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Category: Containers

Running Kubernetes Clusters on Windows

Boemo Mmopelwa shows off Kubernetes Kind:

Kubernetes production clusters are typically run on cloud platforms. However, running and deploying Kubernetes applications on cloud platforms such as Google Kubernetes Engine is costly. These high costs can restrict the Kubernetes learning process for beginners. However, running Kubernetes clusters locally helps you efficiently test applications without disrupting the production environment or paying for cloud services. 

To make things easier, the Kubernetes team developed two tools,  Minikube and Kind, that allow Kubernetes users to run clusters locally without spending a dollar. This article will cover how to do it with Kind. Kind is a command-line tool used to run Kubernetes clusters locally on your computer using Docker containers. Kind works with Docker by loading Docker containers into Kind clusters. A Kubernetes cluster is a group of nodes used to run containerized applications.

Read the whole thing.

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Kubernetes for the R User

Roel M. Hogervorst provides an introduction to Kubernetes for R users:

Many R users come from an academic background, statistics and social sciences. That makes you an excellent problem solver with a deep knowledge of problems and a nuanced understanding of the world. You actually know what you are talking about!

But there is a different world, a world where the most important thing is showing an advertisement to as many people as possible. I’m joking, but the computer science world is where ideas like kubernetes were born. And like every other group specific words are used that can be hard to understand without context. That means that you have to use those words to find answers on your questions. This post will introduce some of those words and I have a list at the bottom. And now it is available to all of us, through a cloud provider in your area.

Read on for a light introduction to using Kubernetes.

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Monitoring Kubernetes in Production

Samir Behara provides some guidance:

Kubernetes is an open-source container orchestration system for automating the deployment and management of containerized applications. Kubernetes provides capabilities like service discovery, horizontal autoscaling, and load balancing, while ensuring that application configurations are declarative and that systems are self-healing.

In this article, I will explain how to monitor your Kubernetes cluster and implement automated health checks, and discuss the various monitoring tools available.

Read on for some thoughts. In addition to Samir’s links and ideas, I’d also throw in some tools like Rancher to make management a little easier.

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Running MSDTC on Linux Containers in Kubernetes

Amit Khandelwal reminds us that MSDTC exists:

It’s been a while since I’ve had the opportunity to write and share a blog post about SQL Server containers and Linux. Today, I’d like to show you how to set up and use MSDTC (Microsoft Distributed Transaction Coordinator) to execute distributed transactions for SQL Server containers running on a Kubernetes platform.

Please see the following documentation for more information on DTC and SQL Server on Linux. How to configure MSDTC on Linux – SQL Server | Microsoft Docs.

I kid (sort of) but it is good to see as much parity between the Windows and Linux versions of SQL Server as possible.

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Configuring a Debezium Connector for Event Hub Streaming

Niels Berglund continues a series:

This series came about as I in the post How to Use Kafka Client with Azure Event Hubs, somewhat foolishly said:

An interesting point here is that it is not only your Kafka applications that can publish to Event Hubs but any application that uses Kafka Client 1.0+, like Kafka Connect connectors!

I wrote the above without testing it myself, so when I was called out on it, I started researching (read “Googling”) to see if it was possible. The result of the “Googling” didn’t give a 100% answer, so I decided to try it out, and this series is the result.

In the first post, – as mentioned – we configured Kafka Connect to connect into Event Hubs. In this post, we look at configuring the Debezium connector.

Click through and enjoy the fruits of Berglund’s Folly—which, as far as it goes, I’d still rate Seward’s Folly higher but this one’s pretty good too.

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Using containerd as a Kubernetes Container Runtime

Anthony Nocentino has a guide for us:

In this post, I’m going to show you how to install containerd as the container runtime in a Kubernetes cluster. I will also cover setting the cgroup driver for containerd to systemd which is the preferred cgroup driver for Kubernetes. In Kubernetes version 1.20 Docker was deprecated and will be removed after 1.22. containerd is a CRI compatible container runtime and is one of the supported options you have as a container runtime in Kubernetes in this post Docker Kubernetes world. I do want to call out that you can use containers created with Docker in containerd. This post was previously published in February of 2021, this is an updated version with the latest installation and configuration steps.

Click through for instructions on installation and configuration.

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Deploying SQL Server to Azure Container Instance via ARM

Rajendra Gupta builds an ARM template:

The Azure Resource Manager (ARM) template is a JavaScript Object Notation (JSON) file for deploying Azure resources automatically. You can use a declarative syntax to specify the resources, their configurations. Usually, if you need to deploy Azure resources, it might be a tiring experience of navigating through different services, their configurations. With the ARM templates, you no longer need to click and navigate around the portal. For example, you can use configure the template for Azure VM or Azure SQL Database deployment.

Click through for a step-by-step walkthrough. I will say, though, that I tend heavily to revise ARM templates the Azure Portal creates. They tend to make everything parameters, to the point where you get inundated with context-free decisions.

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Clear out Those Old Container Images

Joy George Kunjikkur has a public service announcement for us:

When we use self-hosted Azure pipeline agents, we may encounter the below issue during the build process. This is not a hard issue to troubleshoot. The reason is there in the error message.

Error processing tar file(exit status 1): open /root/.local/share/NuGet/v3-cache/670c1461c29885f9aa22c281d8b7da90845b38e4$ps:_api.nuget.org_v3_index.json/nupkg_system.reflection.metadata.1.4.2.dat: no space left on device

This is known in the industry as a whoopsie-doops. Click through to see what you can do to resolve the problem.

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Reducing Image Sizes with Docker-Slim

Evan Seabrook puts Docker images on a diet:

If you’ve ever worked with Docker, there’s likely been at least one time when it started taking up significant storage space on your computer. For example, some of your images took a long time to download in a CI/CD pipeline. Some common approaches to this problem are to:

– Swap out the base image for something lighter

– Reduce the number of RUN statements in your Dockerfile

– Remove cached package manager artifacts as part of your Dockerfile

These steps, while helpful, can take up a significant amount of time and effort. Thankfully, there are open source tools that can automatically minify an existing Docker image. Enter docker-slim.

Looks like it can slim things down considerably. I haven’t tried this, but might give it a go and see how it works.

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