Service Debugging

Structured approach to investigating and fixing service issues. Symptoms in, root cause out.

When to Use

• API endpoint returning errors (4xx, 5xx)
• Performance degradation or slow queries
• Service not starting or crashing
• Data inconsistency between services
• After a deploy when something broke
• User reports "something is broken"

Process

1. Gather Symptoms

Before touching code, collect:

• What's broken? (specific endpoint, feature, or behavior)
• When did it start? (after a deploy? gradually? suddenly?)
• Who's affected? (all users, specific users, specific data?)
• Error messages? (logs, HTTP responses, stack traces)

2. Check the Obvious

Run these first — they catch 80% of issues:

# Recent deploys (did someone push something?)
git log --oneline -10

# Service health
curl -s http://localhost:8080/health | jq .

# Recent errors in logs
grep -i "error\|exception\|fatal" logs/app.log | tail -20

# Database connectivity
psql -h $DB_HOST -U $DB_USER -d $DB_NAME -c "SELECT 1"

# Environment variables (missing or wrong?)
env | grep -i "DB_\|API_\|SECRET_" | sort

3. Narrow Down

deleted_at

4. Reproduce

• Can you trigger the bug locally?
• What's the minimal request that fails?
• Does it fail consistently or intermittently?

5. Find Root Cause

Use git bisect if it's a regression:

git bisect start
git bisect bad HEAD
git bisect good <last-known-good-commit>
# Test each commit until you find the one that broke it

Use grep to find related code:

# Find where the error message comes from
grep -r "error message text" --include="*.kt" src/

# Find all callers of a broken function
grep -r "functionName" --include="*.kt" src/

6. Fix and Verify

1. Write a test that reproduces the bug (red)
2. Fix the code (green)
3. Run full test suite
4. Test manually if it's a user-facing issue

See

common-issues.md

for a catalog of frequently seen bugs and their fixes.

Gotchas

• Don't fix the symptom, fix the cause. Adding a null check that hides a data issue means the data issue will bite you later.
• Check the deploy log before blaming the code. Config changes, environment variable updates, and infra changes cause more outages than code bugs.
• "It works on my machine" usually means environment difference. Compare local env vars, database state, and service versions with the target environment.
• Intermittent failures are usually race conditions. If it fails 1 in 10 times, look for concurrent access, shared mutable state, or connection pool exhaustion.
• Don't restart the service as your first debugging step. You'll lose the state that helps you diagnose. Read logs first, then restart if needed.
• Soft-deleted records are the #1 "data missing" cause. Always check

  deleted_at IS NULL

  in your queries.

Rules

• Always gather symptoms before changing code
• Write a failing test before fixing
• Check recent git history — most bugs are regressions
• Don't deploy a fix without understanding the root cause
• Document the incident if it affected users