The current popularity of Redis is well deserved; it’s one of the best caching engines available and it addresses numerous use cases – including distributed locking, geospatial indexing, rate limiting, and more. Redis is so widely used today that many major cloud providers, including The Big 3 — offer it as one of their managed services. In this article, we’ll look at how to monitor Redis performance using Prometheus, the similarly popular open-source monitoring system.

With the current financial climate, cost reduction is top of mind for everyone. IT is one of the biggest cost centers in organizations, and understanding what drives those costs is critical. Many simply don’t understand the cost of their Kubernetes workloads, or even have observability into basic units of cost. This is where FinOps comes into play, and organizations are beginning to implement those best practice standards to understand their cost.

The MongoDB document-oriented database is one of the most popular database tools available today. Developed as an open-source project, MongoDB is highly scalable and can be set up in your environment in just a few simple steps. When running and managing databases, monitoring is a key requirement.

Over the past decade, Prometheus has become the most prominent open source monitoring tool in the world, allowing users to quickly and easily collect metrics on their systems and help identify issues in their cloud infrastructure and applications. Prometheus was originally developed by SoundCloud when the company felt their metrics and monitoring solutions weren’t meeting their needs.

Kubernetes has come a long way, but the current state of Kubernetes open source monitoring is in need of improvement. This is in part due to the issues related to an unnecessary volume of data related to that monitoring. For example, a 3-node Kubernetes cluster with Prometheus will ship around 40,000 active series by default. Do we really need all that data?