What is "Extreme HTTP Performance Tuning" about?

The article "Extreme HTTP Performance Tuning" details the process of optimizing an HTTP server to handle 1.2 million JSON API requests per second on a 4 vCPU AWS EC2 instance. It outlines a systematic approach through nine optimization categories, ranging from application code to Linux kernel parameters and hardware considerations.

Who is this performance tuning guide for?

This guide is intended for developers, DevOps engineers, and system administrators interested in deep performance tuning for high-throughput network applications running on Linux, particularly within AWS EC2 environments. It targets those already handling significant traffic, generally above 50,000 requests per second.

How does this performance tuning approach differ from typical web server optimization guides?

This approach differs by focusing on extreme, low-level optimizations for a custom C-based API server leveraging Linux primitives like epoll, rather than general web server configurations. It systematically explores deep kernel tunings, speculative execution mitigations, and interrupt optimizations to achieve a 5x performance gain.

When should one consider applying the performance tuning techniques described in this blog post?

These performance tuning techniques should be considered when an application demands extreme low-latency and high-throughput, and conventional optimizations have been exhausted. The article suggests that many specific tunings are most impactful for systems already processing more than 50,000 requests per second.

What is one specific technical optimization discussed in the article?

One significant technical optimization discussed is the disabling of iptables and netfilter, which provided a 22% increase in throughput by eliminating the overhead of packet filtering. Another crucial step was achieving "perfect locality" by explicitly pinning server processes and client threads to specific vCPUs.

talawah.io · 11 JUL '21

Extreme HTTP Performance Tuning: 1.2M API req/s on a 4 vCPU EC2 Instance

Item: Extreme HTTP Performance Tuning: 1.2M API req/s on a 4 vCPU EC2 Instance
Rating: 5
Author: Simon Frey

This is a great blog post on how to optimize network code on Linux, detailing the steps taken to achieve 1.2M API requests/second on a 4 vCPU EC2 instance through various system and application-level tunings. It's a solid illustration of compounding gains in optimization.

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Questions & Answers

What is "Extreme HTTP Performance Tuning" about?: The article "Extreme HTTP Performance Tuning" details the process of optimizing an HTTP server to handle 1.2 million JSON API requests per second on a 4 vCPU AWS EC2 instance. It outlines a systematic approach through nine optimization categories, ranging from application code to Linux kernel parameters and hardware considerations.
Who is this performance tuning guide for?: This guide is intended for developers, DevOps engineers, and system administrators interested in deep performance tuning for high-throughput network applications running on Linux, particularly within AWS EC2 environments. It targets those already handling significant traffic, generally above 50,000 requests per second.
How does this performance tuning approach differ from typical web server optimization guides?: This approach differs by focusing on extreme, low-level optimizations for a custom C-based API server leveraging Linux primitives like epoll, rather than general web server configurations. It systematically explores deep kernel tunings, speculative execution mitigations, and interrupt optimizations to achieve a 5x performance gain.
When should one consider applying the performance tuning techniques described in this blog post?: These performance tuning techniques should be considered when an application demands extreme low-latency and high-throughput, and conventional optimizations have been exhausted. The article suggests that many specific tunings are most impactful for systems already processing more than 50,000 requests per second.
What is one specific technical optimization discussed in the article?: One significant technical optimization discussed is the disabling of iptables and netfilter, which provided a 22% increase in throughput by eliminating the overhead of packet filtering. Another crucial step was achieving "perfect locality" by explicitly pinning server processes and client threads to specific vCPUs.