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Category: Containers

The Benefits of Kubernetes for App Hosting

Joy George Kunjikkur enumerates reasons why you might want to use Kubernetes to host applications:

I started writing this post 2-3 years back. Mainly when Apache Spark 2.3 started supporting Kubernetes (K8s) in 2018. It was obvious that Kubernetes is taking over app hosting space the same way virtual machines took over physical machines. All are expected to understand where the industry is moving and adopt. Hence I paused this post as there is nothing I need to endorse. But it’s time to resume this post and publish it.

Click through for a slew of thoughts on the topic.

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A Primer on Azure Kubernetes Service

Arun Sirpal gives us a brief introduction of Azure Kubernetes Service:

You have the ability to run these on-premises (complex) or in a cloud service, like AWS or Azure. Hence AKS – Azure Kubernetes Service which helps reduce the complexity and operational overhead of managing Kubernetes by offloading much of that responsibility to Microsoft. You may be wondering how does containers relate to this? It was something on my mind when I first entered into this technology. Remember that containers is the next step beyond traditional virtualisation, you can run SQL Server Linux in containers, as an example. I then look at AKS as the “management” layer of the container solution, carrying out tasks such as scheduling, scaling, health, load balancing and host management.

Click through for more information.

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SQL Server Baselines with the TIG Stack

Mark Wilkinson combines Telegraf, InfluxDB, and Grafana:

Lots of folks wonder why I would go through the trouble of building out a system when so many vendors have already solved the problem of collecting baseline metrics. The answer at the time was simple: cost. With my setup I could monitor close to 600 instances (including dev) for $3,000 USD per year. That includes data retention of ~2 years! Are there some administration costs as far as my time is concerned? Of course. In the begining things were a little rough as I learned more about InfluxDB, but once things were configured correctly the most work I’ve had to do is to expand the size of the data drive as we started collecting more metrics.

Click through for more info and check out the GitHub repo.

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Fun with Containers

Barney Lawrence has some fun with containers, starting with running SQL Server and ending with something a little more entertaining:

Many of you out there may, like me, find yourselves sharing a home with a miniature Minecraft Addict. I do and in between showing off her latest builds she’s begun pestering me to find a way to play with friends and family. I figured I could maybe save some work and re-use my newfound containerised powers for fun as well as profit and a few quick searches proved me right.

Click through for more.

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Uses for SQL Server Containers

Aaron Bertrand explains two good uses for using SQL Server containers:

I used this technique of “stop, drop, repeat” just the other day while testing some behavior around case-sensitive and binary collations at the instance level. In the old days, I would have had to install a second full-on instance of SQL Server in order to test a specific instance-level collation, then repeat for every collation in my set of tests. Yikes! With containers, this is much easier; I just have to add one additional argument to the docker run command:

Check it out for a quick walkthrough of how to spin up a container and some good uses for it.

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Running Azure ML On-Premises via Azure Arc

Tsuyoshi Matsuzaki takes us through running Azure Machine Learning via Azure Arc:

First of all, you must run Azure Arc enabled Kubernetes on-premise or on 3rd party cloud. For running Arc-enabled Machine Learning later, use machines with more than 4 CPUs, since Arc-enabled ML requires enough resources.

In this post, I assume that we run KIND (Kubernetes in Docker) cluster on on-premise Ubuntu server. (For test purpose, I have used Ubuntu 18.04 on a single virtual machine in Azure, Standard D3 v2, which has 4 CPUs and 14 GB memory.)

Click through to see how it’s done.

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SQL Server on Azure Container Instances

Arun Sirpal has a series for us. Part 1 involves spinning up SQL Server on ACI:

This is Microsoft’s serverless technology which allows us to deploy containers without having to worry about managing the underlying hardware. It’s a way to get access to SQL fast (faster than traditional methods like installing a virtual machine) to do things like test code fixes etc.

There a couple of ways of doing this, you can use the portal, PowerShell or Azure CLI, I actually like Azure CLI.

Part 2 gives you an idea of what you get:

In the last post we built an image of SQL server 2019 Linux hosted in Azure Container Instance for fast access to SQL server. So, your next question is probably, lets see some database action?

When you connect to SSMS its not different, the feel and look, is, SQL server. Lets have a tour.

The normal warning with Azure Container Instances is that they’re great for development and testing efforts (in part because of how inexpensive it is compared to alternatives on Azure) but won’t have the same uptime or high availability guarantees that a service like Azure Kubernetes Service will have.

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Goodbye, SQL Server on Windows Containers

Amit Khandelwal shuts the doors:

As you may be aware, the SQL Server on Windows Containers Beta program began in 2017. It has remained in Beta mode meant for only test and development environment until now. Due to the existing ecosystem challenges and usage patterns we have decided to suspend the SQL Server on Windows Containers beta program for foreseeable future. Should the circumstances change, we will revisit the decision at appropriate time and make relevant announcement.

I never heard of many people using Widows containers, but with the differences in available products and features between Windows and Linux versions of SQL Server, I can see why some people would want to use them.

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