Operations | Monitoring | ITSM | DevOps | Cloud

Redgate’s annual “State of the Database Landscape” survey has been published. Like every other year, it paints a really interesting picture. Personally, I love looking through this in order to better understand where people are experiencing pain in the management of their data. If you know where people are experiencing pain, as a technical person, you know where to focus your own skill development.

This is a guest post from Stephanie Herr. If your team uses GitHub Actions to ship application code, you've probably wished your database changes could move through the same pipeline just as smoothly. Today, that's easier than ever. We've launched verified Redgate Flyway GitHub Actions on the GitHub Marketplace, giving you a simple, reliable way to integrate database deployments into your existing GitHub workflows.

Writing code is moving from the good old IDE into the realm of autonomous AI agents. One example of this is OpenAI, which has been developing internally with 0 lines of manually written code. You can read about their workflow in their engineering blog: Harness engineering: leveraging Codex in an agent-first world. For me, the main takeaway of OpenAI’s article is how AI has rewritten the constraints equation.

At VictoriaMetrics, we built vlagent as a high-performance log collector for VictoriaLogs. To validate its performance and correctness under a real production-like load, we developed a benchmark suite and ran it against 8 popular log collectors. This post covers the methodology, throughput results, resource usage, and delivery correctness. Collectors under the test: We’ve made all benchmark configurations and source code public, so you can reproduce and verify the results independently.

This is a guest post from Kellyn Gorman. Kellyn Gorman is a Database and AI Advocate and Engineer at Redgate She's the previous director of Data and AI at Silk, and the Oracle SME in Azure at Microsoft. With a robust background in cloud technology and a passion for promoting its merits and potential, I am thrilled to spearhead conversations and actions that help shape the future of this industry.

In case you don't know the back story, in order for me to play with radios and label it "work," I've created a PostgreSQL database running on AWS Aurora. The db is fed from API calls to aprs.fi through Lambda functions on AWS. Some of the DDL & code is mine. Some is from Claude. Neither of us paid much attention to indexing when we were putting things together.

This is a guest post from Phil James. Database teams are already juggling a lot. Monitoring the performance of complex, multi-platform estates takes expertise and focus — and that's before you factor in installing, maintaining, and updating the monitoring tooling itself. That's the tension we've been hearing from database teams for a while. The monitoring solution is supposed to reduce operational burden, yet the infrastructure that runs it adds more.

This is a guest post from udara.ratnakumara. In a recent webinar I hosted with my colleague Chris Hawkins, Inside a DBA’s Day: What Really Happens and How to Stay Ahead, we talked through the realities of a typical DBA day and the practical ways teams can stay ahead of issues rather than constantly reacting. For many DBAs, the day doesn’t start with coffee. It starts with an alert. A report is suddenly slow. An application query is timing out.

Whether you’re spinning up your first relational database or running a global e-commerce platform, Aiven for MySQL provides the performance and reliability you need. In the world of open-source databases, MySQL is the engine behind millions of applications, and at Aiven, we believe managing it shouldn't keep you up at night. Our platform is built to grow with you, from when you're just getting started all the way through to enterprise scale.