I’m a Data Architect and I’ve been working with data and databases for years at companies like LA Fitness, Dell and now Kingston Technology in Fountain Valley, California. Over all of that time, I’ve used SQL Monitor. I loved it from the beginning and the latest updates to the global overview dashboard and other features have stepped it up another few notches.

Have you ever deployed a new application that ran fine at first, then slowed to crawl as more and more data was added? Or tried to run a report that took minutes or even hours to come back? Database performance is a frequent bottleneck for many applications, and in this post you’ll learn about a critical aspect of database performance—indexes.

Azure Functions are great for running bits of processing on a trigger without having to worry about hosting. Recently, I needed to debug an Azure Function—I needed to hunt down a particularly evasive bug that wasn’t showing up in the unit and integration tests. As it turns out, debugging an Azure Function isn’t as trivial as simply running the debugger in Visual Studio. Instead, it requires some setup to replicate the environment and configuration typically available in Azure.

Last year was a year of unprecedented challenges for everyone in every part of the world and every industry, and it was also a year of big changes in the IT sector. The pandemic underscored the role of the IT department as an enabler and a critical part of the transition to remote working. While digitalization was well underway before 2020, no one could have predicted the acceleration the pandemic brought on.

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.