Blocked queries are one of the key issues faced by database analysts, engineers, and anyone managing database performance at scale. Blocking can be caused by inefficient query or database design as well as resource saturation, and can lead to increased latency, errors, and user frustration. Pinpointing root blockers—the underlying problematic queries that set off cascading locks on database resources—is key to troubleshooting and remediating database performance issues.

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.

Get a guided tour on advanced Oracle monitoring based on Microsoft System Center Operations Manager.

We recently got this great feedback from a dear user in our Discord: This is great and exactly what we want, a clear problem or improvement we could make to help make that users monitoring life a little easier. This is also where the beauty of open source comes in and being able to build on the shoulders of giants - adding such a feature turned out to be pretty easy by just extending our existing Pandas collector to support SQL queries leveraging its read_sql() capabilities.