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Category: Containers

Reporting Services Scale-Out With Docker

Published 2019-01-30 by Kevin Feasel

Paul Stanton architects out a scenario using Windocks to create cloned Reporting Services containers in order to scale out Reporting Services:

Database cloning is a key aspect of the SSRS scale out architecture, with database clones providing each container a complete set of databases.  Two or more VMs operated behind a load balancer delivers a highly available and scalable reporting service.  This article focuses on Windows SQL Server containers and Windows Virtual Hard Drive (VHD) based cloning, but the same architecture can support SQL Server Linux containers or conventional instances (Windows or Linux).   Redgate SQL Clone, for example would support SQL Server instances.   Other options include the use of storage arrays instead of Windows VHD based clones.   The trade-offs between SQL containers and instances, and between VHDs and storage arrays are covered in separate sections below. 

The combination of SSRS containers with database cloning is appealing for simplicity and operational savings.  SSRS containers are also drawing interest as part of public cloud strategies, as SSRS containers can be integrated with AWS RDS or SQL Azure databases to provide a horizontally scalable reporting solution.

This is a bit more complex than Reporting Services scale-out with Enterprise Edition, but if you’re on Standard Edition and can’t use scale-out, it’s an interesting alternative.

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Powershell Core On Ubuntu Using Docker

Published 2019-01-28 by Kevin Feasel

Max Trinidad has an Ubuntu VM running Powershell Core on Docker:

While learning about Docker Container, I notice that is much easier to installed on a Linux system. In Windows, Hyper-V is a requirement to install Docker, and specially if you want to use the “Windows Subsystem in Linux” WSL feature, there’s more setup to complete. So, I’m not using Hyper-V, I’m using VMware Workstation.  To keeping simple, I created an Ubuntu 18.04 VM using VMWare Workstation.

You can find the Docker CE installation instructions in the following link.

If you’re using Ubuntu 18.04. make sure to install Curl, as it isn’t included in the OS.

Click through for instructions on how to set this up and join the three layers club (which is not quite the three commas club but close).

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Deploying SQL Server To Kubernetes The Easy Way

Published 2019-01-16 by Kevin Feasel

Andrew Pruski doesn’t want to mess with a bunch of yaml files:

In previous posts I’ve run through how to deploy sql server to Kubernetes using yaml files. That’s a great way to deploy but is there possibly an easier way?
Enter Helm. A package manager for Kubernetes.
Helm packages are called charts and wouldn’t you know it? There’s a chart for SQL Server!
Helm comes in two parts. Helm itself is the client side tool, and tiller, which is the server side component. Details of what each part does can be found here.

They’re making it too easy now…

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A Docker-Based Sandbox For dbatools

Published 2019-01-09 by Kevin Feasel

Chrissy LeMaire takes us through using Docker to build a playground for learning the functionality inside dbatools:

I’ve long wanted to do this to help dbatools users easily create a non-production environment to test commands and safely explore our toolset. I finally made it a priority because I needed to ensure some Availability Group commands I was creating worked on Docker, too, and having some clean images permanently available was required. Also, in general, Docker is a just a good thing to know for both automation and career opportunities

Probably a little bit better to work on cmdlets you don’t know about in a sandboxed container rather than on production. Just a little bit.

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The Basics Of Docker For R Users

Published 2019-01-07 by Kevin Feasel

Colin Fay explains some of the core principles behind Docker, containerizing some R code along the way:

Docker is designed to enclose environments inside an image / a container. What this allows, for example, is to have a Linux machine on a Macbook, or a machine with R 3.3 when your main computer has R 3.5. Also, this means that you can use older versions of a package for a specific task, while still keeping the package on your machine up-to-date.
This way, you can “solve” dependencies issues: if ever you are afraid dependencies will break your analysis when packages are updated, build a container that will always have the software versions you desire: be it Linux, R, or any package.

Click through for the details. H/T R-bloggers

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Containerizing Python And MySQL

Published 2019-01-07 by Kevin Feasel

Allison Tharp walks us through containerizing a Python-based game she had created:

I’m really amazed at how easy creating the container was.  It took only 11 lines to spin up a Linux environment on my own machine.  The majority of the commands (7 of the 11) are simply adding the files and dependencies.  I’m also pretty shocked that I didn’t have to do anything to my Python script to get this to work.  I had assumed I would need to do something but, I didn’t.  Very cool!  Also, by using the following command while my Python script is running, I see that this is only taking up 1.3 GB!

Click through for scripts and important lessons learned along the way.

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Building A Kubernetes Cluster With Kubespray

Published 2019-01-02 by Kevin Feasel

Chris Adkin continues a series on Kubernetes clusters:

In essence Kubespray is a bunch of Ansible playbooks; yaml file that specify what actions should take place against one or more machines specified in a hosts.ini file, this resides in what is known as an inventory. Of all the infrastructure as code tools available at the time of writing, Ansible is the most popular and has the greatest traction. Examples of playbooks produced by Microsoft can be found on GitHub for automating tasks in Azure and deploying SQL Server availability groups on Linux. The good news for anyone into PowerShell is that PowerShell modules can be installed via Ansible and PowerShell commands can be executed via Ansible. Also, there are people already using PowerShell desired state configuration with Ansible. Ansible’s popularity is down to the facts it is easy to pick up and agent-less because it relies on ssh, hence why one of the steps in this post includes the creation of keys for ssh. This free tutorial is highly recommended for anyone wishing to pick up Ansible.

Click through for a step-by-step tutorial.

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Combining Windows And Linux Docker Containers

Published 2018-12-26 by Kevin Feasel

Rob Sewell crosses the streams:

This is NOT a production ready solution, in fact I would not even recommend that you try it.
I definitely wouldn’t recommend it on any machine with anything useful on it that you want to use again.
We will be using a re-compiled dockerd.exe created by someone else and you know the rules about downloading things from the internet don’t you? and trusting unknown unverified people?
Maybe you can try this in an Azure VM or somewhere else safe.
Anyway, with that in mind, lets go.

That’s the kind of intro that makes me want to try it out.

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Deploying SQL Server 2019 Big Data Clusters With Kubernetes

Published 2018-12-19 by Kevin Feasel

Chris Adkin has the start of a new series:

Minikube is a good learning tool and Microsoft provides instructions for deploying a big data cluster to this ‘Platform’. However, its single node nature and the fact that application pods run on the master node means that this does not reflect a cluster that anyone would run in production. Kubernetes-as-a-service is probably by far the easiest option for spinning a cluster up, however it relies on an Aws, Azure or Google Cloud Platform account, hence there is a $ cost associated with this. This leaves a vanilla deployment of Kubernetes on premises. Based on the assumption that most people will have access to Windows server version 2008 or above, a relatively cheap and way of deploying a Kubernetes cluster is via Linux virtual machines running on Hyper-V. This blog post will provide step by step instructions for creating the virtual machines to act as the master and worker nodes in the cluster. 

This is going on my “try this out when I have time” list.  So expect a full report sometime in the year 2023.

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