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Analytics & Insights

Monitor mock simulation usage, performance, and patterns with comprehensive analytics dashboards. Track request patterns, consumer behavior, error rates, latency distribution, and AI-powered insights.

Prerequisites​

  • An existing mock simulation with traffic
  • Active request history (data to analyze)
  • Basic understanding of HTTP metrics

Analytics Dashboard Overview​

The analytics dashboard provides multiple views of simulation traffic:

Key Metrics​

  • Total Requests - Number of requests in time period
  • Error Rate - Percentage of failed requests
  • Success Rate - Percentage of successful requests
  • Average Latency - Mean response time
  • P95 Latency - 95th percentile response time
  • Unique Consumers - Number of different clients
  • Top Routes - Most frequently accessed endpoints

Time Ranges​

Select analysis period:

  • 1 Day (1d) - Hourly buckets
  • 7 Days (7d) - Hourly buckets
  • 30 Days (30d) - Daily buckets
  • 90 Days (90d) - Daily buckets

Accessing Analytics​

Simulation Analytics​

  1. Open mock simulation
  2. Click Analytics tab
  3. Select time range
  4. View overview and metrics

Company-Wide Analytics​

View aggregated metrics across all simulations:

  1. Go to dashboard
  2. Click Analytics Overview or Company Analytics
  3. See cross-simulation statistics
  4. Drill down to specific simulations

Analytics Views​

Overview​

Summary of key metrics:

Simulation: Payment Service (24h)
├─ Total Requests: 2,545
├─ Success Rate: 96.2%
├─ Error Rate: 3.8%
├─ Avg Latency: 125ms
├─ P95 Latency: 380ms
├─ Unique Consumers: 18
└─ Top Route: POST /api/payments (485 requests)

Click metrics to drill down for details.

Route Heatmap​

Visualize request distribution across routes and time:

Heatmap Display:

  • Y-axis: Routes (methods + paths)
  • X-axis: Time buckets (hours or days)
  • Color intensity: Request volume

Using Heatmap:

  1. View which routes are busiest
  2. Identify peak usage times
  3. Spot unused routes (no color)
  4. Find sudden spikes (bright spots)
  5. Click cell to drill into route traffic

Example:

GET /api/users      ████████████ (high traffic)
POST /api/users     ████████ (medium traffic)
PUT /api/users/:id  ███ (low traffic)
DELETE /api/users   █ (very low traffic)

9am  10am 11am 12pm 1pm  2pm  3pm

Consumer Tracking​

Track unique consumers by fingerprint:

Consumer Fingerprint = IP address + User-Agent hash

View consumers:

  1. Click Consumers in analytics
  2. See table with:
    • Consumer fingerprint (anonymized)
    • Request count
    • First seen
    • Last seen
    • Top routes
    • HTTP methods used

Use For:

  • Identify test clients vs. users
  • Track integration partners
  • Monitor malicious clients
  • Quota tracking per consumer

Error Patterns​

Analyze errors by route and status code:

Error Analysis:

  1. Click Errors view
  2. See errors grouped by:
    • Route (method + path)
    • HTTP status code (400, 401, 403, 404, 500, etc.)
    • Error count

Example:

POST /api/auth/login
├─ 401 Unauthorized: 23 errors
│  └─ Invalid credentials (from logs)
├─ 429 Too Many Requests: 5 errors
│  └─ Rate limit exceeded
└─ 500 Internal Error: 2 errors
   └─ Database connection timeout

GET /api/users/:id
├─ 404 Not Found: 15 errors
│  └─ User ID not found
└─ 403 Forbidden: 3 errors
   └─ Permission denied

Insights:

  • Most common errors
  • Error rate per route
  • Error distribution
  • Trends over time

Latency Distribution​

Analyze response time performance:

Percentiles:

Route: GET /api/data
├─ Min: 15ms
├─ P50: 45ms
├─ P95: 180ms
├─ P99: 420ms
└─ Max: 2450ms

Analysis:

  1. View latency stats per route
  2. Identify slow routes
  3. Compare P50 vs P95 (variability)
  4. Spot outliers (max)
  5. Track trends over time

Use For:

  • Performance tuning
  • SLA compliance checking
  • Client timeout issues
  • Load balancing decisions

Time-series data for charting:

Trend Data:

Time Range: Last 7 Days (hourly buckets)
[
  { time: "2026-01-15T09:00:00Z", requests: 142, errors: 5, latency: 120 },
  { time: "2026-01-15T10:00:00Z", requests: 185, errors: 7, latency: 135 },
  { time: "2026-01-15T11:00:00Z", requests: 223, errors: 12, latency: 150 },
  ...
]

Chart Types:

  • Line Chart - Request volume over time
  • Area Chart - Success vs. error stacked
  • Bar Chart - Requests per hour
  • Combination - Multiple metrics

Analyze:

  • Peak usage times
  • Low traffic periods
  • Error spikes
  • Latency trends
  • Day-over-day patterns

Cost Attribution​

Estimate costs per route:

Cost Calculation: $0.001 per request

Route: POST /api/users (500 requests)
  Cost: $0.50

Route: GET /api/data (2000 requests)
  Cost: $2.00

Total Simulation Cost: $10.45

(Stub implementation for future billing integration)

AI-Powered Insights​

Automatic analysis and recommendations:

Insight Categories​

Unused Routes

Finding: GET /api/old-endpoint has 0 requests (30 days)
Impact: Dead code in mock config
Action: Consider removing if no longer needed

High Error Rate

Finding: POST /api/upload has 15% error rate
Impact: Likely indicates validation issues
Action: Review error logs and fix validation schema

Slow Responses

Finding: PUT /api/process has P95 latency of 2.5s
Impact: May cause timeouts in tests
Action: Reduce simulated delay or review complex processing

Missing Error Coverage

Finding: GET /api/data only returns 200 responses
Impact: No error scenarios mocked
Action: Add 400, 401, 404, 500 response variants

Viewing Insights​

  1. Open simulation analytics
  2. Click Insights tab
  3. See list of insights:
    • Title
    • Severity (critical, warning, info)
    • Description
    • Recommended action
    • Status (active, dismissed, resolved)

Refreshing Insights​

Generate fresh insights:

  1. Click Refresh Insights
  2. System re-analyzes simulation
  3. Previous active insights are resolved
  4. New insights generated
  5. View updated insight list

Managing Insights​

Dismiss Insight

Acknowledge but don't resolve:

  1. Click insight
  2. Click Dismiss
  3. Insight marked "dismissed"
  4. Hidden from active list

Resolve Insight

Take action on insight:

  1. Make recommended change (e.g., add response)
  2. Click insight
  3. Click Mark as Resolved
  4. Insight removed from active list

View Resolved

See completed insights:

  1. Click Show Resolved
  2. View archived insights
  3. See action taken and when

Analytics Workflow​

Monitoring Simulation Health​

  1. Check Overview - See current metrics
  2. Review Errors - Find problem patterns
  3. Analyze Latency - Identify performance issues
  4. Read Insights - See AI recommendations
  5. Take Action - Fix issues
  6. Verify Trends - Confirm improvement

Identifying Issues​

High Error Rate:

  1. Go to Error Patterns view
  2. Find routes with errors
  3. Check error codes (401 = auth, 400 = validation, 500 = server)
  4. Review validation schema or response logic
  5. Add test cases for error scenarios

Slow Routes:

  1. Go to Latency Distribution
  2. Sort by P95 latency
  3. Identify slowest routes
  4. Reduce simulated delay (latencyMs)
  5. Or review response processing logic
  6. Verify new latency in next analytics refresh

Unused Routes:

  1. Check heatmap for no-color rows
  2. Identify routes with zero requests
  3. Confirm they're not needed
  4. Update documentation
  5. Consider removing if truly unused

Analytics Use Cases​

Development​

Monitor your mock simulation while developing:

  • Verify routes are being called
  • Check response times are reasonable
  • Catch errors in validation logic
  • Track coverage of scenarios

Testing​

Analyze test traffic patterns:

  • Ensure all critical paths exercised
  • Check error scenarios tested
  • Verify performance expectations met
  • Identify untested code paths

Integration​

Monitor consumer behavior:

  • Track different client implementations
  • Identify problematic patterns
  • Monitor error patterns from consumers
  • Ensure compatibility

Onboarding​

Track new consumer adoption:

  • Monitor connection growth
  • Track request volume growth
  • Identify early errors
  • Support integration issues

Incident Response​

Analyze traffic during issues:

  • When did problems start?
  • Which routes affected?
  • Error rate spike?
  • Latency degradation?
  • Consumer impact?

Analytics Best Practices​

Regular Monitoring​

  • Check analytics daily during active development
  • Weekly review of trends and insights
  • Monthly assessment of health metrics
  • Quarterly planning based on usage patterns

Performance Tuning​

  1. Monitor latency trends
  2. Identify slow routes
  3. Reduce simulated delays
  4. Verify improvement in next refresh
  5. Repeat for next slowest route

Error Reduction​

  1. Check error patterns regularly
  2. Focus on high-error routes
  3. Review validation rules
  4. Add error response variants
  5. Track error rate improvement

Capacity Planning​

Use analytics to anticipate needs:

  • Growing request volume
  • New consumer onboarding
  • Seasonal traffic patterns
  • Resource scaling decisions

Troubleshooting​

No Analytics Data​

  • Ensure simulation has traffic
  • Wait 5-10 minutes for data to aggregate
  • Check time range covers traffic period
  • Verify simulation is active

Metrics Look Wrong​

  • Refresh the analytics page
  • Check time range selection
  • Verify you're viewing correct simulation
  • Compare against request logs

Insights Not Generating​

  • Ensure simulation has sufficient traffic
  • Click Refresh Insights to trigger analysis
  • Wait for re-analysis to complete
  • Check for system errors

API Reference​

Analytics Endpoints​

MethodPathDescription
GET/instances/:id/analytics/overviewGet summary metrics
GET/instances/:id/analytics/heatmapGet route heatmap
GET/instances/:id/analytics/consumersGet consumer fingerprints
GET/instances/:id/analytics/errorsGet error patterns
GET/instances/:id/analytics/latencyGet latency distribution
GET/instances/:id/analytics/trendsGet time-series trends
GET/instances/:id/analytics/costGet cost attribution
GET/instances/:id/insightsList insights
POST/instances/:id/insights/refreshRefresh insights
PATCH/instances/:id/insights/:insightIdUpdate insight status

Cross-Simulation Analytics​

MethodPathDescription
GET/analytics/overviewCross-simulation summary
GET/analytics/costCross-simulation costs

Next Steps​