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Autocannon Alternatives
Similar projects and alternatives to autocannon
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zig
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SurveyJS
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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aws-lambda-power-tuning
AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced.
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mitosis
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llnode
An lldb plugin for Node.js and V8, which enables inspection of JavaScript states for insights into Node.js processes and their core dumps.
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aws-lambda-builders
Python library to compile, build & package AWS Lambda functions for several runtimes & framework
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WorkOS
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autocannon reviews and mentions
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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, letβs 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/):
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A note from our sponsor - InfluxDB
www.influxdata.com | 23 Apr 2024
Stats
mcollina/autocannon is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of autocannon is JavaScript.
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