Operations | Monitoring | ITSM | DevOps | Cloud

In January 2015, I wrote about the future of professional database administrators (DBAs) in a three-part series of articles for Database Trends & Applications magazine. Back then I predicted we would see strong growth in DBA salaries because of the acute and persistent shortage of talent, very little means of training new DBAs, and a median age of DBAs creeping closer to retirement age with each passing year.

VictoriaMetrics is an open-source time-series database (TSDB) written in Go, and I’ve had the pleasure of working on it for the past couple of years. TSDBs have stringent performance requirements, and building VictoriaMetrics has taught me a thing or two about optimization. In this blog post, I’ll share some of the performance tips I’ve learned during my time at VictoriaMetrics.

Starting around June this year, we upgraded our Grafana databases in Grafana Cloud from MySQL 5.7 to MySQL 8, due to MySQL 5.7 reaching end-of-life in October. This project involved tens of thousands of customer databases across dozens of MySQL database servers, multiple cloud providers, and many Kubernetes clusters.

Redis, as an in-memory data store, excels at providing high-speed data access and manipulation. However, without effective monitoring, the potential advantages of Redis can be compromised due to performance bottlenecks, scalability issues, and resource constraints. By closely scrutinizing key metrics, Redis monitoring allows you to proactively detect and address potential problems, ensuring the stability, reliability, and high-performance operation of your Redis environment.

We’re happy to announce a landmark 320% growth in 2023! VictoriaMetrics, our open source time series database and monitoring solution, already hit 268 million downloads this year (still counting), and received close to 13,000 stars on GitHub.