Monitoring and Analytics

Once your API is live, you need eyes on it. "It works on my machine" doesn't help when a customer says 500 errors are spiking.

Types of Monitoring

1. Availability (Uptime)

Is the API reachable?

Health Checks: A /health endpoint that checks DB connections.

Synthetic Monitoring: Automating calls (like Apidog Scheduled Tasks) to run every minute from different global locations to verify the API is up.

2. Performance (Latency)

How fast is the API?

Average Latency: "200ms". Good for general trends.

P95 / P99 Latency: "99% of requests are faster than 500ms." This is more important than average, as it shows the experience of your slowest users (often the 'heaviest' and most valuable customers).

3. Usage (Business Metrics)

How is the API being used?

Traffic Patterns: "1M calls per day."

Top Consumers: "User A accounts for 30% of traffic."

Popular Endpoints: "/search is used 10x more than /profile."

Observability: Logs, Metrics, Traces

To debug why something failed, you need Observability.

Logs: "What happened?" (Timestamped error messages).

Metrics: "What is happening now?" (CPU usage, Request/sec).

Traces: "Where did it happen?" (Distributed tracing across microservices).

Key Takeaways

Uptime != Health: Just because the server responds to ping doesn't mean the database is connected. Use deep health checks.

Watch the Tail: Monitor P99 latency to catch performance issues that affect outliers.

Business Value: Use analytics to understand customer behavior and drive product decisions.

Proactive: Set up alerts so you know about an outage before your customers tweet about it.

Continue with → API Versioning Strategies

Monitoring and Analytics

Types of Monitoring#

1. Availability (Uptime)#

2. Performance (Latency)#

3. Usage (Business Metrics)#