autocannon
algorithms
autocannon | algorithms | |
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14 | 3 | |
7,586 | 2,653 | |
- | - | |
6.5 | 5.6 | |
3 days ago | 4 months ago | |
JavaScript | Ruby | |
MIT License | MIT License |
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autocannon
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Optimize Your Node.js API with Clustering, Load Testing, and Advanced Caching
Autocannon GitHub Repository
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Taming the dragon: using llnode to debug your Node.js application
To make things interesting, let’s send some requests to this server with autocannon:
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Benchmarking Deno vs Node with GraphQL
Using autocannon, I did the following script to simulate 500 concurrent connections over 30 seconds:
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A first look at Bun: is it really 3x faster than Node.js and Deno?
We then used autocannon to measure the throughput (requests per second) of each runtime server-rendering our React app.
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Can we use Pydantic models (Basemodel) directly inside model.predict using FastAPI, if not why?
You could also use tools like autocannon to see how many requests/second you can achieve with various methods. : https://github.com/mcollina/autocannon
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How to Use Source Maps in TypeScript Lambda Functions (with Benchmarks)
I used autocannon to test the function at 100 concurrent executions for 30 seconds. I also used Lambda Power Tuning to find the ideal memory configuration, which proved to be 512MB. All the results are available.
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Find bottlenecks in Node.js apps with Clinic Flame
Moreover, if your blocking issue is appearing only on heavy load, you can easily test it using the very nice --autocannon CLI param (see it with clinic flame --help) where you can specificy autocannon options to generate some HTTP load on your web service.
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Created a URL shortener in Node (Fastify) and in Go (net/http). Why isn't Go faster?
I packaged them both with Docker and deployed them to an EC2 instance, each behind an Nginx reverse proxy I setup in docker-compose. I'm currently testing performance using autocannon from my laptop like this: `autocannon -a 5000 -w 10 URL` (5000 requests with 10 workers), and both apps complete in around 40 seconds. The EC2 instance is in Oregon and I'm testing from Toronto.
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DB query performance options.
You can test it by yourself using console.time(). You can use autocannon to stress-test your http server to see what is really the best options.
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Experiments in concurrency 3: Event loops
When I test this with autocannon making three simultaneous requests (autocannon --connections 3 --amount 3 --timeout 10000 --no-progress http://localhost:5678/):
algorithms
- Ruby Heaps Inspired by Python
- Using Ruby for technical interviews at FAANG companies?
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Experiments in concurrency 3: Event loops
Rather than implementing mine, I'll be using the priority queue from this library. We'll replace our @timers array with a priority queue instead. Here's how our queue will work:
What are some alternatives?
node-clinic - Clinic.js diagnoses your Node.js performance issues
jaro_winkler - Ruby & C implementation of Jaro-Winkler distance algorithm which supports UTF-8 string.
octane - Supercharge your Laravel application's performance.
clipboard-rails - clipboard.js javascript library integration for your Rails 4 and Rails 5 applications
serverless-graphql - Serverless GraphQL Examples for AWS AppSync and Apollo
smarter_csv - Ruby Gem for smarter importing of CSV Files as Array(s) of Hashes, with optional features for processing large files in parallel, embedded comments, unusual field- and record-separators, flexible mapping of CSV-headers to Hash-keys
aws-sam-cli - CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM
Time Math - Small library for operations with time steps (like "next day", "floor to hour" and so on)
lambda-sourcemaps
Piperator - Composable pipelines for Enumerators.
Swoole - 🚀 Coroutine-based concurrency library for PHP
Related - Pure Ruby relational algebra