Monitoring & Logging: Track API Usage
Monitor your API integrations like a pro. Master the analytics dashboard, error tracking, usage alerts, custom metrics, and observability best practices for production-grade systems.
TL;DR
- AppHighway Analytics Dashboard tracks all API usage, costs, and performance metrics
- Set up usage alerts: get notified when points drop below threshold or API errors spike
- Error tracking: identify which APIs fail most often and why
- Custom metrics: export usage data to external monitoring tools (Datadog, Grafana)
- Real-time logs: debug API calls with request/response inspection
- Cost analysis: identify which APIs consume the most points and optimize
Why Monitoring Matters
Production systems require visibility. Without monitoring, you're flying blindâunaware of errors, cost spikes, or performance degradation until users complain. AppHighway's analytics dashboard provides real-time insights into API usage, errors, and costs, enabling proactive management and optimization.
Analytics Dashboard Overview
The AppHighway dashboard provides comprehensive insights into your API usage.
Usage Metrics
Track total API calls, points consumed, and request volume over time
Insights: Identify usage trends, peak hours, and seasonal patterns
Cost Tracking
Monitor points consumption per API and per day/week/month
Insights: Identify most expensive APIs and optimize workflow
Error Rates
Track failed requests, error types, and success rates per API
Insights: Detect reliability issues early and fix before impact
Response Time
Monitor average API response times and latency percentiles
Insights: Identify slow APIs and optimize performance bottlenecks
Error Tracking & Debugging
Identify and resolve API errors quickly with comprehensive error tracking.
Common Error Types
401 Unauthorized: Invalid or expired API token
429 Too Many Requests: Rate limit exceeded
402 Payment Required: Insufficient points balance
400 Bad Request: Invalid input parameters
500 Internal Server Error: API processing failure
Debugging Workflow
Step 1: Identify error pattern in dashboard (which API, frequency, time)
Step 2: Inspect failed request details (headers, body, parameters)
Step 3: Check error message and status code for root cause
Step 4: Test fix in development environment
Step 5: Monitor production for resolution confirmation
Usage Alerts & Notifications
Stay informed with automated alerts for critical events.
Low Points Balance
Triggered when points balance drops below threshold (e.g., <100 points)
Action: Purchase more points before running out
Error Rate Spike
Triggered when error rate exceeds 10% within 1 hour
Action: Investigate and fix failing API calls
Unusual Usage Pattern
Triggered when API call volume exceeds 3x normal baseline
Action: Check for unexpected traffic or potential abuse
Token Expiration Warning
Triggered 7 days before API token expires
Action: Rotate token to avoid service disruption
Notification Channels
Email: Receive alerts via email (default)
Webhook: POST alerts to custom endpoint for integration with Slack, PagerDuty
SMS: Critical alerts via SMS (premium feature)
Custom Metrics & Export
Export AppHighway metrics to external monitoring and observability platforms.
Datadog Integration
Forward metrics to Datadog for centralized monitoring
Metrics: API call count, error rate, response time, points consumed
Grafana Dashboards
Build custom dashboards with Prometheus metrics
Use case: Visualize API usage alongside other infrastructure metrics
AWS CloudWatch
Send metrics to CloudWatch for AWS-native monitoring
Use case: Unified monitoring for Lambda + AppHighway tools
New Relic APM
Track API calls as distributed traces in APM
Use case: End-to-end request tracing across services
Real-World Example: E-commerce Monitoring Setup
Scenario: E-commerce platform processing 10,000 orders/day with AppHighway tools
Monitoring Setup
Dashboard: Track points consumption per API (Structify, Email Validator, etc.)
Alerts: Low points warning (<500 pts), error rate spike (>5%)
Logs: Enable request logging for failed Structify calls
Metrics: Export to Datadog for unified infrastructure monitoring
Reports: Weekly cost analysis email to finance team
Incident Example
Problem: Error rate spiked to 30% at 2 AM, 300 failed Structify calls
Detection: Alert fired within 5 minutes via email + Slack webhook
Diagnosis: Dashboard logs showed 400 Bad Request errorsâinvalid JSON input
Resolution: Fixed upstream data validation bug in order parser
Outcome: Error rate dropped to 0.1% within 30 minutes, prevented 2,000+ failed orders
Monitoring Best Practices
Set up alerts BEFORE going to productionâdon't wait for outages
Monitor golden signals: latency, traffic, errors, saturation
Review dashboard weekly to identify optimization opportunities
Enable request logging for critical APIs (can be disabled for cost savings)
Export metrics to external tools for long-term trend analysis
Document incident response proceduresâknow what to do when alerts fire
Test alert thresholds in staging before deploying to production
Logging Levels & Retention
Minimal Logging (Free)
Includes: API call count, success/failure status, points consumed
Retention: 7 days
Standard Logging (Included)
Includes: All minimal + error messages, response times
Retention: 30 days
Detailed Logging (Premium)
Includes: All standard + request/response bodies, headers, IP addresses
Retention: 90 days
Use case: Debugging complex issues, compliance audits
Next Steps
Start monitoring today
Explore Analytics Dashboard
View your current API usage, costs, and error rates in real-time.
Configure Usage Alerts
Set up notifications for low points balance and error rate spikes.
Visibility Prevents Outages
Monitoring transforms reactive firefighting into proactive management. With the analytics dashboard, error tracking, and usage alerts, you'll catch issues before they impact users. Set up monitoring on day oneâyour future self will thank you.
Ready to monitor your tools? Explore the analytics dashboard and configure your first alert.