Windows-Containers VS kubernetes

You're trading one convenience for a world of hurt if you use Kubernetes with Windows. Just take a casual glance at the "Windows containers" issues list on GitHub: https://github.com/microsoft/Windows-Containers/issues

Some of the very recently closed issues were jaw-dropping, such as totally broken networking in common scenarios.

DNS resolution is very different in Windows compared to Linux, making much of the "neatness" of Kubernetes pod-to-pod communication not work.

There is no maximum memory limit in Windows kernel "job objects" (equivalent to cgroups), so one memory leak in one pod can kill an entire node or cluster. This is very hard to solve, and I've seen it take out Service Fabric clusters also.

Etc, etc...

There is also a GitHub unresolved closed issue with similar issue: https://github.com/microsoft/Windows-Containers/issues/173

We keep checking for version compatibility with testing internally before releasing it externally. However, if something still breaks, you can expect a communication from Microsoft - most likely here: https://github.com/microsoft/Windows-Containers/issues

If you think this is a bug and want the Microsoft team to investigate, please file a an issue here: https://github.com/microsoft/Windows-Containers/issues (Please remember to post the resolution here so other Reddit users can also see that)

I’m joking of course. I’m not really sure about what a faded keyboard says about its owner. What I do know for sure is how important kubectl is to anybody who wants to be a proficient Kubernetes administrator.

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

Securing access to your Kubernetes clusters is crucial as inadequate security measures can lead to unauthorized access and potential data breaches. However, navigating the complexities of Kubernetes access security, especially when setting up strong authentication, authorization, and network policies, can be challenging.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.