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Category: Containers

Troubleshooting an Azure ML Deployment Locally

I have a new video:

In this video, I take us through the process of creating a local deployment of an Azure ML managed endpoint. We will cover requirements, why you might want to do this, and common problems you may run into along the way.

This was a fun video to make, especially in anticipating the sorts of problems that come up along the way. I won’t pretend that it’s comprehensive but it does hit several of the most common problems I see (or cause).

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Application Portability Challenges with Kubernetes

Kiana Harris lays out some challenges:

As organizations embrace containerization and Kubernetes for their applications, the need for seamless portability across the Kubernetes ecosystem coupled with cloud object storage and local persistence has become a pressing concern.  In this blog post, we will dive into the core problem and dissect the complex challenges that customers face in achieving containerized app portability.

Read on for the list of challenges, followed by what you can do to address them. This is at a really high level but can provide food for thought.

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An Overview of Docker Security Principles

Jagdish Mohite talks security:

Docker incorporates several inherent security features that contribute to its overall security posture. When you use Docker to quickly create an environment and test some code, security is important enough (especially if you execute any , but when using Docker for production, multi-user environments, it is essential to treat the container as you would any other server environment.

The following is a list of some of the basic security principles that are baked into Docker.

This includes some of the things Docker does for your automatically, limitations around securing containers, and common attack modes. It’s a high-level overview but interesting to read.

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Persisting Data for SQL Server on Docker Swarm

Andrew Pruski saves the day, or at least the data:

In my last couple of blog posts (here and here) I talked about how to get SQL Server running in Docker Swarm. But there is one big (and show-stopping) issue that I have not covered. How do we persist data for SQL Server in Docker Swarm?

Docker Swarm, like Kubernetes, has no native method to persist data across nodes…so we need another option and one of the options available to us is Portworx.

So how can we use Portworx to persist SQL Server databases in the event of a node failure in Docker Swarm?

Read on to find out how.

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Secrets Management in Docker Swarm

Andrew Pruski has a secret:

In a previous post I went through how to run SQL Server in Docker Swarm and in this post I want to continue delving into the Docker Swarm platform by looking at secrets.

Like Kubernetes, Docker Swarm has functionality to store sensitive data in secrets. When running SQL Server in containers we usually have to manually type out the environment variable for the MSSQL_SA_PASSWORD which isn’t great if we want to store that code in a public repository so being able to obfuscate that password is great!

Read on for a failed first attempt, followed by analysis and then success.

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Deploying a SQL Server Container via go-sqlcmd

Jes Schultz builds a container:

In the past, you may have downloaded and installed SQL Server Developer Edition on your computer to test features, write queries, and have a sandbox. Do you want a more lightweight development environment that’s quicker to install and use? Enter Docker or Podmansqlcmd, and SQL Server containers. 

Our modern sqlcmd gives you the capability to query your existing SQL Server and Azure SQL Database instances. It also introduces new features such as creating containers in one line of code, using an existing backup file to restore a database when the instance is created, and opening Azure Data Studio for data exploration in one command. Here is how you can do this end-to-end. 

Click through for the demo.

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