Operations | Monitoring | ITSM | DevOps | Cloud

If writing SQL code is part of your daily work, you won’t be surprised by things like context-aware code completion, as-you-type syntax validation, and debugging. All of them are designed to enhance and speed up your SQL coding. But what if we said that you could completely reshape your experience with an AI-powered assistant? What if you could have your error-free queries generated, analyzed, and optimized in just a couple of moments?

Toward the end of Q1 2022, survey findings reported that Microsoft’s Azure cloud computing services had, for the first time, eclipsed Amazon Web Services (AWS) in some enterprise categories. According to the respondents, more enterprises preferred Azure because it integrates well with the many Microsoft products they already use. A second reason is that Azure is suitable for running on-premises and at the edge. Some organizations also use Microsoft Azure to avoid vendor lock-in to AWS.

For many businesses, 2020 marked the dawn of the cloud-first era, with organisations around the world embracing public cloud. And it made sense at the time; promise of reduced infrastructure costs, flexibility and scalability meant that leveraging cloud services was a no-brainer. But with any new technology, the shifting tides that come along with its proliferation also informs the cyclical nature of its adoption.

Insecure system configuration is a textbook example of how neglected settings can create an entry point for attackers targeting your CI/CD pipelines. It’s rarely the cutting-edge zero-day that causes a breach. More often, it’s the unpatched service, the overly permissive role, or the default password that was never changed. While this risk overlaps with CI/CD credential hygiene (covered in Part 6 of our OWASP CI/CD series), the focus here is much broader.

We are thrilled to announce the next major milestone in our platform vision: Qovery observability! Qovery Observability is our new product, ready to give you the fastest way to gain a crystal-clear, unified understanding of your application and infrastructure. Fully managed, zero lock-in, you keep the data. Devs love it, no DevOps needed. Coming soon!

Several years ago, while surfing the web, the author of these lines discovered something unexpected… an organization with focus on optical networks he had not heard of before.

Kubernetes excels at managing complex, containerized systems, and one of its most impactful patterns is the sidecar. Sidecar containers extend applications by running supplementary processes in tandem. This modular architecture enables enhanced observability, networking, or security layers — all without changing the core application code. Continuous Integration and Continuous Deployment (CI/CD) practices are key to reliably shipping these configurations.

Code reviews are a crucial step in maintaining code quality, but many developers find them tedious and inconsistent. What if you could get helpful feedback automatically, as soon as a pull request is opened? In this tutorial, you’ll learn how to set up and integrate an AI-powered code review agent into your Go project. The agent uses the OpenAI API to post contextual suggestions and praise directly on pull requests.