Operations | Monitoring | ITSM | DevOps | Cloud

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.

Welcome back to our five-part series in which we discuss a top habit for DBAs to increase business functionality. In part one of this series, we discussed the importance of a capability maturity model (CMM) and more specifically Level 1 of the information management maturity model (IMMM) and how the framework can provide a step-by-step process for DBAs to follow while also allowing businesses to gain skills along the way.

Data provides an essential basis for reports and analytics, with the databases storing the data now driving and informing most custom and line-of-business applications. Thus, anything organizations can do to speed up troubleshooting for database problems is pure gold. In fact, time saved on troubleshooting turns into time organizations can invest in being more productive and profitable.

Indexes play a critical role in SQL Server query performance. SQL Sentry Fragmentation Manager helps you make intelligent decisions about index management based on the table and index information collected. In this blog post, I’m going to discuss index fragmentation, several ways you can identify it, and why a more granular approach to index maintenance can save time and allow you to focus on other tasks during maintenance windows.