The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Hey Alternatives
Similar projects and alternatives to Hey
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Redis
Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
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ddosify
Effortless Kubernetes Monitoring and Performance Testing. Available on CLI, Self-Hosted, and Cloud
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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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keda
KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
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Gor
GoReplay is an open-source tool for capturing and replaying live HTTP traffic into a test environment in order to continuously test your system with real data. It can be used to increase confidence in code deployments, configuration changes and infrastructure changes.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Hey alternative or higher similarity.
Hey reviews and mentions
Posts with mentions or reviews of Hey.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-25.
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AWS SnapStart - Part 19 Measuring cold starts and deployment time with Java 17 using different Lambda memory settings
The results of the experiment below were based on reproducing approximately 100 cold starts for the duration of our experiment which ran for approximately 1 hour. For it (and all experiments from my previous articles) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman
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Data API for Amazon Aurora Serverless v2 with AWS SDK for Java - Part 5 Basic cold and warm starts measurements
The results of the experiment to retrieve the existing product from the database by its id see GetProductByIdViaAuroraServerlessV2DataApiHandler with Lambda function with 1024 MB memory setting were based on reproducing more than 100 cold and approximately 10.000 warm starts with experiment which ran for approximately 1 hour. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. We won't enable SnapStart on the Lambda function first.
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AWS SnapStart - Part 15 Measuring cold and warm starts with Java 21 using different synchronous HTTP clients
The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts with experiment which ran for approximately 1 hour. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. I ran all these experiments for all 3 scenarios using 2 different compilation options in template.yaml each:
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AWS SnapStart - Part 13 Measuring warm starts with Java 21 using different Lambda memory settings
In our experiment we'll re-use the application introduced in part 9 for this. There are basically 2 Lambda functions which both respond to the API Gateway requests and retrieve product by id received from the API Gateway from DynamoDB. One Lambda function GetProductByIdWithPureJava21Lambda can be used with and without SnapStart and the second one GetProductByIdWithPureJava21LambdaAndPriming uses SnapStart and DynamoDB request invocation priming. We'll measure cold and warm starts using the following memory settings in MBs : 256, 512, 768, 1024, 1536 and 2048. I also put the cold starts measured in the part 12 into the tables to see both cold and warm starts in one place. The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts for the duration of our experiment which ran for approximately 1 hour. Here is the code for the sample application. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. Abbreviation c is for the cold start and w is for the warm start.
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Diagnósticos usando dotnet-monitor + prometheus + grafana
Por último, podemos executar os testes de carga usando hey.
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Amazon DevOps Guru for the Serverless applications - Part 2 Setting up the Sample Application for the Anomaly Detection
For running our experiments to provoke anomalies we'll use the stress test tool. You can use the tool of your choice (like Gatling, JMeter, Fiddler or Artillery), I personally prefer to use the tool hey as it is easy to use and similar to curl. On Linux this tool can be installed by executing
- Threadpool no aspnet e problemas de performance
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The Uncreative Software Engineer's Compendium to Testing
Hey: is a fast HTTP load testing tool used to test web applications and APIs. It provides a CLI (command-line interface) and supports concurrent requests.
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The TCP receiver only ack the minimum bytes of MSS one by one
The client and server nodes are CentOS7.9/X86_64. If the HTTP POST requests were sent directly to the server with hey -c 1, there are about 0.2% of cases that may timeout. If the HTTP POST requests were sent through an NGINX proxy on the client node, there are about 20% of cases will timeout. I've confirmed that only one backend node has this problem. All other nodes are 100% succeeded even with higher throughput.
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Benchmarking SQLite Performance in Go. Using Go's awesome built-in simple benchmarking tools to investigate SQLite database performance in a couple of different benchmarks, plus a comparison to Postgres.
64 concurrent requests isn't a lot. Modern web apps can typically handle much more than that (depending on what the request does, of course). Try it yourself with a load tester like https://github.com/rakyll/hey against a Go HTTP server, for example the one I've built in https://www.golang.dk/articles/go-and-sqlite-in-the-cloud
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A note from our sponsor - WorkOS
workos.com | 27 Apr 2024
Stats
Basic Hey repo stats
38
17,249
0.0
4 days ago
rakyll/hey is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of Hey is Go.
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