By continuously running a well-built general-purpose database performance monitoring facility, organizations can gain constant visibility into the availability and responsiveness of their databases and database management systems (DBMSs). When such a tool is equipped with analytics to compare historical metrics against current values, administrators can immediately understand how current values and behaviors stack up against prior averages and typical baselines.

As part of our research for the 2021 State of Database DevOps report, we asked 3,000+ recipients what they consider to be the greatest challenge when integrating database changes into a DevOps process. According to the respondents, these are the most important challenges facing database professionals when introducing DevOps practices to database development.

Mikhail Volkov is building observability and monitoring solutions at Volkov Labs and leading Redis plugins for Grafana. Since the Redis project first got underway in 2009, the open source in-memory data store has been embraced by thousands of companies of all types and sizes. According to Stackshare.io, well over 5,000 companies use Redis, including Uber, Airbnb, Twitter, Instagram, and Slack.

For good or for ill, technology is constantly shifting and with it, the roles of those who manage that technology also shift. This is no different for a DBA than it is for a developer, an admin, or analyst. As new technology, like the adoption of the cloud, changes the role, people start to question whether or not there’s even a need for a DBA. The shortest possible answer to that question, in my opinion, is “Yes”.

One of the most common questions database professionals are asked by their systems and virtual machine (VM) administrators is “Why does the database server need so much memory?” You’ll get a more detailed answer to that question later in this post, but it’s important to understand a database engine is almost like a server within a server.

Although writing better queries and building the right indexes are important parts of improving database performance, building clear database documentation can also contribute to this goal by helping you understand your database architecture. Painting a clear picture of the structure of your database gives you insight into your data flows and helps you identify redundant data and clarify business processes.

PostgreSQL monitoring with Prometheus is an easy thing to do thanks to the PostgreSQL Exporter. PostgreSQL is an open-source relational database with a powerful community behind it. It’s very popular due to its strong stability and powerful data types. In this article, you’ll learn the top 10 metrics in PostgreSQL monitoring, with alert examples, both for PostgreSQL instances in Kubernetes and AWS RDS PostgreSQL instances.

Given the overwhelming importance of data to organizations, anything they can do to speed up troubleshooting problems in the databases they use is of great value. If a company can speed up or avoid troubleshooting, it frees up time they can invest in doing and building more with their data. Careful attention to database query construction and execution also pays similar dividends, as improved database performance helps organizations get more done faster.

I work as Director at ThoughtWorks in the database and DevOps space. I’ve been here for 20+ years and I vaguely remember my first project at ThoughtWorks in 1999 when we had just started using Agile software development practices. The basic challenge we faced was how to move database changes at the same pace as application code and keep them in sync so that deployments would work. At the time, we had to invent all the tools, processes, and techniques that we needed.