How do I find the dependency causing API failures?

To find the dependency causing API failures, use a divide-and-conquer approach and check recent changes, logs, and request paths.

1) Confirm the failure scope

• Is it all API calls or only certain endpoints/users?
• Is it intermittent or constant?
• Did it start after a deploy, config change, or downstream outage?

2) Check logs and error traces

Look for:

• HTTP status codes: 500, 502, 503, 504
• Timeout messages
• Connection errors
• “upstream unavailable”, “circuit breaker open”, “DNS failure”, “TLS handshake failed”

In logs, identify:

• The first failing service
• The downstream call it was making when it failed
• Correlated request IDs / trace IDs

3) Use distributed tracing if available

Tools like OpenTelemetry, Datadog, Jaeger, or New Relic can show:

• Which service is slow/failing
• Which dependency call is taking too long
• Whether the API fails before reaching a dependency or after a specific one

Start from the API request and follow the trace until the error appears.

4) Isolate dependencies one by one

If you have several dependencies (DB, cache, auth service, payment service, third-party API):

• Temporarily stub/mock one dependency at a time
• Disable non-critical calls via feature flags
• Compare behavior when a dependency is bypassed

If the API works when a dependency is bypassed, that dependency is likely the cause.

5) Look at dependency health metrics

Check for:

• Latency spikes
• Error rate spikes
• Connection pool exhaustion
• Rate limiting
• CPU/memory saturation
• Restart loops
• 4xx/5xx from downstream services

6) Verify timeouts and retries

A bad dependency often causes:

• Too-short timeouts
• Retry storms
• Thread pool exhaustion
• Cascading failures

Check whether:

• Retries are masking the real root cause
• Timeouts are hitting a specific downstream call
• Circuit breakers are opening

7) Reproduce with targeted tests

• Call the API with known inputs that fail
• Replay a failing request in staging
• Use network tools to simulate a slow or unavailable dependency
• Watch which component breaks first

8) Common suspects

Most often the culprit is:

• Database
• Cache/Redis
• Auth/identity provider
• Message queue
• External HTTP API
• DNS/network layer
• Configuration/secrets service

Quick triage checklist

1. Find the first error in logs
2. Match it to a trace/request ID
3. Identify the downstream call at that moment
4. Check dependency metrics for spikes
5. Disable or stub dependencies to isolate
6. Confirm with a repro

If you want, I can help you build a step-by-step troubleshooting flow for your specific stack (e.g., Kubernetes, AWS, Node.js, Java/Spring, Python/FastAPI).