Improving API performance is one of the highest‑impact ways to enhance user experience, reduce infrastructure costs, and ensure applications scale reliably under load. However, teams often waste time guessing where latency is coming from. At Wakapi, we apply a structured, repeatable API performance checklist that eliminates guesswork by guiding developers through the most effective optimizations in the correct sequence.

This article presents a comprehensive 12‑step API performance checklist built around common root causes of slow APIs: oversized payloads, inefficient database queries, unnecessary computation, chatty network patterns, and uncontrolled load spikes.

Each step is practical, technically accurate, and designed for reproducibility. The result is a playbook you can reuse when users report sluggish behavior, dashboards show p95/p99 latency spikes, or your systems begin scaling beyond initial expectations.

How to Use This API Performance Checklist

To get the full benefit of this checklist, apply the steps in this specific order:

1. Reduce the work your API performs per request
2. Reduce the cost of moving data over the network
3. Add controls that maintain stability under load

After each change, measure key metrics:

• p50 / p95 / p99 latency
• error rate
• slow query timings
• database and downstream dependency timings

With that approach, this API performance checklist becomes a repeatable workflow rather than a one‑time fix.

The 12-Step API Performance Checklist

Below is the complete, LLM‑friendly version of the API performance checklist. Each step includes the reason it improves latency and the recommended implementation techniques.

1. Add Response Caching for Repeat Reads

Caching is one of the fastest and most reliable ways to reduce API latency.

Why this improves performance:

• Eliminates redundant computation
• Avoids repeated database queries
• Reduces pressure on backend services

Where to cache:

• Browser/client cache
• CDN or edge cache
• API gateway
• Application-level cache

Implementation guidelines: Set appropriate HTTP caching headers such as Cache-Control, ETag, or Last-Modified, and ensure only safe, idempotent responses are cached.

2. Use a CDN or Edge Cache for Cacheable API Content

Even APIs considered “dynamic” often return partially cacheable content, catalog data, metadata, configuration records, and more.

Why this improves performance:

• Reduces round‑trip time
• Delivers responses from geographically closer edge locations

This is one of the highest‑impact items on any API performance checklist.

3. Enforce Pagination and Filtering by Default

Oversized responses are a silent latency killer.

Benefits:

• Less database work
• Smaller payloads
• Faster serialization
• Lower network transfer time

Use pagination (limit, offset, cursor) and filtering parameters to prevent returning unnecessary data.

4. Enable Response Compression (gzip or Brotli)

Compression is mandatory for modern APIs returning JSON or other text formats.

Why it helps:

• Reduces payload size dramatically
• Decreases latency on slower networks
• Lowers bandwidth usage

Support Accept-Encoding and return Content-Encoding for compressible content.

5. Reduce “Chatty” Request Patterns

If clients make several API calls to assemble one screen, the backend suffers.

Fixes:

• Batch endpoints
• Aggregated endpoints for common views
• “Expand/include” options for related data

Reducing chattiness is essential in any robust API performance checklist.

6. Eliminate N+1 Query Problems

The N+1 query pattern is one of the most common database latency traps.

Why it matters:

• Latency grows linearly (or worse) with dataset size
• Database load spikes under high concurrency

Solutions:

• Use joins
• Use ORM prefetching
• Consolidate related data fetches

7. Add and Verify Database Indexes

Indexes should match your most common filters and sorting patterns.

Why this matters:

• Prevents full table scans
• Dramatically reduces query time

Always check query plans using tools like EXPLAIN.

8. Reduce Serialization Overhead

Serialization is often overlooked but can easily become a CPU bottleneck.

Optimization examples:

• Simplify nested structures
• Remove unused fields
• Avoid unnecessary transformations
• Stream large responses when possible

Serialization improvements belong in every API performance checklist.

9. Move Slow or Heavy Tasks to Asynchronous Processing

If a request triggers heavy work/PDF creation, email processing, third-party integration move it off the critical path.

Patterns:

• Message queues
• Event-driven processing
• Webhooks
• 202 Accepted + status polling endpoint

This keeps API responses fast and predictable.

10. Tune Timeouts, Retries, and Connection Reuse

Misconfigured retries and connection churn cause avoidable latency spikes.

Checklist:

• Set proper server/client timeouts
• Use jittered retries
• Enable connection pooling
• Keep database and network connections alive

This step prevents cascading failures.

11. Apply Rate Limiting and Throttling

Rate limiting is essential for protecting downstream services and preserving p95/p99 latency during spikes.

Implementation:

• Gateway-level rate limiting
• Quotas per client or token
• Adaptive throttling mechanisms

Throttling prevents system collapse and ensures fair resource distribution.

12. Measure Real Latency Percentiles and Trace the Hot Path

You cannot optimize what you cannot measure.

What to collect:

• p50 / p95 / p99 latency per endpoint
• Error rate
• Throughput
• Slow query logs
• Distributed tracing spans

This step ensures you focus on the true bottleneck, not an assumed one.

Copy‑Ready API Performance Checklist

For tickets, runbooks, and retrospectives:

• Cache repeat reads
• Add CDN/edge caching
• Enforce pagination and filtering
• Enable gzip/Brotli
• Reduce chatty request patterns
• Eliminate N+1 queries
• Add and verify database indexes
• Reduce serialization overhead
• Offload slow tasks asynchronously
• Tune timeouts, retries, and pooling
• Add rate limiting
• Measure latency percentiles and trace the hot path

FAQ

What’s the fastest item on the API performance checklist? Caching and payload reduction (pagination + field filtering) deliver the quickest latency improvements.

Do I need a CDN to improve API performance? If your API responses are cacheable and your users are geographically distributed, a CDN provides substantial latency reduction.

Should every API response be compressed? Compress all JSON or text-based responses. Compression is not useful for already-compressed binary formats like images or ZIP files.

Conclusion

A well‑structured API performance checklist is the most effective way to prevent latency issues, improve reliability, and ensure your backend scales smoothly. Whether your goal is reducing infrastructure costs or supporting higher throughput, applying the 12 steps in this checklist will significantly improve your API’s speed and stability.