How to Monitor Your API Endpoints for Uptime and Performance

If your product has an API — whether it's a public REST API, a mobile app backend, or internal microservices — monitoring it is different from monitoring a website. A marketing page returning 200 OK doesn't mean your API is healthy.

Here's how to set up effective API monitoring.

Why API monitoring is different

A website check is simple: hit the URL, get a 200, done. APIs are more nuanced:

Different endpoints have different health. Your /users endpoint might work fine while /payments is broken due to a downstream dependency.
Response codes matter more. A website might return a "sorry" page with a 200 status. An API returning 200 with an error in the body is a silent failure.
Response time is critical. A website that loads in 3 seconds is slow but usable. An API call that takes 3 seconds can cascade into timeouts across every service that depends on it.
Authentication adds complexity. Many API endpoints require tokens, API keys, or specific headers.

What to monitor

Health check endpoint

The most important thing to monitor is a dedicated health check endpoint. If you don't have one, create one:

GET /health

A good health check verifies your critical dependencies:

{
  "status": "ok",
  "database": "connected",
  "cache": "connected",
  "queue": "connected",
  "version": "2.4.1"
}

Return 200 when everything is healthy, 503 when any critical dependency is down. This gives your monitoring tool a clear signal.

Critical business endpoints

Beyond the health check, monitor the endpoints your users hit most:

Authentication — /api/login or /api/auth/token. If auth is down, nothing works.
Core operations — whatever your product's main action is. For an e-commerce API, that's /api/orders. For a messaging app, /api/messages.
Third-party integrations — payment processing, email sending, SMS. These fail independently of your infrastructure.

Response time thresholds

Set alerts not just for outages but for performance degradation:

< 200ms — healthy for most APIs
200–500ms — acceptable, but worth watching
500ms–2s — degraded, users will notice
> 2s — effectively broken for real-time operations

Setting up API monitoring in PoppaPing

Add a new monitor and enter your API endpoint URL (e.g. https://api.yourapp.com/health)
Set the check interval — for APIs, every 30 seconds or 1 minute is recommended since even brief outages cause cascading failures
Choose your HTTP method — GET works for most endpoints; HEAD is faster if your server supports it
Set up alert channels — Slack/Discord webhooks for team awareness, email or PagerDuty for on-call escalation

Monitoring authenticated endpoints

If your API requires authentication, you have two options:

Option 1: Public health endpoint. Create an unauthenticated /health endpoint that still checks internal dependencies. This is the standard approach — most API frameworks support it.

Option 2: Webhook monitoring. Use PoppaPing's webhook alerting to integrate with your own internal checks. Your app runs its own health verification and calls PoppaPing's API to report status.

Best practices

Monitor from multiple regions. An API that works from US-East but times out from Europe is half-broken. Multi-region monitoring catches regional routing issues and CDN problems.

Don't just check the load balancer. A load balancer returning 200 doesn't mean your app servers are healthy. Point your monitor at the actual application endpoint, not the infrastructure health check.

Monitor dependencies separately. If your API depends on a database, a cache, and a payment provider, monitor each one independently. When something breaks, you'll know immediately which dependency failed instead of debugging blindly.

Set up synthetic transactions. For critical flows (sign up, create order, process payment), set up monitors that actually exercise the flow, not just check if the endpoint responds. A 200 response from /api/orders is meaningless if it's returning empty results because the database is disconnected.

Track response time trends. A gradual slowdown from 100ms to 800ms over a week usually means a growing dataset, a memory leak, or connection pool exhaustion. Catching this trend before it becomes an outage is the difference between a fix and a firefight.

Common API failure patterns

Understanding common failure modes helps you set up better monitoring:

Cascading timeouts. Service A calls Service B calls Service C. Service C gets slow, causing B to time out, causing A to time out. Monitor each service independently to find the source quickly.

Connection pool exhaustion. Your app opens database connections faster than it closes them. Health checks pass (they get a connection from the pool) until the pool fills completely and everything fails at once. Monitor both response time and error rate to catch the gradual degradation.

SSL certificate expiration. Your API works perfectly until the cert expires and every client gets a TLS error. Monitor the HTTPS endpoint to catch cert issues before they become outages.

DNS failures. Your API resolves to the right IP until a DNS TTL expires and propagation goes wrong. Multi-region monitoring from different DNS resolvers catches this.

The minimum viable setup

If you do nothing else:

Create a /health endpoint that checks your database connection
Monitor it every 60 seconds from multiple regions
Alert to Slack or Discord
Set a response time alert threshold at 2 seconds

That covers 90% of the outage scenarios you'll encounter. You can add more sophisticated monitoring as your API grows.