How to Prepare Your API for a Traffic Spike (Checklist)
Traffic spikes are predictable (launches, sales) or surprising (viral posts). Either way, APIs fail in predictable ways: connection exhaustion, slow queries, and cascading timeouts. This checklist helps you prepare before the spike — with Load Curl validating each step.
1. Define your target load profile
Work backward from expected traffic:
- Peak concurrent users (marketing forecast × safety factor)
- Requests per user session
- Duration of elevated traffic (hours vs days)
Configure a Load Curl test that matches 80% of worst-case first, then ramp to 100% in staging.
2. Load test critical paths end-to-end
Do not only test /health. Prioritize:
- Authentication and session refresh
- Read-heavy paths (search, feeds, catalogs)
- Write paths (checkout, submissions) with realistic payloads
- Webhooks or async jobs triggered by API calls
Use the scenario builder to chain dependent calls when flows span multiple endpoints.
3. Validate autoscaling and limits
Confirm Kubernetes HPA, serverless concurrency limits, and database connection pools scale with load. A load test that passes at minute 5 but fails at minute 30 often means scaling lag or pool exhaustion.
4. Cache and CDN strategy
- Are cache headers correct for static and semi-static responses?
- Does cache busting on deploy invalidate safely?
- Will CDN shield origin during spikes?
Compare report cards with and without CDN in the path when possible.
5. Database and downstream dependencies
- Index hot queries identified under load
- Set timeouts on outbound HTTP calls — unbounded waits amplify failures
- Use circuit breakers where appropriate
- Coordinate with teams owning shared databases in staging
6. Rate limiting and abuse protection
Ensure legitimate spike traffic is not classified as abuse. Tune WAF and rate limits using test traffic from distributed workers, not a single IP.
7. Observability and on-call
- Dashboards for golden signals per service
- Alerts on SLO burn rates, not just CPU
- Runbooks linked from PagerDuty for load-related incidents
- Load Curl threshold alerts on Pro for automated notifications when grades slip
8. Run a game day
Schedule a tabletop + live load test with engineering, SRE, and product:
- Execute peak load test in staging
- Practice scaling actions manually
- Practice rollback if a deploy coincides with the event
- Document actual RPS achieved vs target
9. Production validation (optional)
If staging cannot match scale, run a limited production test with executive approval. See our guide on staging vs production load tests for guardrails.
10. Post-spike retrospective
After the event, compare Load Curl report cards to real APM data. Calibrate future tests — if staging was optimistic, increase concurrency margins next time.
Quick reference
| Item | Tooling | |------|---------| | Load simulation | Load Curl distributed workers | | Grade / SLO check | Report card A–F | | CI gate | GitHub Actions + Load Curl CLI | | Alerts | Threshold alerts (Pro) |
Spikes are stressful; preparation is not optional. Run your checklist, fix the red dimensions on your report card, and ship knowing you tested — not hoping.