The latest News and Information on DevOps, CI/CD, Automation and related technologies.
I’m excited to announce the release of Puppet Enterprise 2019.8.3. This release builds on a number of important product enhancements based on customer feedback and delivers on the second phase of our highly requested Value Dashboard.
We’ve had an exciting year here at Puppet, and although it’s not the year we could have expected, I’m encouraged and inspired every day by the resilience of our team, our commitment to each other, and our drive to help customers navigate through so much uncertainty and change.
Netdata is zero-configuration monitoring. It’s a principle that we’ve stood behind since the project’s beginning, when it was only our CEO Costa trying to solve a “painful, real-world problem,” and it’s one we stand by today. Our insistence on zero-configuration guides every product decision we make, every grooming process, and every React component our frontend teams design.
On our journey to democratize monitoring, we are proud to have open source at the core of both our products and our company values. What started as a project out of frustration for lack of existing alternatives (see anger-driven development), quickly became one of the most starred open-source projects on all of GitHub.
Modern applications are changing, and traditional testing practices are no longer up to the task. Learn more about the changing landscape of QA and how Chaos Engineering provides the necessary framework for testing modern applications. Chaos and Reliability Engineering techniques are quickly gaining traction as essential disciplines to building reliable applications. Many organizations have embraced Chaos Engineering over the last few years.
We created the Fleet Project to provide centralized GitOps-style management of a large number of Kubernetes clusters. A key design goal of Fleet is to be able to manage 1 million geographically distributed clusters. When we architected Fleet, we wanted to use a standard Kubernetes controller architecture. This meant in order to scale, we needed to prove we could scale Kubernetes much farther than we ever had.