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Category: Containers

Persisting SQL Server Databases on Kubernetes

Published 2019-05-09 by Kevin Feasel

Anthony Nocentino walks us through persistent volumes and Kubernetes:

One of the key principals of Kubernetes is the ephemerality of Pods. No Pod is every redeployed, a completely new Pod is created. If a Pod dies, for whatever reason, a new Pod is created in its place there is no continuity in the state of that Pod. The newly created Pod will go back to the initial state of the container image defined in the Pod’s spec. This is very valuable for stateless workloads, not so much for stateful workloads like SQL Server.

This means that for a stateful workload like SQL Server we need to store both configuration and data externally from the Pod to maintain state through the recreation of a Pod. Kubernetes give us constructs two constructs to do that, environment variables and Persistent Volumes. 

Read on for a good bit of background and a few scripts to help you get started.

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Deploying SQL Server Containers to Azure with Terraform

Published 2019-05-08 by Kevin Feasel

Andrew Pruski has a post covering deployment of SQL Server containers to Azure using Terraform:

What this is going to do is create an Azure Container Instance Group with one container it in, running SQL Server 2019 CTP 2.5. It’ll be publicly exposed to the internet on port 1433 (I’ll cover fixing that in a future post) so we’ll get a public IP that we can use to connect to.

Notice that the location and resource_group_name are set using variables that retrieve the values of the resource group are going to create.

Cool! We are ready to go!

Fun stuff, and Andrew promises more.

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Using Powershell Core in Containers

Published 2019-05-06 by Kevin Feasel

Anthony Nocentino shows us how we can run Powershell Core in containers:

Now, with that last technique, we’ve encapsulated the entire lifecycle of the execution of that script into one line of code. It’s like this script execution never happened…or did it 😉 All kidding aside, we effectively have a serverless computing platform now. Using this technique in our data centers, we can spin up a container, on any version of PowerShell on any platform, run some workload/script and when the workload finishes, the container just goes away. For this to work well, we will need something to drive that process. In an upcoming blog post, we’ll talk more about how we can automate the running of PowerShell containers in Kubernetes.
 
In this post, we covered a lot, we looked at how you can interactively run PowerShell Core in a container, how you can pass cmdlets into a container at runtime, running different versions of PowerShell Core and also how you can persistently store scripts outside of containers in volumes and run those scripts in your containers. We also looked at how you can encapsulate the whole execution of a script and the containers life cycle into one line of code. Really giving you the ability to run PowerShell Core anywhere on any platform.

Check it out for sure. Containers today are where VMs were about a decade ago: becoming more common but still a bit “out there” for administrators. It’s not a stretch to say that within a few years, containers will be as ubiquitous as VMs were by 2012, if not more so.

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Building an AKS Cluster with Azure DevOps

Published 2019-04-24 by Kevin Feasel

Rob Sewell shows how to use Azure DevOps to build an AKS cluster with Terraform:

In the last few posts I have moved from building an Azure SQL DB with Terraform using VS Code to automating the build process for the Azure SQL DB using Azure DevOps Build Pipelines to using Task Groups in Azure DevOps to reuse the same Build Process and build an Azure Linux SQL VM and Network Security Group. This evolution is fantastic but Task Groups can only be used in the same Azure DevOps repository. It would be brilliant if I could use Configuration as Code for the Azure Build Pipeline and store that in a separate source control repository which can be used from any Azure DevOps Project.

Luckily, you can

And Rob shows us how it’s done.

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Centralized Kubernetes Management with Rancher

Published 2019-04-18 by Kevin Feasel

Praveen Sripati shows us how we can use Rancher to create a Kubernetes cluster anywhere, using AWS as an example:

In the previous blog  we explored on setting up an K8S Cluster on the AWS Cloud without using any additional softwares or tools. The Cloud Providers make it easy to create a K8S Cluster in the Cloud. The tough part is securing, fine tuning, upgradation, access management etc. Rancher provides a centralized management of the different K8S Clusters, these can be in any of the Cloud (AWS, GCP, Azure) or In-Prem. More on what Rancher has to offer on top of K8S here. The good thing about Rancher is that’s it’s 100% Open Source and there is no Vendor Lock-in. We can simply remove Rancher and interact with the K8S Cluster directly.

I like this kind of tooling because it reduces cloud lock-in. For something like Kubernetes, where the whole point is orchestration of ephemeral containers, there’s a lot of benefit in being able to shift between services as needed.

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Custom kubectl Plugin: Connect to SQL Server

Published 2019-04-18 by Kevin Feasel

Andrew Pruski shows how to create custom kubectl plugins:

When I deploy SQL Server to Kubernetes I usually create a load balanced service so that I can get an external IP to connect from my local machine to SQL running in the cluster. So how about creating a plugin that will grab that external IP and drop it into mssql-cli?

Let’s have a go at creating that now.

Click through for two demos including the appropriately-named kubectl prusk.

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Getting Started with Docker

Published 2019-04-15 by Kevin Feasel

Achilleus has a brief primer on Docker:

Now that we know, some basic definitions. It’s time we ask the main question! Why do I care?

There are many reasons you might wanna use Docker. I will give my perspective on why I started to learn about Docker.

I had to test my Kafka producers and consumers locally instead of deploying my code in DEV/QA even before I was sure things are working fine but also be sure that the same code, when deployed in other environments, should behave the same.

There are a few really good reasons for containers and testing is one of them.

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Persistent Storage and Kubernetes

Published 2019-04-12 by Kevin Feasel

Chris Adkin explains the concepts behind persistent storage in containers:

A question that often crops up is “Can I use local storage”, the answer is “It depends”. Kubernetes is essentially a container scheduler at its most basic and fundamental level. The ‘Pod’ is the unit of scheduling, containers in the same pod share the same life cycle and always run on the same node. For stateless pods life is reasonably simple and straight forward, for state-full pods, life is a bit more nuanced. If for any reason a node fails, the pods that ran on that node have to be rescheduled to run on a working node, and their  storage needs to follow them. This involves un-mounting the volume from the failed node and then mounting it on the node the pod(s) are rescheduled to run on. With basic vanilla hyper-converged storage, i.e. storage and compute in the same chassis, this will ultimately lead to scheduling problems. However, software defined solutions exist that enable this kind of infrastructure to be turned into a storage cluster which allows state to follow pods around the cluster. Some people automatically associated HDFS with local storage, the reason for this is probably because “Back in the day”, the most cost efficient way for Google to scale out its infrastructure was via commodity servers with local disks. 

Read the whole thing.

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Deploying and Executing Containerized Packages

Published 2019-04-08 by Kevin Feasel

Andy Leonard continues a series on Integration Services in Docker. Part 5 shows how you can deploy a package to a containerized SSIS instance:

Returning to Matt Masson’s PowerShell script – combined with the docker volume added earlier – I have a means to deploy an SSIS Project to the SSIS Catalog in the container.

Part 6 shows how we can run those packages:

An aside regarding attempting SSIS package execution from SSMS connected to an instance of SQL Server in a container (using the runas /netonly trick shared earlier: It appears to work, but doesn’t. The package execution is created but “hangs” in Pending Execution status:

Read both to learn more about Andy’s travails in getting this working.

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Managing Kubernetes Resources

Published 2019-04-04 by Kevin Feasel

Vincent-Philippe Lauzon takes us through some thoughts on Kubernetes resource allocation:

In this article we will look at how to inform Kubernetes about pods’ resources and how we can optimize for different scenarios.

A scenario that typically comes up is when a cluster has a bunch of pods where a lot of them are dormant, i.e. they don’t consume CPU or memory. Do we have to carve them a space they won’t use most of the time? The answer is no. As usual, it’s safer to provision capacity for a workload than relying on optimistic heuristic that not all workloads will require resources at the same time. So, we can configure Kubernetes optimistically or pessimistically.

Read the whole thing.

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