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Stanislav Anisimov
API Scaling and Performance
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Modern APIs must cope with high load, peak requests and parallel calls. We design and implement solutions that enable smooth scaling and consistent performance even in high-volume environments.

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


Approaches to scaling

MethodDescription
Horizontal scalingIncreasing the number of API instances under load
Load balancingDistribution of requests between servers (HAProxy, Nginx, AWS ELB)
CachingQuick access to frequently used data (Redis, Memcached, CDN)
Asynchronous processingPending tasks through queues (RabbitMQ, Kafka, Celery)
Rate Limiting и ThrottlingControl the flow of requests from clients

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.

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