In this guide, we will discuss the different aspects of MongoDB performance monitoring. MongoDB provides a set of tools and command-line utilities to monitor MongoDB instances. But first, you need to know what metrics should be monitored. Once you understand the performance metrics, you can create workflows and processes to keep a check on your MongoDB cluster’s health and performance.

Wherever you read about observability, you are told that there are "3 pillars" of observability - Metrics, Traces and Logs. An image that is generally projected is something like this. But wait a minute, why are there only three pillars, and does it really matter to the end user? At the end of the day, users are just trying to solve their problems fast.

One of the easiest ways to see if the application running in our nodes is in an optimized state or not is by monitoring them. It is the last yet critical stage of any software development lifecycle. It opens up many possible improvements in your application, networking, IT automation, and other miscellaneous configurations. As we move towards microservice architecture, containerization and orchestration tools are rising. Containers are special processes that run in isolation from other processes.

It’s time for our monthly product updates. Closing GitHub issues, fixing bugs, shipping code, and sipping coffee, time flies by every month. Last month, we crossed a major milestone of 7000+ GitHub stargazers. We can not thank the developer community enough for supporting us in our mission to democratize observability.

Prometheus and InfluxDB are open-source projects created to make application performance monitoring a breeze. That is, of course, if you choose the option that covers your entire observability scope. This article compares and contrasts the extent to which Prometheus and InfluxDB remedy the need for real-time insights into your applications’ operations. We’ll highlight similarities and overlaps in both usability and practicality.