Monthly Archives: May 2019

Workshop – Kubernetes Zero to Hero – Installation, Configuration, and Application Deployment

Pre-conference Workshop at SQLSaturday Baton Rouge

I’m proud to announce that I will be be presenting an all day pre-conference workshop at SQL Saturday Chicago on March 23rd 2018! This one won’t let you down! 

The workshop is Kubernetes Zero to Hero – Installation, Configuration, and Application Deployment” 


Here’s the abstract for the workshop

Modern application deployment needs to be fast and consistent to keep up with business objectives and Kubernetes is quickly becoming the standard for deploying container-based applications, fast. In this day-long session, we will start with an architectural overview of a Kubernetes cluster and how it manages application state. Then we will learn how to build a production-ready cluster. With our cluster up and running, we will learn how to interact with our cluster, common administrative tasks, then wrap up with how to deploy applications and SQL Server. At the end of the session, you will know how to set up a Kubernetes cluster, manage a cluster, deploy applications and databases, and how to keep everything up and running.

Session Objectives

  • Introduce Kubernetes Cluster Components
  • Introduce Kubernetes API Objects and Controllers
  • Installing Kubernetes
  • Interacting with your cluster
  • Storing persistent data in Kubernetes
  • Deploying Applications in Kubernetes
  • Deploying SQL Server in Kubernetes
  • High Availability scenarios in Kubernetes


How much does it cost?

The full day training event is $125 per attendee.

What can I bring into the event?
WiFi at the location is limited. The workshop will be primarily demonstration based. Code will be made available for download prior to the event if you would like to follow along during the session.

How can I contact the organizer with any questions?
Please feel free to email me with any questions:

What’s the refund policy?
7 days: Attendees can receive refunds up to 7 days before your event start date.

Do I need to know SQL Server or Kubernetes to attend this workshop?
No, while we will be focusing on deploying SQL Server in Kubernetes, no prior knowledge of SQL Server or Kubernetes is needed. We will build up our Kubernetes skills using SQL Server as the primary application we will deploy.

What are the prerequisites for the workshop?
All examples will be executed at the command line, so proficiency at a command line is required. Platform dependent (Linux/Windows,Cloud CLIs) configurations and commands will be introduced and discussed in the workshop.  

New Pluralsight Course – Managing the Kubernetes API Server and Pods

New Pluralsight Course – Managing the Kubernetes API Server and Pods

My new course “Managing the Kubernetes API Server and Pods” in now available on Pluralsight here! Check out the trailer here or if you want to dive right in go here! This course offers practical tips from my experiences managing Kubernetes Clusters and workloads for Centino Systems clients.

This course targets IT professionals that design and maintain Kubernetes and container based solutions.The course can be used by both the IT pro learning new skills and the system administrator or developer preparing for using Kubernetes both on premises and in the Cloud.

Let’s take your Kubernetes administration and configuration skills to the next level and get you started now!

The modules of the course are:

  • Using the Kubernetes API – In this module we will dive into the Kubernetes API, looking closely at the architecture of the API Server and how exposes and manages Kubernetes API Objects. Then we will learn about API versioning and object maturity. Next, we’ll look at anatomy of an API request, leading us up to debugging interactions with the API Server.
  • Managing Objects with Labels, Annotations and Namespaces – In this demo-heavy module, we will learn out to organize and interact with resources in Kubernetes using Labels, Annotations, and Namespaces. We will also learn how to use labels to influence Kubernetes operations in Controllers and Pod scheduling.
  • Running and Managing Pods – In this module, we will look at the fundamental unit of work in Kubernetes, the Pod, looking at why the Pod abstraction is needed and design principals for placing your applications in Pods and running those Pods in your cluster.  We’ll examine Pod lifecycle and how its state impacts application health and availability. We wrap up with how Controllers interact with Pods and how Pods report their health status with readiness probes and liveness probes. 


Check out the course at Pluralsight!


Speaking at SQLSaturday Atlanta – 845

Speaking at SQLSaturday Atlanta!

I’m proud to announce that I will be speaking at SQL Saturday Atlanta on May 17th 2018! This one won’t let you down! Check out the amazing schedule!

If you don’t know what SQLSaturday is, it’s a whole day of free SQL Server training available to you at no cost!

If you haven’t been to a SQLSaturday, what are you waiting for! Sign up now!

My presentation is Containers – You Better Get on Board!” 

SQLSaturday #845 - Atlanta 2019

Here’s the abstract for the talk

Containers are taking over, changing the way systems are developed and deployed…and that’s NOT hyperbole. Just imagine if you could deploy SQL Server or even your whole application stack in just minutes. You can do that, leveraging containers! In this session, we’ll get you started on your container journey learning container fundamentals in Docker, then look at some common container scenarios and introduce deployment automation with Kubernetes.

In this session we’ll look at
Container Fundamentals with Docker
Common Container Scenarios
Automation with Kubernetes

Prerequisites: Operating system concepts such as command line use and basic networking skills.

Data Persistency and Advanced SQL Server Disk Topologies in Kubernetes

When working with SQL Server in containers and Kubernetes storage is a key concept. In this post, we’re going to walk through how to deploy SQL Server in Kubernetes with Persistent Volumes for the system and user databases.

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. 

Using Environment Variables for Container Configuration

Container-based applications use environment variables for configuration at startup. The SQL Server container has a collection of environment variables that can be used to configure it at container startup. We will leverage two of those in this configuration. MSSQL_DATA_DIR and MSSQL_LOG_DIR these allow us to define a file system locations for user database and log files. When the SQL Server container is started inside the Pod, it reads the environment variables at runtime and sets its configuration based on those values. We define these variables as part of the Pod Spec. We will cover that configuration below.

Using Persistent Volumes to Maintain Database State

To persist the state of our SQL Server container, we will configure SQL Server to store its data and log files for both user and system databases on Persistent Volumes.

First, let’s review how SQL Server in a container starts up. During the initial startup, the SQL Server process checks to see if there are any system databases in the default system file location which is, /var/opt/mssql/data. If there are none the system databases are copied there, if they are there no action is taken. 

To add persistently to the system databases, and really all of the other components of SQL Server such as the Error Log and other system files, we will configure /var/opt/mssql so that it is backed by a Persistent Volume.

By placing the system databases on a Persistent Volume, when a Pod is recreated and the Persistent Volumes are attached and mounted in the same location when the SQL Server process starts up it sees the system databases and has what it needs to maintain state between creation.

If there are records for user databases in the system databases, SQL Server will start the process of bringing those databases online as well. We certainly the default location for user databases is /var/opt/mssql/data but we are going to override that with an environment variable for both the data and log directories, placing each on a dedicated Persistent Volumes.

Let’s walk through that configuration together. 

Persistent Volume Claims

In this configuration, we will use dynamic storage provisioning. In dynamic provisioning, a Persistent Volume Claim (PVC) is used to request a Persistent Volume (PV) from a Storage Class. In this case, we’ll be using AKS’s managed-premium Storage Class. 

Here we define three PVCs, one for each place we want Persistent Volume, for the system files and databases and the user database and log files.

apiVersion: v1
kind: PersistentVolumeClaim
  name: "pvc-sql-data"
  - ReadWriteOnce
  storageClassName: managed-premium
      storage: 10Gi
apiVersion: v1
kind: PersistentVolumeClaim
  name: "pvc-sql-system"
  - ReadWriteOnce
  storageClassName: managed-premium
      storage: 10Gi
apiVersion: v1
kind: PersistentVolumeClaim
  name: "pvc-sql-log"
  - ReadWriteOnce
  storageClassName: managed-premium
      storage: 10Gi


In the Pod spec for our Deployment, we want to define several elements to support this configuration. 

  • Volumes – define volumes that can be mounted by this Pod. In this case, we’re creating and naming three volumes, backed by the PVCs defined above.
  • volumeMounts – volumes mounted into the container and their mountPath, location. This maps the names from the named Volumes to a location in the filesystem in the container.
  • env – due to the ephemerality of the container in the Pod, we need to tell SQL Server at start up that the data and log files will be stored in a specified directory. We are leaving the system databases and files in the default location which is /var/opt/mssql
The net effect of this storage configuration is that we are mapping the Persistent Volumes into a particular location in the filesystem inside the container. 
apiVersion: apps/v1
kind: Deployment
  name: mssql-deployment
  replicas: 1
      app: mssql
    type: Recreate
        app: mssql
      terminationGracePeriodSeconds: 10
      - name: mssql
        image: ''
        - containerPort: 1433
        - name: ACCEPT_EULA
          value: 'Y'
        - name: MSSQL_DATA_DIR
          value: '/data'
        - name: MSSQL_LOG_DIR
          value: '/log'
        - name: SA_PASSWORD
          value: 'S0methingS@Str0ng!'
        - name: mssql-system
          mountPath: /var/opt/mssql
        - name: mssql-data
          mountPath: /data
        - name: mssql-log
          mountPath: /log
      - name: mssql-system
          claimName: pvc-sql-system
      - name: mssql-data
          claimName: pvc-sql-data
      - name: mssql-log
          claimName: pvc-sql-log


We’ll front end our SQL Server with a public IP address and a load balancer. 

apiVersion: v1
kind: Service
  name: mssql-deployment
    app: mssql
    - protocol: TCP
      port: 31433
      targetPort: 1433
  type: LoadBalancer

Apply the Configuration

Save the code above into a YAML file and deploy it into SQL Server.

kubectl apply -f deployment-advanced-disk.yaml

You’ll get this output

persistentvolumeclaim/pvc-sql-data created
persistentvolumeclaim/pvc-sql-system created
persistentvolumeclaim/pvc-sql-log created
deployment.apps/mssql-deployment created
service/mssql-deployment created

Confirm the configuration

We can use kubectl get pv to list the Persistent Volumes (PV) dynamically allocated by our cluster. Here there are three Persistent Volumes. The key here is the status is Bound, which means they are bound to a PVC. I also want to point out the Reclaim Policy is Delete. This means if the PVC is deleted, the PV will be deleted at a cleanup interval sometime in the future. 

kubectl get pv
NAME                                       CAPACITY   ACCESS MODES   RECLAIM POLICY   STATUS   CLAIM                    STORAGECLASS      REASON   AGE
pvc-e0b418ef-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            Delete           Bound    default/pvc-sql-data     managed-premium            11m
pvc-e0cf2345-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            Delete           Bound    default/pvc-sql-system   managed-premium            11m
pvc-e0ea01a8-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            Delete           Bound    default/pvc-sql-log      managed-premium            11m

With kubectl get pvc we get a list of the PVCs in our configuration, once for each we defined above. The key here is the status is Bound, or that they are bound to a PV.

kubectl get pvc
NAME             STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS      AGE
pvc-sql-data     Bound    pvc-e0b418ef-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            managed-premium   12m
pvc-sql-log      Bound    pvc-e0ea01a8-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            managed-premium   12m
pvc-sql-system   Bound    pvc-e0cf2345-6e69-11e9-a433-f659caf6a6f5   10Gi       RWO            managed-premium   12m 

Now let’s use kubectl describe pods to get the deep dive info about our storage configuration and how it’s mapped into the Pod. 

There are three keep places in the output below I want to point you to

  • Containers: mssql: Environment: you’ll find the two environment variables set for the data and log directories. Configured as /data and /log
  • Mounts: we see the file system location inside the container and the name of the Volumes defined in the Pod Spec
  • Volumes: we see the name of the Volumes, their type, claim name and the read/write status.
  • Events: this is a log of the events for the creation of this Pod. Key here is that sometimes the container will come up prior to the storage being available to the Pod. That’s what the error below is, but it clears itself up and the container is able to start.
kubectl describe pods
Name:               mssql-deployment-df4cf5c4c-nf8lf
Namespace:          default
Priority:           0
Node:               aks-nodepool1-89481420-2/
Start Time:         Sat, 04 May 2019 07:41:59 -0500
Labels:             app=mssql
Status:             Running
Controlled By:      ReplicaSet/mssql-deployment-df4cf5c4c
    Container ID:   docker://f2320ae8f94c24fbb04214b903b4a218b82e9548f8d88a95daa7e207eeaa42b4
    Image ID:       docker-pullable://
    Port:           1433/TCP
    Host Port:      0/TCP
    State:          Running
      Started:      Sat, 04 May 2019 07:44:21 -0500
    Ready:          True
    Restart Count:  0
      ACCEPT_EULA:                   Y
      MSSQL_DATA_DIR:                /data
      MSSQL_LOG_DIR:                 /log
      SA_PASSWORD:                   S0methingS@Str0ng!
      KUBERNETES_PORT:               tcp://
      KUBERNETES_PORT_443_TCP:       tcp://
      /data from mssql-data (rw)
      /log from mssql-log (rw)
      /var/opt/mssql from mssql-system (rw)
      /var/run/secrets/ from default-token-z9sbf (ro)
  Type              Status
  Initialized       True
  Ready             True
  ContainersReady   True
  PodScheduled      True
    Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
    ClaimName:  pvc-sql-system
    ReadOnly:   false
    Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
    ClaimName:  pvc-sql-data
    ReadOnly:   false
    Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
    ClaimName:  pvc-sql-log
    ReadOnly:   false
    Type:        Secret (a volume populated by a Secret)
    SecretName:  default-token-z9sbf
    Optional:    false
QoS Class:       BestEffort
Tolerations: for 300s
        for 300s
  Type     Reason                  Age   From                               Message
  ----     ------                  ----  ----                               -------
  Normal   Scheduled               13m   default-scheduler                  Successfully assigned default/mssql-deployment-df4cf5c4c-nf8lf to aks-nodepool1-89481420-2
  Normal   SuccessfulAttachVolume  13m   attachdetach-controller            AttachVolume.Attach succeeded for volume "pvc-e0ea01a8-6e69-11e9-a433-f659caf6a6f5"
  Normal   SuccessfulAttachVolume  12m   attachdetach-controller            AttachVolume.Attach succeeded for volume "pvc-e0cf2345-6e69-11e9-a433-f659caf6a6f5"
  Normal   SuccessfulAttachVolume  12m   attachdetach-controller            AttachVolume.Attach succeeded for volume "pvc-e0b418ef-6e69-11e9-a433-f659caf6a6f5"
  Warning  FailedMount             11m   kubelet, aks-nodepool1-89481420-2  Unable to mount volumes for pod "mssql-deployment-df4cf5c4c-nf8lf_default(027c46f7-6e6a-11e9-a433-f659caf6a6f5)": timeout expired waiting for volumes to attach or mount for pod "default"/"mssql-deployment-df4cf5c4c-nf8lf". list of unmounted volumes=[mssql-system mssql-data]. list of unattached volumes=[mssql-system mssql-data mssql-log default-token-z9sbf]
  Normal   Pulled                  11m   kubelet, aks-nodepool1-89481420-2  Container image "" already present on machine
  Normal   Created                 11m   kubelet, aks-nodepool1-89481420-2  Created container
  Normal   Started                 11m   kubelet, aks-nodepool1-89481420-2  Started container

Creating a Database and Verifying File Location

With this code, we’ll get our IP address for our SQL Server service then we’ll create a database and query master_files for a list of data files. Notice I’m defining my service port as 31443 which is what we defined when creating our service in the earlier step.

SVCIP=$(kubectl get svc mssql-deployment | grep mssql-deployment |  awk '{print $4}')
sqlcmd -S $SVCIP,31433 -U sa -Q 'CREATE DATABASE TestDB1' -P $PASSWORD
sqlcmd -S $SVCIP,31433 -U sa -Q 'SELECT name,physical_name from sys.master_files' -P $PASSWORD

And we’ll get this output, you can see all of the system databases backed by /var/opt/mssql and our user database is on /data and the log is on /log. All backed by Persistent Volumes.

master        /var/opt/mssql/data/master.mdf
mastlog       /var/opt/mssql/data/mastlog.ldf
tempdev       /var/opt/mssql/data/tempdb.mdf
templog       /var/opt/mssql/data/templog.ldf
modeldev      /var/opt/mssql/data/model.mdf
modellog      /var/opt/mssql/data/modellog.ldf
MSDBData      /var/opt/mssql/data/MSDBData.mdf
MSDBLog       /var/opt/mssql/data/MSDBLog.ldf
TestDB1       /data/TestDB1.mdf
TestDB1_log   /log/TestDB1_log.ldf

Confirming Persistency

Let’s go ahead and delete our Pod to confirm that when it’s recreated by our Deployment our data is still there. 

kubectl get pods
NAME                               READY   STATUS    RESTARTS   AGE
mssql-deployment-df4cf5c4c-nf8lf   1/1     Running   0          4d2h

kubectl delete pod mssql-deployment-df4cf5c4c-nf8lf 
pod "mssql-deployment-df4cf5c4c-nf8lf" deleted

Once the Pod is recreated, let’s query master files to see where our databases are located. And you’ll find that your the database created in the previous step persisted between Pod creations.

sqlcmd -S $SVCIP,31433 -U sa -Q 'SELECT name,physical_name from sys.master_files' -P $PASSWORD

master        /var/opt/mssql/data/master.mdf
mastlog       /var/opt/mssql/data/mastlog.ldf
tempdev       /var/opt/mssql/data/tempdb.mdf
templog       /var/opt/mssql/data/templog.ldf
modeldev      /var/opt/mssql/data/model.mdf
modellog      /var/opt/mssql/data/modellog.ldf
MSDBData      /var/opt/mssql/data/MSDBData.mdf
MSDBLog       /var/opt/mssql/data/MSDBLog.ldf
TestDB1       /data/TestDB1.mdf
TestDB1_log   /log/TestDB1_log.ldf

OpenSSH Resources for Windows and PowerShell

Had a conversation with a good friend in the SQL Community about OpenSSH and how it fits as a transport layer for PowerShell Remoting. I pointed him towards several resources I have online. So here’s a post aggregating those resources.

If you’re looking to get started with OpenSSH on Linux and Windows Systems check out thisPowerShell Summit presentation I did in 2018. This covers OpenSSH in theory and practice.

Session: OpenSSH Internals for PowerShell Pros

  • Remote Access Concepts
  • OpenSSH Architecture
  • Authentication Methods (including Key Based Authentication)
  • OpenSSH Server and Client Configuration

If you’re looking to get started with OpenSSH based PowerShell Remoting check out this session from PowerShell Summit in 2018 co-presented with Richard Siddaway.

Session: PowerShell Remoting: Installing and TroubleShooting in a Multiplatform Environment

  • Installing OpenSSH on Windows and Linux
  • Authentication Users (Including AD Authentication)
  • Setting Up PowerShell Remoting on Windows and Linux
  • Troubleshooting OpenSSH

Shortly after I did the sessions above, OpenSSH was released as a Window Capability, check out this blog post on how to install OpenSSH at the command line using Add-WindowsCapability.  This also applies to Windows 2016 Server. 

Session: Firewall Evasion and Remote Access with OpenSSH

  • OpenSSH is much more than just remote terminal access to servers, it provides a full suite of remote connectivity methods to your network and its services. In this session, we will look at how to use OpenSSH and its forwarding, tunneling and VPN capabilities so that we can reach securely reach network services that are behind firewalls and other security boundaries. Common use cases for these techniques are cloud jump boxes, secure access into segmented networks and being able to get remote access and move data around in poorly secured networks….these tips are things that will likely get you some extra attention from your security team

Blog Post: Configuring Passwordless PowerShell Remoting over SSH

Blog Post: Distributing SSH User Keys via PowerShell

Blog Post: Installing OpenSSH Server on Windows 10

Blog Post: PowerShell Remoting in Multi-Platform Environments using OpenSSH

Using PowerShell in Containers

The vision for PowerShell Core is to be able to run PowerShell anywhere. In this article, I’m going to discuss how you can use Docker Containers to enable just that. We’ll look at running PowerShell in a container, running cmdlets, running different versions of PowerShell at the same time, and also how to build our own “serverless” computing platform.

Let’s address a few reasons why you would want to run PowerShell in a container.

  • Speed and agility – this for me is probably the number one reason to run PowerShell in a container.  The PowerShell container images are coming in at around 375MB, this means with a modern Internet connection you’ll be able to pull a PowerShell container image and be up in running in a very small amount of time.
  • Version – there are container images available for every release of PowerShell Core, including preview/release candidate code. With containers, you can run multiple versions of PowerShell Core in a way where they will not conflict with each other.
  • Platform independence – there are container images for Ubuntu, Fedora, Windows Server Core, Nano Server and more. This allows you to be able to consume PowerShell Core regardless of your underlying platform. You can select whichever image you want, pull the container and go. 
  • Testing – if you need to test your scripts across various versions of PowerShell Core you can pull the container, run the script on the exact version you need. You can have multiple containers on your system running multiple versions of PowerShell and be able to run them all at the same time.  
  • Isolation – containers will allow you to have self-contained environments for execution, security, environment, and configuration settings. You can also use this idea to isolate conflicting modules from each other. This is particularly valuable when developing modules and/or cmdlets.

Getting Up and Running

Let’s get started with using PowerShell Core in a container. First up, we will want to pull the Docker Container Image to our local machine. This will pull the image with the latest tag. Which at the time of this post is 6.2.0-ubuntu-18.04.

With the container image local, let’s go ahead and start up the container. In this first go, I’m going to start up the container with the docker run command and with the –interactive and –tty flags. What these flags do is, when the container starts, attach to the terminal of the container so I can use PowerShell Core interactively at the command line.

This will get you a PowerShell prompt. I told you this was going to be fast.

From that prompt, we can do the normal PowerShell things we need to do. Let’s start our journey like all good PowerShell demos do and run Get-Process. You’ll notice that there is only one process running in the container, and that’s your pwsh session. This is due to the isolation concepts of Containers. With this isolation, problems like conflicting modules and settings go away. The container gives you script an isolated execution environment. If you need to have two conflicting versions of a module, DLL or library to run your workload or script…you can use a container to isolate their execution giving them the ability to co-exist on the same system.

We can use exit to get out of PowerShell. When you exit PowerShell the container will stop. You can see that status of your container with docker ps.

If you’d like to get back into your container you can use docker start pwsh-latest -i where pwsh-latest is the container name we just created and -i is for interactive (we used –interactive earlier). Run that and you’ll land right back at a PowerShell prompt again. 

Running a cmdlet When Starting a Container

Now, let’s say we wanted to start our container up and non-interactively run a cmdlet right away, we can do that. With the docker run command, we can tell the container that we want it to start pwsh and pass in a cmdlet as a parameter into pwsh, with the -c parameter and that cmdlet will be executed. Let’s check out how.
From a performance standpoint, I want to point out the time it takes to do this work, we can use the time command to help us with that. Less than two seconds to start the container, start pwsh and execute our cmdlet and shut down the container.
Now let’s say I wanted to test a cmdlet execution against a specific version of PowerShell Core, perhaps even a Release Candidate. Let’s change the tag from latest to preview and docker will pull that container, start it up and we immediately have an environment for testing. This could be leveraged for script testing, cmdlet testing, module testing and so on. In the output below, you can see the preview tag points to the 6.2.0-rc1 version of PowerShell Core.
Now, each time we started a container so far in this post and then exited pwsh, the container shut down and was still on our system. We can see the containers with a docker ps -a. We can restart any of these containers and get them back by using the command mentioned previously.
We can delete each container by name, using docker rm then specifying the name as a parameter. For example, docker rm pwsh-latest would delete that container.

Running a Script When Starting a Container

When a container is deleted, the data “inside” the container is deleted too. So if we created a script inside a container and then delete the container that means the script would go away too. In Docker, we can use a volume to help us with this. A volume allows us to store our data externally to the container, we can mount the volume inside the container and it looks like it’s part of the container’s file system.
With volumes, when we delete the container, the data stays inside the volume. We can then create a new container and attach the volume to that new container and the data will be there for us to work with.
Let’s start a container and attach a volume at the /scripts location of the container’s file system. Let’s also add the –detach parameter. This is going to start the container, start pwsh and then stop the container. Then I’m going to copy a script from my local file system into the container. The container does not need to be running for the copy operation to succeed.
Here’s the code to copy the script from my local file system into the container where pwsh-script is the container name and /scripts is the location we want to copy the script to inside the container. This is the volume we attached to the container. The script is a simple hello-world script.
With that, let’s go ahead and remove the container. We used it just to copy the script into the volume. I kind of feel bad, but we’ll keep moving on.
With that, let’s create a new container in interactive mode, with the volume attached. This will put us at a pwsh prompt.
Now, since our script is in the volume and we attached that volume when we created this new container, it’s available for us inside the container. Let’s go ahead and run that script inside the container and then delete the container with docker rm when it’s finished. 

Sounds Like…Serverless?

Now let’s take that technique we just stepped through, where we started the container, ran a script and deleted the container and combine all of that into one step. To do so, we’ll use the following command options for docker run. We specify the –rm option which will delete the container when it exits, add the /scripts volume and tell pwsh to run the script that’s in our volume by specifying its location with the parameter -F /scripts/Get-Containers.ps1.
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.
I hope you enjoyed this and are as excited as I am about how we can leverage this technology to solve new and unique problems in your data center and IT operations.