What are API aggregation best practices?

API aggregation is the practice of combining data or functionality from multiple APIs into a single unified response or workflow. Best practices focus on making the aggregation fast, reliable, secure, and maintainable.

1. Define a clear contract

• Expose a well-documented schema for the aggregated response.
• Keep field names, types, and error formats consistent.
• Avoid leaking upstream API quirks to consumers.

2. Use timeout and retry policies carefully

• Set strict timeouts for each upstream API.
• Retry only idempotent calls.
• Use exponential backoff and jitter.
• Don’t retry aggressively when the upstream is failing.

3. Handle partial failures gracefully

• Decide whether the aggregate should fail entirely or return partial data.
• Include per-source status if some sources fail.
• Prefer degrading gracefully over returning nothing.

4. Optimize latency

• Call independent APIs in parallel.
• Cache responses where possible.
• Avoid unnecessary data fetching.
• Consider pagination or limiting payload size.

5. Protect against cascading failures

• Use circuit breakers for unreliable upstreams.
• Apply bulkheads or isolation so one failing API doesn’t take down the whole system.
• Rate-limit requests to upstreams.

6. Secure all integrations

• Store credentials safely, preferably in a secrets manager.
• Use least-privilege scopes.
• Validate and sanitize all upstream data.
• Encrypt traffic with TLS.
• Audit access to sensitive data.

7. Normalize and validate data

• Map different upstream formats into one canonical model.
• Validate data types and required fields.
• Handle missing or inconsistent fields predictably.

8. Monitor and observe everything

• Track latency, error rates, and timeout rates per upstream API.
• Add distributed tracing and correlation IDs.
• Log enough for troubleshooting, but avoid sensitive data.

9. Version carefully

• Version your aggregate API so changes don’t break clients.
• Be cautious when upstream APIs change.
• Use adapter layers to shield your clients from upstream churn.

10. Design for maintainability

• Keep aggregation logic modular.
• Isolate each upstream integration in its own component.
• Write contract tests and integration tests.
• Mock upstream APIs in tests.

11. Be mindful of rate limits and quotas

• Cache aggressively when data is reusable.
• Respect upstream quotas.
• Use batching where supported.

12. Decide where aggregation should happen

• Backend aggregation is usually better than client-side for security, performance, and consistency.
• Consider GraphQL or API gateways if your use case fits.
• Keep server-side aggregation simple when possible.

Common anti-patterns

• Making sequential calls when they could be parallel.
• Passing raw upstream responses directly to clients.
• No timeouts or retries.
• Ignoring partial failures.
• Tight coupling to upstream response shapes.
• Aggregating too much in one endpoint, making it slow and brittle.

If you want, I can also give you:

1. a checklist for designing an aggregation layer,
2. an example architecture, or
3. sample code in a specific language.