Chronicle Map VS Apache JMeter

I decided to start with an overview of what open-source options are currently available. When it comes to the implementation of the on-heap cache mechanism, the options are numerous – there is well known: guava, ehcache, caffeine and many other solutions. However, when I began researching cache mechanisms offering the possibility of storing data outside GC control, I found out that there are very few solutions left. Out of the popular ones, only Terracotta is supported. It seems that this is a very niche solution and we do not have many options to choose from. In terms of less-known projects, I came across Chronicle-Map, MapDB and OHC. I chose the last one because it was created as part of the Cassandra project, which I had some experience with and was curious about how this component worked:

Chronicle-Map: Chronicle Map is an in-memory, key-value store, designed for low-latency, and/or multi-process applications.

I've wrangled data sets in the ~600gb range using nothing but plain old Java and a few beefy boxes. This can all be kept in memory, but you have to go off-heap. You can use Chronicle Map and Chronicle Values to model this data and work with it off-heap in a way that's still very clean and object oriented. 128gb of RAM is cheap these days, whether you're in the cloud or not.

You could use many methods to run performance tests on your app, one of the most popular being Apache JMeter. Let's use the benchmark numbers to compare Hanami and Rails.

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?

Apache JMeter: This tool is an open-source application built on Java, designed specifically to test load functionality and performance. Developed by the Apache Software Foundation, JMeter is versatile, able to simulate loads across a wide range of services and protocols such as HTTP, HTTPS, JDBC, LDAP, and SOAP. With an extensible core that can be tailored with plugins, it provides the flexibility needed for different testing scenarios. Its intuitive GUI makes it easy for testers to design test plans and visualize the results in various ways.

I'll use Apache JMeter to do this experiment:

Thanks for the tip. Hows that compare to this tool? https://jmeter.apache.org/

Apache JMeter: Download and install JMeter from the official website (https://jmeter.apache.org/). Java Development Kit (JDK): JMeter requires Java, so ensure you have the latest JDK installed on your system. Postman: Install Postman from the official website (https://www.postman.com/downloads/).

The test scenario consists of querying for descriptions of different offers. During the test, I will collect data on memory and GC parameters using jConsole. I will run the test scenario using jMeter, which additionally will allow me to measure response times.

FYI some of our people internally use Jmeter. https://jmeter.apache.org/

It's not flashy so it probably wont get the standard "we are going to milk you for data" plan

Issue #5682Pull request #717 - Open Model Thread Group: avoid skipping rows from CSV Data Set Config

Performance and load testing are essential parts of GraphQL API testing. It ensures APIs can handle expected traffic volumes and respond within acceptable timeframes. You can use tools like Apache JMeter or Gatling to generate realistic loads and evaluate the API's performance under different scenarios. Techniques like batched queries and caching can help mitigate this issue.