Why Kargo?
Making Kubernetes operationally strong is a widely held priority and I track many deployment efforts around the project. The incubated Kargo project is of particular interest for me because it uses the popular Ansible toolset to build robust, upgradable clusters on both cloud and physical targets. I believe using tools familiar to operators grows our community.
We recently announced that the entire Windows codebase is moving to a single Git repo that is hosted on Visual Studio Team Services. This migration has presented us with some very interesting scale challenges to solve, ranging from issues inherent in the Git protocol and object storage, to the performance of the git command line, to workflow challenges for a team of that size working in one repo. In this series of articles, we’ll discuss each of these scale challenges in depth, and how we have solved them to enable a team of this size to work successfully in Git.
It’s been 3 months since I first wrote about our efforts to scale Git to extremely large projects and teams with an effort we called “Git Virtual File System”. As a reminder, GVFS, together with a set of enhancements to Git, enables Git to scale to VERY large repos by virtualizing both the .git folder and the working directory. Rather than download the entire repo and checkout all the files, it dynamically downloads only the portions you need based on what you use.
This is the last post in a 4-part series about Kubernetes monitoring. Part 1 discusses how Kubernetes changes your monitoring strategies, Part 2 explores Kubernetes metrics and events you should monitor, Part 3 covers the different ways to collect that data, and this post details how to monitor Kubernetes performance with Datadog.
This post is Part 3 of a 4-part series about Kubernetes monitoring. Part 1 discusses how Kubernetes changes your monitoring strategies, Part 2 explores Kubernetes metrics and events you should monitor, this post covers the different ways to collect that data, and Part 4 details how to monitor Kubernetes performance with Datadog.
This post is Part 2 of a 4-part series about Kubernetes monitoring. Part 1 discusses how Kubernetes changes your monitoring strategies, this post breaks down the key metrics to monitor, Part 3 covers the different ways to collect that data, and Part 4 details how to monitor Kubernetes performance with Datadog.
This post is Part 1 of a 4-part series about Kubernetes monitoring. Part 2 explores Kubernetes metrics and events you should monitor, Part 3 covers the different ways to collect that data, and Part 4 details how to monitor Kubernetes performance with Datadog.
Simple yet Powerful Turnkey Solution to Build Clouds and Manage Data Center Virtualization
Founded by the legendary Keith Code in 1980, the California Superbike School offers a step-by-step method of technique oriented rider training in the art of cornering motorcycles. The four California Superbike School training levels are completed in order with each of the first three levels presenting precise technical riding skills, taught the old fashioned way - one step at a time. Each skill builds upon the last to create a complete package of control and confidence.
About a week ago many users may have noticed instability on our hosted ZeroTier Central. Network controllers would flicker on and off, and eventually the whole service needed to be restarted across our cluster. 500 errors and timeouts were a thing.
Siege is an http load testing and benchmarking utility. It was designed to let web developers measure their code under duress, to see how it will stand up to load on the internet. Siege supports basic authentication, cookies, HTTP, HTTPS and FTP protocols. It lets its user hit a server with a configurable number of simulated clients. Those clients place the server “under siege.”