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Load Testing With Prometheus and Grafana

In order to measure the amount of memory and cpu time consumed by every service I created this project using the following technologies:

  • Prometheus: for querying metrics info from each service by exposing a "/metrics" API that's called by prometheus server to pull cpu and memory data.
  • Grafana: for displaying the data gathered by prometheus in a clear dashboard
  • Apache Bench: for executing the load testing scripts locally

Test Results

  • Fetching 3000 requests wih 20 concurrent connections in node

    as shown here node is not the best option for this kind of operation because it is a single threaded language and it's not that fast in terms of execution time and for the cpu and memory usage it is not that good either.

  • Fetching 3000 requests wih 20 concurrent connections in Go

    zoomed-in for better visibility

    go here runs smoothly in all aspects, it's fast, it's memory efficient and it's cpu efficient.

  • Fetching 3000 requests wih 20 concurrent connections in Java

    java is good in terms of execution time but it's not that good in terms of memory consumption and cpu usage compared to go

  • Fetching 5000 requests wih 20 concurrent connections all services

When I ran this test, Node and Go executed as expected. However, Node's response time and memory footprint increased, while Go's remained the same. Java, on the other hand, experienced a huge spike in memory usage even after the test was completed, due to its garbage collector.

Both Java and Go utilize garbage collection to manage memory. However, Go's garbage collector is designed to be more efficient and have less impact on CPU and memory usage compared to Java's. Go's concurrent garbage collector reduces the impact of garbage collection on resources and allows the application to run smoothly without pausing.

The Java garbage collector identifies objects that are no longer being used by the program and frees the memory associated with those objects. However, to do this, the garbage collector needs to temporarily allocate additional memory to perform its analysis and bookkeeping.