Every 100ms of API Latency Costs You 7% in Conversions

Akamai research proves that speed is revenue. We optimize API response times through strategic caching, database query optimization, connection pooling, efficient serialization, and smart pagination so your API meets its latency targets under production load.

7%

conversion rate reduction per 100ms of API latency, making API performance directly tied to business revenue

Akamai, 2017

API Performance Optimization

API response time optimization through caching strategies, database query tuning, connection pooling, efficient serialization, and load testing under realistic traffic conditions.

What's Included

Everything you get with our API Performance Optimization

Performance Audit and Bottleneck Analysis

Detailed analysis of every endpoint's response time with flame graphs, query plans, and latency breakdown identifying exactly where time is spent

Caching and Query Optimization

Redis or Memcached caching layer, database query optimization with proper indexing, N+1 query elimination, and connection pooling configuration

Load Testing and Monitoring

Realistic load tests that verify performance under projected traffic, with ongoing monitoring that alerts when response times degrade

Our API Performance Optimization Process

1

Performance Audit

We instrument every endpoint with timing data, analyze slow queries with EXPLAIN plans, profile serialization overhead, and identify the specific bottlenecks that contribute most to latency. We rank optimizations by impact.

2

Database and Query Optimization

We add missing indexes, restructure slow queries, eliminate N+1 patterns, configure connection pooling, and implement query result caching. We verify each optimization with before-and-after benchmarks.

3

Caching Layer Implementation

We design and implement the caching strategy: which endpoints to cache, cache key design, TTL policies, and invalidation triggers. We configure Redis or Memcached and integrate the caching layer into your API middleware.

4

Load Testing and Monitoring

We run load tests simulating realistic traffic patterns and verify that all endpoints meet their latency targets. We set up ongoing performance monitoring with alerting that catches degradation before users notice.

Key Benefits

Sub-100ms response times for cached endpoints

Redis caching for frequently accessed, infrequently changed data means many API calls resolve in under 10ms. Cache invalidation strategies ensure data freshness while delivering the response times that Akamai's research shows directly correlate with conversion rates.

Database queries that scale with data growth

Proper indexing, query optimization, and N+1 elimination ensure your API stays fast as your database grows from thousands to millions of rows. We analyze query execution plans and add the indexes that make the biggest impact.

Performance under realistic load

Load testing with realistic traffic patterns, not synthetic benchmarks, verifies that your API meets latency targets at projected traffic levels. We test with concurrent users, mixed read/write workloads, and burst traffic patterns.

Research & Evidence

Backed by industry research and proven results

The State of Online Retail Performance

A 100ms delay in load time can hurt conversion rates by 7%, and since API response time is a major component of total page load time, API optimization has direct revenue impact

Akamai (2017)

Page Load and Conversion

A site that loads in 1 second has a 3x higher conversion rate than one loading in 5 seconds, and API latency is often the biggest contributor to slow page loads in dynamic applications

Portent (2022)

Frequently Asked Questions

How much faster can our API get?

Typical improvements range from 3x to 10x depending on the starting point. APIs with no caching, missing indexes, and N+1 queries often see 10x improvements. Already-optimized APIs typically see 2 to 3x gains from advanced caching and query restructuring. We provide specific improvement projections after the initial audit.

Will caching cause data staleness issues?

Not with proper invalidation. We implement cache invalidation triggers on data mutations, TTL-based expiry for time-sensitive data, and cache versioning for deployments. The caching strategy is designed around your data freshness requirements. Critical endpoints can bypass cache entirely.

Do you fix the issues or just identify them?

Both. The audit identifies and prioritizes issues. The implementation phase fixes them. We deliver optimized code, not just a report. Every optimization is verified with before-and-after benchmarks showing the measurable improvement.

How long does API performance optimization take?

A performance audit with recommendations takes 1 to 2 weeks. Implementing the optimizations for a focused API takes 2 to 4 weeks. A comprehensive optimization of a large API with caching layer, database tuning, and load testing takes 4 to 8 weeks.

Turn API Latency Into Revenue Growth

Request an API performance audit. We will identify the specific bottlenecks costing you speed and conversions, with projected improvement metrics.