Jedis VS artillery

Finding out what's causing that was not that simple as Jedis does not write a lot of log information when the log level is set to debug. From what we could tell from the Jedis source code it seems that when the Jedis client connects to the configuration endpoint it fetches all known hosts. It stores that in a local cache and figures out the primary node from the set of nodes. Once the primary node is known it will execute operations against the primary node. It does so by connecting to the Amazon-generated domain name/entry and when that entry is down / unreachable it seems it does not use the configuration endpoint to rediscover the nodes or fetch the new cluster topology. We initially thought this had to do with the DNS caching of the JVM, so we also tried to disable caching, but we did not see any effect after that change.

jedis is used to interact with Redis.

Como um bônus, deixo aqui uma classe SessionManager pra ajudar na implementação em Java usando Jedis e o gerador de token do Tomcat, que já é normalmente incluído no Spring Boot:

Usually, I would let organic users be my load test. However, I am working on a project that has an anticipated load on a new-to-my-team stack, so I'm looking into ways to load test.

I've seen tools like k6 (https://k6.io/), Artillery (https://www.artillery.io), and JMeter (https://jmeter.apache.org/).

I've been using Artillery, but it's hard to visualize the results.

What do you use?

This week was Tracetest’s first-ever Launch Week. We’ve been working on a major integration with Artillery for the last month and our team is beyond excited to share it with you all!

I found a tool for load testing called Artillery. Following this guide I installed Artillery and began research for the test configuration.

This is a great blog post! just taking the opportunity here to comment on this:

> Finally for full scale high fidelity load tests there are relatively few tools out there for browser based load testing.

It exists as of a few months ago and it's fully open source: https://github.com/artilleryio/artillery (I'm the lead dev). You write a Playwright script, then run it in your own AWS account on serverless Fargate and scale it out horizontally as you see fit. Artillery takes care of spinning up and down all of the infra. It will also automatically grab and report Core Web Vitals for you from all those browser sessions, and we just released support for tracing so you can dig into the details of each session if you want to (OpenTelemetry based so works with most vendors- Datadago APM, New Relic etc)

So not to stress test Momento or AWS' Lambda, I wanted to build a small but stable 10-minute workload that hits the Momento Topic API and then let Momento trigger the FunctionURL to run the Lambda code. I wrote a small Artillery config file that ramps up to 20 users and then sustains that for the duration. Again, the script is simple to trigger the work.

Tool Spotlight: Featuring insights on how Artillery and Gitpod can enhance and streamline the benchmarking process.

curl is fantastic. There's also HTTPStat which provides a waterfall visualization on top of curl timings: https://github.com/reorx/httpstat

There's also Skytrace (made by yours truly), which provides timing info as a waterfall visualization inspired by HTTPStat + lots more (syntax highlighting for responses, built-in JMESPath support, command-line assertions and checks etc) - https://github.com/artilleryio/artillery/tree/main/packages/...

https://www.artillery.io/

I know it's an annoying answer, but it depends on your application. The only true way to know is to test it using a load tester like artillery. Measuring performance is a fundamental part of any optimisation (otherwise how do you know?), so it's a great idea to be using tools like this anyway.

For this test I have used artillery.io with the following configuration: