Operations | Monitoring | ITSM | DevOps | Cloud

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.

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!

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.

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.

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.

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.

Machine learning (ML) pipelines are increasingly being treated like software; built, tested, deployed, and monitored using automated tooling. But while infrastructure as code and microservices have matured with security best practices, ML systems often lag behind. The truth is, your ML pipeline is part of your software supply chain and it is vulnerable.

GCP’s recent outage on June 12th was a reminder of just how interconnected modern architectures are. The 2 hour and 28 minute outage affected dozens of companies and spanned 80+ Google services and products. But what was really illuminating was just how far the outage spread due to hidden dependency risks. Many companies that don’t run on GCP were startled to find their services suddenly affected because they had dependencies or depended on vendors that did use GCP.