Scale and performance

API Scaling and Performance

Modern APIs must cope with high load, peak requests and parallel calls. We design and implement solutions that provide smooth scaling and stable performance even in high-performance environments.

We use best practices: horizontal scaling, caching, queues, asynchronous calls, CDN and load balancing.

Approaches to scaling

Method	Description
Scale-out	Increase the number of API instances under load
Load balancing	Distribution of requests between servers (HAProxy, Nginx, AWS ELB)
Caching	Quick access to frequently used data (Redis, Memcached, CDN)
Asynchronous processing	Pending tasks through queues (RabbitMQ, Kafka, Celery)
Rate Limiting and Throttling	Manage Client Request Flow

Performance optimization

Analysis of bottlenecks by logs and metrics
Support for batch requests and minimization of roundtrip
Using HTTP/2, compressing, merging responses
Code profiling, refactoring, and latency reduction
Load testing (k6, JMeter)

Business results

Reliable operation even with a sharp increase in traffic
Ready to scale at any time
Reduce costs through efficient resource allocation
Predictable performance and fault tolerance
Fewer incidents and manual responses

Where especially important

Mobile and web applications with a large number of users
Financial and Transaction Services
Highly active gaming platforms
API-first products and SaaS solutions

The API should not be a narrow neck of the system. We create a scalable architecture that is resilient to spikes, easy to maintain, and growth-ready - without sacrificing performance or stability.