | | Response time | 48 hours | 8 hours | 1 hour |

Code Examples: - Quota resolution by edition - Quota override mechanism - Quota enforcement middleware

Diagrams: - Edition comparison matrix - Quota inheritance hierarchy

Deliverables: - Complete quota matrix - Edition comparison tool - Quota calculator

Topic 18: Quota Management & Overrides¶

What will be covered: - Quota Override System

public class TenantQuotaOverride
{
    public string TenantId { get; set; }
    public string QuotaKey { get; set; }  // e.g., "ApiRateLimit", "StorageQuotaGB"
    public long OverrideValue { get; set; }
    public string Reason { get; set; }
    public DateTime EffectiveFrom { get; set; }
    public DateTime? ExpiresAt { get; set; }
    public string ApprovedBy { get; set; }
}

public async Task<TenantQuotas> GetEffectiveQuotasAsync(string tenantId)
{
    // 1. Get base quotas from edition
    var edition = await _tenantService.GetEditionAsync(tenantId);
    var baseQuotas = GetEditionBaseQuotas(edition);

    // 2. Apply tenant-specific overrides
    var overrides = await _quotaOverrideRepo.GetActiveOverridesAsync(tenantId);
    foreach (var override in overrides)
    {
        ApplyOverride(baseQuotas, override);
    }

    return baseQuotas;
}

Temporary Quota Increases
Request via support ticket
Approval from customer success manager
Time-bound (e.g., 7-30 days)
Automatic expiration and rollback
Permanent Quota Changes
Edition upgrade (Free → Pro → Enterprise)
Custom contract (Enterprise+)
Configuration deployment (Pulumi update)

Code Examples: - Quota override system - Temporary increase management - Edition upgrade flow

Diagrams: - Quota override workflow - Approval process

Deliverables: - Quota override system - Management UI/API - Approval workflow

CYCLE 10: Monitoring & Alerting (~3,000 lines)¶

Topic 19: Quota Usage Monitoring¶

What will be covered: - Real-Time Usage Tracking

// Current storage usage per tenant
AuditStorageMetrics
| where TimeGenerated > ago(5m)
| extend TenantId = tostring(customDimensions.TenantId)
| extend StorageGB = todouble(customDimensions.StorageGB)
| summarize CurrentStorage = max(StorageGB) by TenantId
| join kind=inner (TenantQuotas | project TenantId, StorageQuota = StorageQuotaGB) on TenantId
| extend PercentageUsed = (CurrentStorage * 100.0) / StorageQuota
| where PercentageUsed > 80
| order by PercentageUsed desc

Usage Dashboards
Per-tenant quota usage (API, storage, export)
Usage trends over time
Quota utilization heat map
Top consumers by resource type
Predictive Alerting
Linear regression on usage trends
Predict quota exhaustion date
Alert when estimated exhaustion < 7 days
Proactive upgrade recommendations

Code Examples: - Usage tracking queries (all quota types) - Dashboard JSON templates - Predictive analytics - Trend analysis

Diagrams: - Usage dashboard layout - Predictive alerting flow

Deliverables: - Monitoring query library - Dashboard templates - Predictive alerting

Topic 20: Alert Rules & Notifications¶

What will be covered: - Alert Thresholds

Threshold | Action                  | Recipient
----------|-------------------------|------------
80%       | Warning email           | Tenant admin
90%       | Critical email + banner | Tenant admin + CSM
95%       | Urgent email            | Tenant admin + CSM + Support
100%      | Service degradation     | All stakeholders

Alert Configuration

alerts:
  - name: StorageQuotaWarning
    condition: storage_usage_percent > 80
    severity: Warning
    frequency: 1h
    recipients:
      - tenant_admin
    actions:
      - send_email
      - log_to_telemetry

  - name: StorageQuotaExceeded
    condition: storage_usage_percent >= 100
    severity: Critical
    frequency: 5m
    recipients:
      - tenant_admin
      - customer_success_manager
      - support_team
    actions:
      - send_email
      - send_sms
      - create_incident
      - block_ingestion

Code Examples: - Alert rule configurations (all quota types) - Notification templates - Escalation workflows

Diagrams: - Alert escalation flow - Notification channels

Deliverables: - Alert rule library - Notification templates - Escalation procedures

CYCLE 11: Scaling Strategies (~3,000 lines)¶

Topic 21: Horizontal & Vertical Scaling¶

What will be covered: - Horizontal Scaling (Scale Out) - Add more pods/instances - KEDA autoscaling based on metrics - Kubernetes HPA (Horizontal Pod Autoscaler) - Azure App Service scaling plans

Vertical Scaling (Scale Up)
Increase CPU/memory per pod
Upgrade Azure service tiers (DTU, RU/s)
Premium storage tiers
Requires downtime or rolling update

Autoscaling Triggers

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: ingestion-scaler
spec:
  scaleTargetRef:
    name: ingestion
  minReplicaCount: 2
  maxReplicaCount: 50
  triggers:
  - type: azure-servicebus
    metadata:
      queueName: ingestion-queue
      messageCount: "100"
      namespace: atp-prod
  - type: cpu
    metadataRef:
      name: cpu-trigger
      threshold: "80"

Code Examples: - KEDA autoscaling configuration - HPA setup - Scaling strategies per service

Diagrams: - Horizontal vs. vertical scaling - KEDA autoscaling flow

Deliverables: - Scaling strategy guide - Autoscaling configurations - Capacity planning

Topic 22: Capacity Planning & Forecasting¶

What will be covered: - Growth Projections - Historical usage trends - Seasonality patterns - Customer acquisition forecasts - Feature adoption rates

Capacity Thresholds

Resource            | Current Capacity | Utilization Target | Scale Trigger
--------------------|------------------|--------------------|--------------
Ingestion Pods      | 10               | 70%                | CPU > 70%
Query Replicas      | 5                | 60%                | Queue > 1000
Storage (TB)        | 50               | 80%                | Usage > 40 TB
Service Bus MUs     | 4                | 75%                | Throughput > 3 MU
SQL DTUs            | 1000             | 70%                | DTU% > 70%

Cost-Aware Scaling
Prefer horizontal scaling (cheaper)
Scale down during off-peak
Reserved instances for baseline
Spot instances for burst capacity

Code Examples: - Capacity forecasting models - Cost optimization scripts - Scaling automation

Diagrams: - Capacity growth timeline - Cost-aware scaling strategy

Deliverables: - Capacity planning templates - Forecasting models - Cost optimization guide

CYCLE 12: Cost Optimization (~3,000 lines)¶

Topic 23: Cost-Aware Quota Design¶

What will be covered: - Cost Drivers by Resource | Resource | Cost Driver | Optimization Strategy | |-----------------------|----------------------|--------------------------------------| | Blob Storage (HOT) | GB stored × days | Lifecycle to WARM/COLD | | Azure SQL | DTU-hours | Right-size DTUs, autoscale | | Service Bus Premium | Messaging Units | Consolidate topics, tune prefetch | | Export Egress | GB transferred | Export windows, compression | | Azure Monitor | GB ingested | Sampling, field filtering | | Cosmos DB | RU/s provisioned | Autoscale, optimize queries |

Quota-Based Cost Control
Enforce export windows (2-6 AM local) to avoid peak egress costs
Limit trace sampling (Free: 0%, Pro: 10%, Enterprise: 100%)
Storage lifecycle automation (HOT → WARM → COLD)
Cap concurrent operations (reduce DTU/RU spikes)

Cost Allocation Tags

tags:
  environment: production
  product: audit-trail
  tenantId: acme-corp
  edition: enterprise
  costCenter: engineering

Code Examples: - Cost tracking queries - Budget alert configuration - Cost allocation tagging

Diagrams: - Cost breakdown by resource - Cost optimization workflow

Deliverables: - Cost optimization playbook - Budget alert templates - Cost allocation strategy

Topic 24: Edition Pricing & Cost Recovery¶

What will be covered: - Cost-Based Pricing Model | Edition | Base Cost/Month | Included Quotas | Overage Costs | |------------|-----------------|------------------------|------------------------| | Free | $0 | As per quota matrix | Not available | | Pro | $299/month | As per quota matrix | $0.10/GB storage | | Enterprise | $2,999/month | As per quota matrix | $0.05/GB storage |

Overage Billing
Storage: $0.10/GB/month (Pro), $0.05/GB/month (Enterprise)
API calls: $5 per 1M requests (Pro), $2 per 1M (Enterprise)
Export egress: $0.15/GB (Pro), $0.10/GB (Enterprise)
Cost Transparency
Monthly usage reports per tenant
Real-time cost estimator in dashboard
Projected month-end costs

Code Examples: - Cost calculator - Overage billing system - Usage report generator

Diagrams: - Pricing tier comparison - Overage billing flow

Deliverables: - Pricing model - Billing system - Usage reports

CYCLE 13: Quota Management & Governance (~2,500 lines)¶

Topic 25: Quota Governance Framework¶

What will be covered: - Quota Change Approval Process 1. Tenant requests quota increase (support ticket) 2. Customer Success Manager reviews usage patterns 3. Engineering validates capacity impact 4. Finance approves cost implications 5. Platform Engineer applies override 6. Tenant notified of approval/rejection

Exception Handling
Emergency quota increases (on-call approval)
Time-bound exceptions (7-30 days)
Compliance-driven exceptions (regulatory requirements)
Performance testing exceptions (temporary unlimited)

Quota Audit Trail

public class QuotaAuditLog
{
    public DateTime Timestamp { get; set; }
    public string TenantId { get; set; }
    public string QuotaKey { get; set; }
    public long PreviousValue { get; set; }
    public long NewValue { get; set; }
    public string Reason { get; set; }
    public string ApprovedBy { get; set; }
    public string ChangeType { get; set; }  // Increase, Decrease, Override, Reset
}

Code Examples: - Approval workflow - Exception handling - Audit trail implementation

Diagrams: - Quota change approval flow - Exception handling process

Deliverables: - Governance framework - Approval workflows - Audit trail system

Topic 26: Quota Review & Evolution¶

What will be covered: - Quarterly Quota Review - Analyze quota utilization trends - Identify under-utilized quotas (increase) - Identify over-utilized quotas (review pricing) - Customer feedback on quota pain points

Quota Evolution Roadmap
Phase 1 (Q1 2026): Baseline quotas (current)
Phase 2 (Q2 2026): Introduce burst quotas (+20% temporary)
Phase 3 (Q3 2026): Dynamic quotas based on usage patterns
Phase 4 (Q4 2026): AI-driven quota optimization
Competitive Benchmarking
Compare ATP quotas with competitors
Adjust to market standards
Differentiate on high-value features

Code Examples: - Quota analysis queries - Evolution tracking - Competitive comparison

Diagrams: - Quota evolution timeline - Competitive benchmarking

Deliverables: - Quarterly review process - Evolution roadmap - Benchmarking reports

CYCLE 14: Troubleshooting & Best Practices (~3,000 lines)¶

Topic 27: Troubleshooting Quota Issues¶

What will be covered: - Common Quota Problems - Problem: 429 Too Many Requests - Cause: API rate limit exceeded - Solution: Implement exponential backoff, request quota increase - Debug: Check X-RateLimit headers, review usage patterns

Problem: Storage quota exceeded
- Cause: Retention policy too long, no lifecycle automation
- Solution: Enable lifecycle policies, archive old data
- Debug: Query storage metrics, identify large tenants
Problem: Export quota exhausted
- Cause: Too many large exports
- Solution: Schedule exports in off-peak, enable compression
- Debug: Review export sizes, optimize queries
Problem: Message queue depth growing
- Cause: Consumers not keeping up with producers
- Solution: Scale consumers (KEDA), optimize processing
- Debug: Monitor queue metrics, check consumer errors

Quota Debugging Tools

# Check current quota usage
curl -H "Authorization: Bearer $TOKEN" \
  https://api.audit.connectsoft.io/v1/tenants/{tenantId}/quotas

# Get quota history
curl -H "Authorization: Bearer $TOKEN" \
  https://api.audit.connectsoft.io/v1/tenants/{tenantId}/quotas/history

# Request quota increase
curl -X POST -H "Authorization: Bearer $TOKEN" \
  -d '{"quotaKey": "ApiRateLimit", "requestedValue": 1200, "reason": "Black Friday traffic"}' \
  https://api.audit.connectsoft.io/v1/tenants/{tenantId}/quotas/increase-request

Code Examples: - Troubleshooting utilities - Quota debugging API - Common fixes

Diagrams: - Troubleshooting decision tree - Debug workflow

Deliverables: - Troubleshooting guide - Debug tools - Common problems catalog

Topic 28: Quota Best Practices¶

What will be covered: - Design Best Practices - ✅ Monitor Early: Track usage at 80%, not 100% - ✅ Fail Gracefully: Return 429 with Retry-After, not 500 - ✅ Burst Tolerance: Allow brief spikes (token bucket) - ✅ Cost-Aware: Design quotas aligned with cost drivers - ✅ Edition Alignment: Higher editions = higher quotas - ✅ Transparent: Show usage and limits in dashboard - ✅ Predictable: Time-based resets (minute, hour, day) - ✅ Auditable: Log all quota changes and exceptions

Implementation Best Practices
✅ Use distributed rate limiting (Redis)
✅ Cache quota lookups (reduce database load)
✅ Implement circuit breakers (prevent cascading failures)
✅ Test quota enforcement (chaos testing)
✅ Document quota limits (OpenAPI, SDKs)
✅ Provide upgrade paths (in-app prompts)
Operational Best Practices
✅ Review quotas quarterly
✅ Automate overage billing
✅ Track quota-related support tickets
✅ Benchmark against competitors
✅ Collect customer feedback
✅ Plan for growth (capacity planning)

Code Examples: - Best practice implementations - Testing strategies - Automation scripts

Diagrams: - Best practices checklist - Implementation patterns

Deliverables: - Best practices handbook - Implementation templates - Review checklists

Summary of Deliverables¶

Across all 14 cycles, this documentation will provide:

Philosophy & Architecture
Limits & quotas philosophy
Quota management architecture
Enforcement mechanisms
Rate Limiting
API rate limiting (all strategies)
Ingestion rate limits
Monitoring and alerting
Resource Limits
Storage quotas and capacity
Query and export limits
Messaging throughput limits
Compute and memory constraints
Azure Services
Complete Azure service limits catalog
SQL, Cosmos DB, Storage, Networking limits
Performance and IOPS limits
Edition Quotas
Complete per-tenant quota matrix
Quota override system
Edition comparison tools
Operations
Real-time monitoring and alerting
Scaling strategies and autoscaling
Cost optimization playbooks
Governance & Troubleshooting
Quota governance framework
Troubleshooting guides
Best practices and patterns

Configuration Reference: Rate limiting and quota configuration
Feature Flags: Edition-based feature gating
Architecture: System design and scalability
Data Architecture: Storage tiers and lifecycle
Environments: Environment-specific resource limits
Quality Gates: Performance testing and thresholds
Observability: Monitoring and alerting
Cost Optimization: Cost-aware quota design

This documentation plan covers complete limits, quotas, and resource constraints for ATP, from API rate limiting and storage capacity to Azure service limits, per-tenant quotas by edition, monitoring, scaling strategies, cost optimization, governance, and troubleshooting, ensuring fair resource allocation, cost predictability, and system stability across all environments.