One of the key benefits of using Kubernetes is that it’s very flexible and fault tolerant. However, that also means that it has quite a lot of complexity to deal with. A well-built operator abstracts that complexity away and helps manage updates and upgrades seamlessly. The Mattermost Kubernetes operator is basically like having a Mattermost Cloud Engineer running inside your Kubernetes cluster managing Mattermost for you.
Kubernetes is said to be the platform to build platforms on. In Freshworks’ case, this is very true. Once Kubernetes established itself as the de-facto container orchestration platform, we set out to create a platform around it with certain very specific capabilities in mind. Kubernetes is a complex beast and takes some effort to tame. Once that is done, there are tremendous advantages.
Lately we’ve been working on improving different parts of the Mattermost server, including our monitoring and observability capabilities. We’ve been using Prometheus and Grafana to monitor our cluster for a while now, and you can read this great post where my colleague Stylianos explains how we have them working for our multi-cluster environment.
Tanay is the Head of Developer Relations at n8n. He has published books on WebVR, virtual assistants on Raspberry Pi, and FirefoxOS. He has been listed in the about:credits of the Firefox web browser for his contributions to the different open source projects of the Mozilla Foundation. I’ve been involved in the DevOps world for a while and yet I finished reading The Phoenix Project only recently. The book piqued my interest in how teams execute their incident response playbooks.
On Monday, March 16, 2020, I had the privilege to (virtually) join Shota Gvinepadze and his students at the Free University of Tbilisi and speak about “Advanced Git @ Mattermost” for a portion of their class time. The following are my speaking notes from the session, slightly modified from the original slides for this format. Keep in mind that the command line examples are illustrative of my workflow, and not meant to be run in isolation.
Jira is a highly adaptable and feature-rich platform, which promises to help all types of teams manage their work. There are several features and toolkits that are purpose-built for software, business, DevOps and any other iteration of IT team to plan, track and release world-class software.
Over the last few years, static type checkers have become available for popular dynamic languages like PHP (Hack) and JavaScript (Flow and TypeScript), and have seen wide adoption. Two years ago, a provisional syntax for static type annotations was added to Python 3. However, static types in Python have yet to be widely adopted, because the tool for checking the type annotations, mypy, was not ready for production use… until now!
