Press "Enter" to skip to content

Category: Containers

Deploying a Big Data Cluster to a Multi-Node kubeadm Cluster

Mohammad Darab shows how we can deploy a SQL Server Big Data Cluster on a multi-node kubeadm cluster:

There are a few assumptions before we get started:

1. You have at least 3 virtual machines running with the minimum hardware requirements
2. All your virtual machines are running Ubuntu Server 16.04 and have OpenSSH installed
3. All the virtual machines have static IPs and on the same subnet
4. All the virtual machines are updated and have been rebooted

Mohammad shows how to set up the cluster, configure Kubernetes, and then install Big Data Clusters. Definitely worth the read if you’re interested in building a Big Data Cluster on-premises.

Leave a Comment

Spark on Docker on YARN on Cloud

Adam Antal has included all of the layers:

Bringing your own libraries to run a Spark job on a shared YARN cluster can be a huge pain. In the past, you had to install the dependencies independently on each host or use different Python package management softwares. Nowadays Docker provides a much simpler way of packaging and managing dependencies so users can easily share a cluster without running into each other, or waiting for central IT to install packages on every node. Today, we are excited to announce the preview of Spark on Docker on YARN available on CDP DataCenter 1.0 release.

Joking about stack length aside, this looks really useful.

Leave a Comment

Upgrading SQL Server Windows Docker Containers

Emanuele Meazzo shows how you can upgrade SQL Server if you are using a Windows Docker container instead of Linux:

With the 1st CU for SQL 2019 released just yesterday, and Microsoft updating the docker image right away, the only natural response for me was to update the docker instance that I showed you how to deploy a few months back.

In theory, a docker container can’t be really “updated”, they’re meant to be stateless machines that you spin up and down responding to changes in demand; what we’re technically doing is creating a new container, based on a new image, that has the same configuration and uses the same persistent storage as the old one.

Read on to see how you can perform this upgrade without losing your data.

Leave a Comment

Another Way to Upgrade SQL Server 2017 Containers to 2019

Anthony Nocentino gives us another option for upgrading SQL Server on containers:

Yesterday in this post I described a method to correct permissions when upgrading a SQL Server 2017 container using Data Volumes to 2019’s non-root container on implementations that use the Moby or HyperKit VM. My friend Steve Jones’ on Twitter wondered if you could do this in one step by attaching a shell (bash) in the 2017 container prior to shutdown. Absolutely…let’s walk through that here in this post.  I opted to use an intermediate container in the prior post out of an abundance of caution so that I was not changing permissions on the SQL Server instance directory and all of the data files while they were in use. Technically this is a-ok, but again…just being paranoid there.

Click through for that process. The good news is that with upgrading from SQL Server 2019 to SQL Server 202x, I wouldn’t expect that we’d need to go through this again, as the process would stay non-root forevermore.

Comments closed

Upgrading SQL Server 2017 Containers to 2019

Anthony Nocentino takes us through one of the big changes to SQL Server containers:

When you start up the 2017 container, the SQL Server (sqlservr) process is running as root (uid 0). Any files created by this process will have the user and group ownership of the root user. Now when we come along later and start up a 2019 container, the sqlservr process is running as the user msssql (uid 10001 by default). This new user doesn’t have permission to open the database files and other files used by SQL Server.

Read on to see how Anthony fixed this.

Comments closed

Named Volumes in Docker with SQL Server 2019

Andrew Pruski takes us through one of the biggest changes with SQL Server 2019 in containers:

I’ve seen a few people online asking how to use docker named volumes with the new SQL Server 2019 RTM images. Microsoft changed the way SQL runs within a container for the RTM versions, SQL no longer runs as the root user.

This is a good thing but does throw up some issues when mounting volumes to create databases on.

Let’s run through what the issue is and how to overcome it.

Click through to see what you need to add to your DOCKERFILE to get things working.

Comments closed

Deploying a Big Data Cluster with Azure Data Studio

Mohammad Darab shows how you can deploy a Big Data Cluster to Azure Kubernetes Service using Azure Data Studio:

A few months ago I posted a blog on deploying a BDC using the built-in ADS notebook. This blog post will go a bit deeper into deploying a Big Data Cluster on AKS (Azure Kubernetes Service) using Azure Data Studio (version 1.13.0). In addition, I’ll go over the pros and cons and dive deeper into the reasons why I recommend going with AKS for your Big Data Cluster deployments.

AKS does make it pretty easy. The toughest part for me was figuring out which instance types were supported—I tried a few which would save me money and they weren’t available. I do like that they added a check to view availability before completing the notebook; that wasn’t in the preview version.

Comments closed

SQL Server Trends Worth Watching

Grant Fritchey follows up on a Kevin Hill tweet:

There are a million things to learn about in our rapidly shifting technological landscape, but I think this assessment, especially the way it was put, “no longer justify ignoring” really nails some of the fundamentals.

Let’s talk about why you can no longer ignore Docker, Git and DBATools either.

If you’re a DBA and aren’t familiar with Docker, Git, or DBATools, that’s a pretty good trio of things to spend some time learning. You can survive without them, but you’re more likely to thrive if you know them.

Comments closed

Deploying a Container Instance in Azure

Anibal Kolker takes us through container deployment in Azure:

As derived from the title, the objective of this post is to help you deploy a container instance inside Azure.

However, we’ll extend the typical scenario and make a slightly more extensive use of networking capabilities, by placing the container group inside a private subnet.

Note: For this example, and for simplicity only, we’ll use NGINX as our container of choice. Of course, you’re welcome to try with any other image.

There are a few pieces in play, but Anibal does a good job putting it all together.

Comments closed