Performance Optimization
I specialize in identifying and eliminating bottlenecks that slow down your applications under real-world conditions. My optimization approach covers the full stack - from database queries and application code to network calls and infrastructure configuration. Using benchmarking, profiling, and observability tools, I transform sluggish systems into high-performance engines capable of handling 10X-100X more traffic with the same hardware. Whether you're battling slow API responses, database contention, or memory leaks, I implement proven optimization strategies that deliver measurable speed improvements.
Development Services
Database Performance Tuning
Analyze and optimize slow queries with EXPLAIN plans, proper indexing strategies, and query restructuring. Implement database connection pooling and optimize JOIN operations for complex queries.
Application Code Profiling
Use py-spy, perf, or YourKit to identify CPU/memory hotspots in your code. Refactor inefficient algorithms, reduce unnecessary object creation, and optimize critical code paths.
Caching Strategy Implementation
Design multi-layer caching with Redis/Memcached for application data and CDN caching for static assets. Implement cache invalidation policies that balance freshness with performance.
Concurrency Optimization
Tune thread pools, worker processes, and async I/O configurations to maximize throughput without overwhelming system resources. Implement non-blocking architectures where appropriate.
Network Latency Reduction
Optimize TCP stack settings, enable HTTP/2, implement connection pooling, and reduce DNS lookups. For distributed systems, optimize inter-service communication patterns.
Memory Management
Analyze and fix memory leaks with heap dumps. Optimize garbage collection settings and reduce memory fragmentation. Implement object pooling for high-creation-rate objects.
Benefits
Faster Response Times
Deliver API responses in single-digit milliseconds for critical endpoints through systematic optimization of the entire request pipeline.
Higher Throughput
Handle more concurrent users with the same infrastructure by eliminating bottlenecks and improving resource utilization.
Reduced Infrastructure Costs
Achieve the same performance with fewer servers through efficient resource usage, saving on cloud/hosting expenses.
Improved Stability
Prevent cascading failures during traffic spikes by optimizing system resource usage and implementing proper throttling.
Development Process
Performance Benchmarking
Establish baseline metrics like requests/sec, latency, error rates under realistic load using tools like k6 or JMeter. Identify key bottlenecks.
Targeted Profiling
Use flame graphs, tracing, and monitoring tools to pinpoint exact causes of slowness at each layer like DB, app, network.
Iterative Optimization
Implement and test improvements one change at a time, measuring impact after each adjustment to validate effectiveness.
Monitoring & Maintenance
Set up performance dashboards with alerts for regression. Document optimization decisions for future reference.