Tag: Docker

Running a Multi-Node Kubernetes Cluster on Windows with Kind

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There are lots of ways to run Kubernetes on your Windows development machine, for example minikube. Even Docker Desktop for Windows now ships with the ability to run a single node Kubernetes cluster, but the simplest and most flexible way I’ve found to run a multi-node Kubernetes cluster locally on Windows is using Kind or Kubernetes in Docker.

Note

All commands should be run from an elevated (administrator) powershell or command prompt
Also, commands listed are for powershell. If using a command prompt you may need to make the appropriate modifications to the paths etc.

Prerequisites

In order to run Kind locally you’ll need to have or install Docker Desktop for Windows (you’re going to be running the nodes of your cluster in docker containers), kubectl (the Kubernetes command line utility), and of course kind. The easiest way to install them is using the Chocolatey package manager. (Strictly speaking you don’t have to have kubectl to set up a kind cluster, but it will make the cluster far more useful once you have it up and running! 🙂 )

choco install docker-desktop
choco install kubernetes-cli
choco install kind

If you would prefer not to use chocolatey, please see the installation documentation for each component

Creating Your First Cluster

Once everything is installed you’re ready to create your first cluster. 

kind create cluster

Note this will download a decent sized docker image to run your node(s) and may take a couple of minutes if you have a slower connection, but you should only have to do it once for each version of Kubernetes that you run as the image will be cached by Docker.

This gives us a single node cluster running the latest version of Kubernetes (at the time of this writing that’s 1.20). It also gives our cluster the default name of kind. You can control the version of Kubernetes by specifying the image to use for your nodes using the –image switch on your create cluster command.

kind create cluster --image=kindest/node:v1.19.7@sha256:a70639454e97a4b733f9d9b67e12c01f6b0297449d5b9cbbef87473458e26dca

You can get a list of the images available for a particular kind release on the Kind GitHub Releases page. For example the current release of Kind (0.10.0) supports the following images:

1.20: 
kindest/node:v1.20.2@sha256:8f7ea6e7642c0da54f04a7ee10431549c0257315b3a634f6ef2fecaaedb19bab
1.19: 
kindest/node:v1.19.7@sha256:a70639454e97a4b733f9d9b67e12c01f6b0297449d5b9cbbef87473458e26dca
1.18: 
kindest/node:v1.18.15@sha256:5c1b980c4d0e0e8e7eb9f36f7df525d079a96169c8a8f20d8bd108c0d0889cc4
1.17: 
kindest/node:v1.17.17@sha256:7b6369d27eee99c7a85c48ffd60e11412dc3f373658bc59b7f4d530b7056823e
1.16: 
kindest/node:v1.16.15@sha256:c10a63a5bda231c0a379bf91aebf8ad3c79146daca59db816fb963f731852a99
1.15: 
kindest/node:v1.15.12@sha256:67181f94f0b3072fb56509107b380e38c55e23bf60e6f052fbd8052d26052fb5
1.14: 
kindest/node:v1.14.10@sha256:3fbed72bcac108055e46e7b4091eb6858ad628ec51bf693c21f5ec34578f6180

You can also set the name of your cluster using the –name switch

kind create cluster --name my-cluster

Removing your Cluster

Eventually you will want to delete/remove/destroy your cluster and reclaim the resources it is using. You can easily accomplish this using the kind delete command.

kind delete --name my-cluster

Going to Multiple-Nodes

So initially I said that we could set up a multi-node cluster using kind, but so far all of our clusters have been a single node. In order to get a multi-node cluster we’ll need to create a configuration file. Here’s a simple example that creates a 3 node cluster (1 control plane node and 2 worker nodes)

# three node (two workers) cluster config
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
- role: worker
- role: worker

We can apply our config file by using the –config switch with our create cluster command as follows

kind create cluster --name my-cluster --config .\my-cluster-config.yaml

And there we have it, a multi-node Kubernetes cluster running on your Windows desktop. Kind makes it pretty quick and simple so you can spin one up, play with it while doing some training or deploy test workloads locally to test your entire system locally. Once your done, or you mess things up, delete the cluster and spin up a new one when you need it.

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Adjusting Resources for Docker Desktop for Windows from PowerShell

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Last week I was searching high and low for documentation of any kind on how to script a change in memory allocated to Docker Desktop for Windows. Unable to find anything online, and failing in all my attempts to piece together a way to make it happen, I opened an issue on GitHub and asked for advice. The fine folks in the Docker Desktop for Windows community on GitHub jumped in quickly to assist (Thank you again!). The suggestion was to change the Docker Desktop settings file directly. From that I was able to put together a process that works.

First we need to stop the docker services, there are two of them: com.docker.service and docker. To stop those is pretty straight forward.

Stop-Service com.docker.service
Stop-Service docker

or shorter:

Stop-Service *docker*

Next we’ll need to read the settings file which is located @ ~\AppData\Roaming\Docker\settings.json. We’ll want to use the $env:APPDATA variable to get the actual path to the ~\AppData\Roaming folder on the current system for the current user, and we’ll pipe the file contents to ConvertFrom-Json to give us a nice object to work with.

$path = "$env:APPDATA\Docker\settings.json"
$settings = Get-Content $path | ConvertFrom-Json

Now we can easily change the memory value by manipulating the memoryMIB property of our settings object.

$settings.memoryMiB = 4096

Then we can save the file again by piping our settings object to ConvertTo-Json and then to Set-Content.

$settings | ConvertTo-Json | Set-Content $path

Now we just need to restart the docker services.

Start-Service *docker*

There’s one last crucial step. It turns out we need to give the Docker daemon a little nudge to get things responding to our docker commands again. According to this article on stack-overflow we do that using:

& $Env:ProgramFiles\Docker\Docker\DockerCli.exe -SwitchDaemon
& $Env:ProgramFiles\Docker\Docker\DockerCli.exe -SwitchDaemon

Yes, twice. I later derived by looking at the DockerCli help that I could just use:

&$Env:ProgramFiles\Docker\Docker\DockerCli.exe -SwitchLinuxEngine

(I’m running Linux containers. If you are running Windows containers use -SwitchWindowsEngine instead.)

So here is the whole thing all in one go.

Stop-Service *docker*
$path = "$env:APPDATA\Docker\settings.json"
$settings = Get-Content $path | ConvertFrom-Json
$settings.memoryMiB = 4096
$settings | ConvertTo-Json | Set-Content $path
Start-Service *docker*        
&$Env:ProgramFiles\Docker\Docker\DockerCli.exe -SwitchLinuxEngine

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Running PostgreSql in a Container on Windows 10

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Today at work we were setting up a development environment for a .Net Core project using PostgreSql as it’s datastore. We decided that we set up the database server running in a container in the same way I have been running SQL Server (See recent article: Running Microsoft SQL Server in a Container on Windows 10) for the local development environment. Using the docker-compose file from this article as a basis and referring to the documentation for the postgres docker image on Docker Hub we put together a docker-compose file for PostgreSQL that looked similar to this:

version: "3"
services:
  postgres:
    image: "postgres"
    ports:
      - 5432:5432
    environment:
      POSTGRES_USER: "MyUser"
      POSTGRES_PASSWORD: "Password!23"
      POSTGRES_DB: "example"
    volumes: 
      - C:\Docker\PostgreSql\data:/var/lib/postgresql/data

Upon running docker-compose we were greeted with the following output containing an error message:

Creating postgresql_postgres_1 ... done
Attaching to postgresql_postgres_1
postgres_1  | The files belonging to this database system will be owned by user "postgres".
postgres_1  | This user must also own the server process.
postgres_1  |
postgres_1  | The database cluster will be initialized with locale "en_US.utf8".
postgres_1  | The default database encoding has accordingly been set to "UTF8".
postgres_1  | The default text search configuration will be set to "english".
postgres_1  |
postgres_1  | Data page checksums are disabled.
postgres_1  |
postgres_1  | fixing permissions on existing directory /var/lib/postgresql/data ... ok
postgres_1  | creating subdirectories ... ok
postgres_1  | selecting dynamic shared memory implementation ... posix
postgres_1  | selecting default max_connections ... 20
postgres_1  | selecting default shared_buffers ... 400kB
postgres_1  | selecting default time zone ... Etc/UTC
postgres_1  | creating configuration files ... ok
postgres_1  | running bootstrap script ... 2020-02-25 02:38:12.326 UTC [80] FATAL:  data directory "/var/lib/postgresql/data" has wrong ownership
postgres_1  | 2020-02-25 02:38:12.326 UTC [80] HINT:  The server must be started by the user that owns the data directory.
postgres_1  | child process exited with exit code 1
postgres_1  | initdb: removing contents of data directory "/var/lib/postgresql/data"
postgresql_postgres_1 exited with code 1

Notice line 19: “FATAL: data directory “/var/lib/postgresql/data” has wrong ownership”. After reading the error message we noted on line 12 it reads “fixing permissions on existing directory /var/lib/postgresql/data … ok”. Also near the top of the output on line 3 it reads “The files belonging to this database system will be owned by user “postgres”.” followed by “This user must also own the server process.”. Interesting…

So after digging around a bit we found that indeed the user “postgres” must own the files in order for the db system to read them and that the container starts up as root. It appears that line 12 is trying to fix the issue, and from what we found online it will… If the data directory is on a Linux file system. Since we are attempting to mount these files from a Windows file system, it appears that “fixing the permissions” fails. No major surprise there. So what is the work around for us poor developers working on Windows machines?

Named Volumes to the Rescue

In order to get this to work we set up a named volume. In this scenario, Docker takes care of handling the files and where they are actually stored, so we don’t readily have access to the files, but we don’t really care all that much. We just want our data to persist and not get blown away when the container gets deleted.

Here is the new (working) docker-compose file with the named volume:

version: "3"
services:
  postgres:
    image: "postgres"
    ports:
      - 5432:5432
    environment:
      POSTGRES_USER: "MyUser"
      POSTGRES_PASSWORD: "Password!23"
      POSTGRES_DB: "example"
    volumes: 
      - psql:/var/lib/postgresql/data

volumes:
  psql:

Using this approach you may want to keep an eye on the named volumes on your system and clean them up when you are no longer using them. To get a list of the volumes on your machine use the following command:

docker volumes ls

That will dump out a list of volumes on your machine that looks something like:

DRIVER              VOLUME NAME
local               600de9fcef37a60b93c410f9e7db6b4b7f9966faf5f6ba067cc6cb55ee851198
local               ae45bfac51d4fb1813bd747cc9af10b7d141cf3affa26d79f46f405ebfa07462
local               b94806ba697f79c7003481f8fd1d65599e532c0e2223800b39a2f90b087d5127
local               d02adf9ab33dfa22e154d25e13c5bb383a5969c19c1dd98cfa2ac8e560d87eb4
local               postgresql_psql

Notice the last entry named “postgresql_psql”? That is the one we just created above. To remove it use the following command (Note: It will not allow you to remove the volume if it is referenced by a container, running or not, so you’ll want to stop and remove the container first):

docker volume rm postgresql_psql

Running Microsoft SQL Server in a Container on Windows 10

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Why you may ask? SQL Server runs just fine on Windows 10, but there are a few advantages to running SQL Server in a container rather than installing it on your machine. The biggest advantage is that you can throw it away at any time, for any reason (like a new version has shipped) and leave your machine pristine and fully functional. If you have ever tried to uninstall SQL Server from your machine you’ll definitely appreciate that. Also it is faster to get up and running than a full install of SQL Server (Assuming you already have Docker Desktop and Docker Compose installed, which I do) .

In the modern world of microservice development I find that over time I end up with all sorts of dependencies installed on my machine for various projects. One project may be using SQL Server, the next MongoDB and the next PostgreSQL. And then there is Redis, RabbitMQ, the list goes on and on… Running these dependencies in containers just makes it quick and easy to switch between projects and not have all of these dependencies cluttering up my machine.

As I mentioned this approach does assume you have Docker Desktop installed, and I prefer to also use docker compose as well just to simplify starting things up and shutting them down when I need to. If you don’t already have these tools installed you can get them at Docker Hub, or by using Chocolatey (The Windows installer for Docker Desktop will install both for you.)

choco install docker-desktop

Getting Started

It’s pretty simple to get an instance of SQL Server running in a container, you’ll find all the basic information to get started on the DockerHub Microsoft SQL Server listing. To start up the latest version of SQL Server 2017 use the following command from your command shell. 

docker run -e "ACCEPT_EULA=Y" -e "SA_PASSWORD=Password#1" -p 4133:1433 -d mcr.microsoft.com/mssql/server:2017-latest

Note: I’m running the commands in PowerShell which requires double quotes. If you run them using the command prompt use single quotes.

The -e arguments set environment variables inside the container that are picked up by SQL Server when it runs.
ACCEPT_EULA=Y accepts the Microsoft SQL Server EULA
SA_PASSWORD set the sa account password (You might want to choose a better password!)

-p maps the ports your-machine:container. If you want to map 1433 (the standard SQL Server port) to itself on your machine use -p 1433:1433, in my examples I’ll be mapping to 4133 on my machine as above.

-d runs the container detached, returning the container id and releasing your shell prompt for you to use. If you omit this standard out will be dumped to your shell as long as the container is running.

mcr.microsoft.com/mssql/server:2017-latest specifies the image to run (and pull if you don’t already have it) The :2017-latest is the tag and means to pull the latest tagged version of the image. You can specify a specific version if you so choose.

So if we run the command above (and we haven’t previously run it) Docker will go out and pull the image and start it up. It will likely take 30 seconds to a few minutes to download the image, but once it is completed you should see something like the following in your shell.

❯ docker run -e "ACCEPT_EULA=Y" -e "SA_PASSWORD=Password#1" -p 4133:1433 -d mcr.microsoft.com/mssql/server:2017-latest
Unable to find image 'mcr.microsoft.com/mssql/server:2017-latest' locally
2017-latest: Pulling from mssql/server
59ab41dd721a: Pull complete
57da90bec92c: Pull complete
06fe57530625: Pull complete
5a6315cba1ff: Pull complete
739f58768b3f: Pull complete
3a58fde0fc61: Pull complete
89b44069090d: Pull complete
93c7ccf94626: Pull complete
0ef1127ca8c9: Pull complete
Digest: sha256:f53d3a54923280133eb73d3b5964527a60348013d12f07b490c99937fde3a536
Status: Downloaded newer image for mcr.microsoft.com/mssql/server:2017-latest
bcb2d2585339b3f7fd1a2fdeafff202359ce563213801949a4c55f954e5beb11
❯

At this point you should have a shiny new instance of SQL Server 2017 up and running. You can see the running container by executing

docker ps

This will list out all of the running containers on your machine.

Note the Container ID and Name, you can use these to reference the container with subsequent Docker commands. At this point you can connect to your database server from your application or SQL Server Management Studio. With the command above the connection string to connect would be: “Server=localhost,4133;Database=master;User Id=sa; Password=Password#1”.

To stop the instance:

docker stop bcb

Above I used a shortened/abbreviated version of the container id, you can do this if it uniquely identifies the container. If I had 2 containers that started with this string I would need to use the full id (or at least more of it) or the name.

I can start it up again using:

docker run bcb

And I can permanently delete the instance using:

docker stop bcb
docker rm bcb

If you need to see the containers you have that are not currently running (ie. you stopped, but did not remove them) use:

docker ps -a

Making Things a Bit More Usable

All this is awesome, but you’ll soon run into a couple of issues:

  • You’ll grow tired of typing in all the long command, remembering all the correct switches etc, and listing out the containers to get the ids to manage them.
  • Once you delete your containers you’ll lose your databases! That’s right, the database files are stored in the container, so once you delete the container it’s gone.

Let’s start by solving the second problem first, which will make the first problem worse :(, then we’ll circle back to solve the first problem.

Mapping Your Data Files to Your Local Machine

Step one: You’ll need to share a drive in Docker. To do this:

  • Right click on the Docker Desktop Icon in your system tray and select “Settings”.
  • Select the “Resources” item and then “File Sharing”.
  • Select a drive to share and click “Apply & Share”

Step two: Create a folder in your shared drive to map into your container. In my case I’ve shared my x: drive so I’ve created a folder X:\DockerVolumes\SqlData\Sample

Step three: Now we are ready to modify our run command to map the shared (empty) folder into our container’s data directory. (I would avoid spaces in the path to your shared volumes directory, as I recall it make things “fun”.)

docker run -e "ACCEPT_EULA=Y" -e "SA_PASSWORD=Password#1" -p 4133:1433 -v X:\DockerVolumes\SqlData\Sample:/var/opt/mssql/data -d mcr.microsoft.com/mssql/server:2017-latest

Assuming everything works as expected, you should now have all of your system databases in your shared directory. Now they will persist even if you destroy the container and spin up a new one.

Directory: X:\DockerVolumes\SqlData\Sample


Mode                LastWriteTime         Length Name
----                -------------         ------ ----
-a----       2020-01-29  10:07 PM        4194304 master.mdf
-a----       2020-01-29  10:07 PM        2097152 mastlog.ldf
-a----       2020-01-29  10:07 PM        8388608 model.mdf
-a----       2020-01-29  10:07 PM        8388608 modellog.ldf
-a----       2020-01-29  10:07 PM       14024704 msdbdata.mdf
-a----       2020-01-29  10:07 PM         524288 msdblog.ldf
-a----       2020-01-29  10:07 PM        8388608 tempdb.mdf
-a----       2020-01-29  10:07 PM        8388608 templog.ldf

If they do not show up, try stopping the container and restarting it without the -d switch and read through the output in your terminal, it will usually give you a clue as to your problem.

Cleaning It All Up with Docker Compose

All that is great but, typing out – docker run -e “ACCEPT_EULA=Y” -e “SA_PASSWORD=Password#1” -p 4133:1433 -v X:\DockerVolumes\SqlData\Sample:/var/opt/mssql/data -d mcr.microsoft.com/mssql/server:2017-latest – every time you want to start SQL Server is a bit annoying and error prone. To solve this we’ll put all these arguments into a docker-compose file and make things much easier.

To organize things I create a folder on my drive to contain my docker-compose files, each file in it’s own sub folder. ex: C:\Docker\Sample would contain 1 docker-compose.yml file that defines my configuration for SQL Server 2017. Here is an example file for the docker run we ran above:

version: "3"
services:
  default-sql:
    image: "mcr.microsoft.com/mssql/server:2017-latest"
    ports:
      - 4133:1433
    environment:
      SA_PASSWORD: "Password#1"
      ACCEPT_EULA: "Y"
    volumes:
      - X:\DockerVolumes\SqlData\Sample:/var/opt/mssql/data

Most of this should look pretty familiar, it’s just a YAML representation of the arguments we’ve been specifying above.

If we navigate to the folder containing our docker-compose file, in my case C:\Docker\Sample\ we can simply run:

docker-compose up -d

Once again the -d switch is to run the container detached. You can omit it an see what is happening inside your container. After a few seconds our server will be up and running. When we are done with our container we can run:

docker-compose down

Now everything should be spun down. If you’re really lazy like me you can create an alias for docker-compose in your PowerShell profile so you can just use:

dc up -d
dc down

Final Thoughts

You’ll want to keep an eye on the containers you have that are sitting around in a stopped state by using “docker ps -a” and cleaning up the old containers by using “docker rm CONTAINERID” to remove them. You’ll also want to keep an eye on the images you have cached and periodically clean them up as well. You can list them with “docker images” and remove them with “docker rmi IMAGEID“. (rmi=remove image) These images can be pretty good size (the current SQL 2017 image is 1.4GB).

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