Workshop Definition¶
The Workshop custom resource defines a workshop.
The raw custom resource definition for the Workshop custom resource can be viewed at:
Workshop title and description¶
Each workshop is required to provide the title and description fields. If the fields are not supplied, the Workshop resource will be rejected when you attempt to load it into the Kubernetes cluster.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
files: github.com/eduk8s/lab-markdown-sample
The title field should be a single line value giving the subject of the workshop.
The description field should be a longer description of the workshop.
The following optional information can also be supplied for the workshop.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
url: https://github.com/eduk8s/lab-markdown-sample
difficulty: beginner
duration: 15m
vendor: eduk8s.io
authors:
- John Smith
tags:
- template
logo: data:image/png;base64,....
content:
files: github.com/eduk8s/lab-markdown-sample
The url field should be a URL you can go to for more information about the workshop.
The difficulty field should give an indication of who the workshop is targeting. The value must be one of beginner, intermediate, advanced and extreme.
The duration field gives the expected maximum amount of time the workshop would take to complete. This field only provides informational value and is not used to police how long a workshop instance will last. The format of the field is an integer number with s, m, or h suffix.
The vendor field should be a value which identifies the company or organisation which the authors are affiliated with. This could be a company or organisation name, or a DNS hostname under the control of whoever has created the workshop.
The authors field should list the people who worked on creating the workshop.
The tags field should list labels which help to identify what the workshop is about. This will be used in a searchable catalog of workshops.
The logo field should be a graphical image provided in embedded data URI format which depicts the topic of the workshop. The image should be 400 by 400 pixels. This will be used in a searchable catalog of workshops.
Note that when referring to a workshop definition after it has been loaded into a Kubernetes cluster, the value of name field given in the metadata is used. If you want to play around with slightly different variations of a workshop, copy the original workshop definition YAML file and change the value of name. Then make your changes and load it into the Kubernetes cluster.
Downloading workshop content¶
Workshop content can be downloaded at the time the workshop instance is created. Provided the amount of content is not too great, this shouldn’t affect startup times for the workshop instance. The alternative is to bundle the workshop content in a container image built from the eduk8s workshop base image.
To download workshop content at the time the workshop instance is started, set the content.files field to the location of the workshop content.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
files: github.com/eduk8s/lab-markdown-sample
The location can be either a GitHub repository reference, or a URL to a tarball hosted on a HTTP server.
In the case of a GitHub repository, do not prefix the location with https:// as this is a symbolic reference and not an actual URL.
The format of the reference to the GitHub repository is similar to that used with kustomize when referencing GitHub repositories. For example:
github.com/organisation/project- Use the workshop content hosted at the root of the Git repository. Themasterbranch is used.github.com/organisation/project/subdir?ref=develop- Use the workshop content hosted atsubdirof the Git repository. Thedevelopbranch is used.
In the case of a URL to a tarball hosted on a HTTP server, the workshop content is taken from the top level directory of the unpacked tarball. It is not possible to specify a subdirectory within the tarball. This means you cannot use a URL reference to refer to release tarballs which are automatically created by GitHub, as these place content in a subdirectory corresponding to the release name, branch or Git reference. For GitHub repositories, always use the GitHub repository reference instead.
In both cases for downloading workshop content, the workshop sub directory holding the actual workshop content, will be relocated to /opt/workshop so that it is not visible to a user. If you want other files ignored and not included in what the user can see, you can supply a .eduk8signore file in your repository or tarball and list patterns for the files in it.
Note that the contents of the .eduk8signore file is processed as a list of patterns and each will be applied recursively to subdirectories. To ensure that a file is only ignored if it resides in the root directory, you need to prefix it with ./.
./.dockerignore
./.gitignore
./Dockerfile
./LICENSE
./README.md
./kustomization.yaml
./resources
Container image for the workshop¶
When workshop content is bundled into a container image, the content.image field should specify the image reference identifying the location of the container image to be deployed for the workshop instance.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
image: quay.io/eduk8s/lab-markdown-sample:master
Even if using the ability to download workshop content when the workshop environment is started, you may still want to override the workshop image used as a base. This would be done where you have a custom workshop base image that includes additional language runtimes or tools required by specialised workshops.
For example, if running a Java workshop, you could specify the jdk11-environment workshop image, with workshop content still pulled down from GitHub.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-spring-testing
spec:
title: Spring Testing
description: Playground for testing Spring development
content:
image: quay.io/eduk8s/jdk11-environment:master
files: github.com/eduk8s-tests/lab-spring-testing
Where special custom workshop base images are available as part of the eduk8s project, instead of specifying the full location for the image, including the image registry, you can specify a short name. The eduk8s operator will then fill in the rest of the details.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-spring-testing
spec:
title: Spring Testing
description: Playground for testing Spring development
content:
image: jdk11-environment:*
files: github.com/eduk8s-tests/lab-spring-testing
The short versions of the names which are recognised are:
base-environment:*- A tagged version of thebase-environmentworkshop image which has been matched with the current version of the eduk8s operator.base-environment:develop- Thedevelopversion of thebase-environmentworkshop image.base-environment:master- Themasterversion of thebase-environmentworkshop image.jdk8-environment:*- A tagged version of thejdk8-environmentworkshop image which has been matched with the current version of the eduk8s operator.jdk8-environment:develop- Thedevelopversion of thejdk8-environmentworkshop image.jdk8-environment:master- Themasterversion of thejdk8-environmentworkshop image.jdk11-environment:*- A tagged version of thejdk11-environmentworkshop image which has been matched with the current version of the eduk8s operator.jdk11-environment:develop- Thedevelopversion of thejdk11-environmentworkshop image.jdk11-environment:master- Themasterversion of thejdk11-environmentworkshop image.conda-environment:*- A tagged version of theconda-environmentworkshop image which has been matched with the current version of the eduk8s operator.conda-environment:develop- Thedevelopversion of theconda-environmentworkshop image.conda-environment:master- Themasterversion of theconda-environmentworkshop image.
The * variants of the short names map to the most up to date version of the image which was available at the time that the version of the eduk8s operator was released. That version is thus guaranteed to work with that version of the eduk8s operator, where as develop and master versions may be newer, with possible incompatibilities. The develop and master versions principally exist to allow testing with newer versions.
Note that if required, the short names can be remapped in the SystemProfile configuration of the eduk8s operator. Additional short names can also be defined which map to your own custom workshop base images for use in your own deployment of the eduk8s operator, along with any workshop of your own.
Setting environment variables¶
If you want to set or override environment variables for the workshop instance, you can supply the session.env field.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
files: github.com/eduk8s/lab-markdown-sample
session:
env:
- name: REPOSITORY_URL
value: https://github.com/eduk8s/lab-markdown-sample
The session.env field should be a list of dictionaries with name and value fields.
Values of fields in the list of resource objects can reference a number of pre-defined parameters. The available parameters are:
session_id- A unique ID for the workshop instance within the workshop environment.session_namespace- The namespace created for and bound to the workshop instance. This is the namespace unique to the session and where a workshop can create their own resources.environment_name- The name of the workshop environment. For now this is the same as the name of the namespace for the workshop environment. Don’t rely on them being the same, and use the most appropriate to cope with any future change.workshop_namespace- The namespace for the workshop environment. This is the namespace where all deployments of the workshop instances are created, and where the service account that the workshop instance runs as exists.service_account- The name of the service account the workshop instance runs as, and which has access to the namespace created for that workshop instance.ingress_domain- The host domain under which hostnames can be created when creating ingress routes.ingress_protocol- The protocol (http/https) that is used for ingress routes which are created for workshops.
The syntax for referencing one of the parameters is $(parameter_name).
Note that the ability to override environment variables using this field should be limited to cases where they are required for the workshop. If you want to set or override an environment for a specific workshop environment, use the ability to set environment variables in the WorkshopEnvironment custom resource for the workshop environment instead.
Overriding the memory available¶
By default the container the workshop environment is running in is allocated 512Mi. If the editor is enabled a total of 1Gi is allocated.
Where the purpose of the workshop is mainly aimed at deploying workloads into the Kubernetes cluster, this would generally be sufficient. If you are running workloads in the workshop environment container itself and need more memory, the default can be overridden by setting memory under session.resources.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
image: quay.io/eduk8s/lab-markdown-sample:master
session:
resources:
memory: 2Gi
Mounting a persistent volume¶
In circumstances where a workshop needs persistent storage to ensure no loss of work if the workshop environment container were killed and restarted, you can request a persistent volume be mounted into the workshop container.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
image: quay.io/eduk8s/lab-markdown-sample:master
session:
resources:
storage: 5Gi
The persistent volume will be mounted on top of the /home/eduk8s directory. Because this would hide any workshop content bundled with the image, an init container is automatically configured and run, which will copy the contents of the home directory to the persistent volume, before the persistent volume is then mounted on top of the home directory.
Resource budget for namespaces¶
In conjunction with each workshop instance, a namespace will be created for use during the workshop. That is, from the terminal of the workshop dashboard applications can be deployed into the namespace via the Kubernetes REST API using tools such as kubectl.
By default this namespace will have whatever limit ranges and resource quota may be enforced by the Kubernetes cluster. In most case this will mean there are no limits or quotas. The exception is likely OpenShift, which through a project template can automatically apply limit ranges and quotas to new namespaces when created.
To control how much resources can be used where no limit ranges and resource quotas are set, or to override any default limit ranges and resource quota, you can set a resource budget for any namespaces created for the workshop instance.
To set the resource budget, set the session.namespaces.budget field.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
image: quay.io/eduk8s/lab-markdown-sample:master
session:
namespaces:
budget: small
The resource budget sizings and quotas for CPU and memory are:
| Budget | CPU | Memory |
|-----------|-------|--------|
| small | 1000m | 1Gi |
| medium | 2000m | 2Gi |
| large | 4000m | 4Gi |
| x-large | 8000m | 8Gi |
| xx-large | 8000m | 12Gi |
| xxx-large | 8000m | 16Gi |
A value of 1000m is equivalent to 1 CPU.
Separate resource quotas for CPU and memory are applied for terminating and non terminating workloads.
Only the CPU and memory quotas are listed above, but limits are also in place on the number of resource objects that can be created of certain types, including persistent volume claims, replication controllers, services and secrets.
For each budget type, a limit range is created with fixed defaults. The limit ranges for CPU usage on a container are as follows.
| Budget | Min | Max | Request | Limit |
|-----------|-----|-------|---------|-------|
| small | 50m | 1000m | 50m | 250m |
| medium | 50m | 2000m | 50m | 500m |
| large | 50m | 4000m | 50m | 500m |
| x-large | 50m | 8000m | 50m | 500m |
| xx-large | 50m | 8000m | 50m | 500m |
| xxx-large | 50m | 8000m | 50m | 500m |
Those for memory are:
| Budget | Min | Max | Request | Limit |
|-----------|------|------|---------|-------|
| small | 32Mi | 1Gi | 128Mi | 256Mi |
| medium | 32Mi | 2Gi | 128Mi | 512Mi |
| large | 32Mi | 4Gi | 128Mi | 1Gi |
| x-large | 32Mi | 8Gi | 128Mi | 2Gi |
| xx-large | 32Mi | 12Gi | 128Mi | 2Gi |
| xxx-large | 32Mi | 16Gi | 128Mi | 2Gi |
The request and limit values are the defaults applied to a container when no resources specification is given in a pod specification.
If a budget sizing for CPU and memory is sufficient, but you need to override the limit ranges and defaults for request and limit values when none is given in a pod specification, you can supply overrides in session.namespaces.limits.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-markdown-sample
spec:
title: Markdown Sample
description: A sample workshop using Markdown
content:
image: quay.io/eduk8s/lab-markdown-sample:master
session:
namespaces:
budget: medium
limits:
min:
cpu: 50m
memory: 32Mi
max:
cpu: 1
memory: 1Gi
defaultRequest:
cpu: 50m
memory: 128Mi
default:
cpu: 500m
memory: 1Gi
Although all possible properties that can be set are listed in this example, you only need to supply the property for the value you want to override.
If you need more control over limit ranges and resource quotas, you should set the resource budget to custom. This will remove any default limit ranges and resource quota which might be applied to the namespace. You can then specify your own LimitRange and ResourceQuota resources as part of the list of resources created for each session.
Before disabling the quota and limit ranges, or contemplating any switch to using a custom set of LimitRange and ResourceQuota resources, consider if that is what is really required. The default requests defined by these for memory and CPU are fallbacks only. In most cases instead of changing the defaults, you should specify memory and CPU resources in the pod template specification of your deployment resources used in the workshop, to indicate what the application actually requires. This will allow you to control exactly what the application is able to use and so fit into the minimum quota required for the task.
Note that this budget setting and the memory values are distinct from the amount of memory the container the workshop environment runs in. If you need to change how much memory is available to the workshop container, set the memory setting under session.resources.
Patching workshop deployment¶
In order to set or override environment variables you can provide session.env. If you need to make other changes to the pod template for the deployment used to create the workshop instance, you need to provide an overlay patch. Such a patch might be used to override the default CPU and memory limit applied to the workshop instance, or to mount a volume.
The patches are provided by setting session.patches. The patch will be applied to the spec field of the pod template.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-resource-testing
spec:
title: Resource testing
description: Play area for testing memory resources
content:
files: github.com/eduk8s-tests/lab-resource-testing
session:
patches:
containers:
- name: workshop
resources:
requests:
memory: "1Gi"
limits:
memory: "1Gi"
In this example the default memory limit of “512Mi” is increased to “1Gi”. Although memory is being set via a patch in this example, the session.resources.memory field is the preferred way to override the memory allocated to the container the workshop environment is running in.
The patch when applied works a bit differently to overlay patches as found elsewhere in Kubernetes. Specifically, when patching an array and the array contains a list of objects, a search is performed on the destination array and if an object already exists with the same value for the name field, the item in the source array will be overlaid on top of the existing item in the destination array. If there is no matching item in the destination array, the item in the source array will be added to the end of the destination array.
This means an array doesn’t outright replace an existing array, but a more intelligent merge is performed of elements in the array.
Creation of session resources¶
When a workshop instance is created, the deployment running the workshop dashboard is created in the namespace for the workshop environment. When more than one workshop instance is created under that workshop environment, all those deployments are in the same namespace.
For each workshop instance, a separate empty namespace is created with name corresponding to the workshop session. The workshop instance is configured so that the service account that the workshop instance runs under can access and create resources in the namespace created for that workshop instance. Each separate workshop instance has its own corresponding namespace and they can’t see the namespace for another instance.
If you want to pre-create additional resources within the namespace for a workshop instance, you can supply a list of the resources against the session.objects field within the workshop definition. You might use this to add additional custom roles to the service account for the workshop instance when working in that namespace, or to deploy a distinct instance of an application for just that workshop instance, such as a private image registry.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-registry-testing
spec:
title: Registry Testing
description: Play area for testing image registry
content:
files: github.com/eduk8s-tests/lab-registry-testing
session:
objects:
- apiVersion: apps/v1
kind: Deployment
metadata:
name: registry
spec:
replicas: 1
selector:
matchLabels:
deployment: registry
strategy:
type: Recreate
template:
metadata:
labels:
deployment: registry
spec:
containers:
- name: registry
image: registry.hub.docker.com/library/registry:2.6.1
imagePullPolicy: IfNotPresent
ports:
- containerPort: 5000
protocol: TCP
env:
- name: REGISTRY_STORAGE_DELETE_ENABLED
value: "true"
- apiVersion: v1
kind: Service
metadata:
name: registry
spec:
type: ClusterIP
ports:
- port: 80
targetPort: 5000
selector:
deployment: registry
Note that for namespaced resources, it is not necessary to specify the namespace field of the resource metadata. When the namespace field is not present the resource will automatically be created within the session namespace for that workshop instance.
When resources are created, owner references are added making the WorkshopSession custom resource corresponding to the workshop instance the owner. This means that when the workshop instance is deleted, any resources will be automatically deleted.
Values of fields in the list of resource objects can reference a number of pre-defined parameters. The available parameters are:
session_id- A unique ID for the workshop instance within the workshop environment.session_namespace- The namespace created for and bound to the workshop instance. This is the namespace unique to the session and where a workshop can create their own resources.environment_name- The name of the workshop environment. For now this is the same as the name of the namespace for the workshop environment. Don’t rely on them being the same, and use the most appropriate to cope with any future change.workshop_namespace- The namespace for the workshop environment. This is the namespace where all deployments of the workshop instances are created, and where the service account that the workshop instance runs as exists.service_account- The name of the service account the workshop instance runs as, and which has access to the namespace created for that workshop instance.ingress_domain- The host domain under which hostnames can be created when creating ingress routes.ingress_protocol- The protocol (http/https) that is used for ingress routes which are created for workshops.
The syntax for referencing one of the parameters is $(parameter_name).
In the case of cluster scoped resources, it is important that you set the name of the created resource so that it embeds the value of $(session_namespace). This way the resource name is unique to the workshop instance and you will not get a clash with a resource for a different workshop instance.
Note that due to shortcomings in the current official Python REST API client for Kubernetes, the way it creates resource objects from an arbitrary resource description means it will fail for custom resources. As a workaround until the Python REST API client is fixed, you need to flag custom resources, and indicate whether they have cluster scope or are namespaced. To do this add an annotation to the metadata for the resource with name training.eduk8s.io/objects.crd.scope and set it to either Cluster or Namespaced.
For examples of making use of the available parameters see the following sections.
Overriding default RBAC rules¶
By default the service account created for the workshop instance, has admin role access to the session namespace created for that workshop instance. This enables the service account to be used to deploy applications to the session namespace, as well as manage secrets and service accounts.
Where a workshop doesn’t require admin access for the namespace, you can reduce the level of access it has to edit or view by setting the session.namespaces.role field.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-role-testing
spec:
title: Role Testing
description: Play area for testing roles
content:
files: github.com/eduk8s-tests/lab-role-testing
session:
namespaces:
role: view
If you need to add additional roles to the service account, such as the ability to work with custom resource types which have been added to the cluster, you can add the appropriate Role and RoleBinding definitions to the session.objects field described previously.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-kpack-testing
spec:
title: Kpack Testing
description: Play area for testing kpack
content:
files: github.com/eduk8s-tests/lab-kpack-testing
session:
objects:
- apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: kpack-user
rules:
- apiGroups:
- build.pivotal.io
resources:
- builds
- builders
- images
- sourceresolvers
verbs:
- get
- list
- watch
- create
- delete
- patch
- update
- apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: kpack-user
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: kpack-user
subjects:
- kind: ServiceAccount
namespace: $(workshop_namespace)
name: $(service_account)
Because the subject of a RoleBinding needs to specify the service account name and namespace it is contained within, both of which are unknown in advance, references to parameters for the workshop namespace and service account for the workshop instance are used when defining the subject.
Adding additional resources via session.objects can also be used to grant cluster level roles, which would be necessary if you need to grant the service account cluster-admin role.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-admin-testing
spec:
title: Admin Testing
description: Play area for testing cluster admin
content:
files: github.com/eduk8s-tests/lab-admin-testing
session:
objects:
- apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: $(session_namespace)-cluster-admin
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: cluster-admin
subjects:
- kind: ServiceAccount
namespace: $(workshop_namespace)
name: $(service_account)
In this case the name of the cluster role binding resource embeds $(session_namespace) so that its name is unique to the workshop instance and doesn’t overlap with a binding for a different workshop instance.
Creating additional namespaces¶
For each workshop instance a primary session namespace is created, into which applications can be pre-deployed, or deployed as part of the workshop.
If you need more than one namespace per workshop instance, you can create secondary namespaces in a couple of ways.
If the secondary namespaces are to be created empty, you can list the details of the namespaces under the property session.namespaces.secondary.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-namespace-testing
spec:
title: Namespace Testing
description: Play area for testing namespaces
content:
files: github.com/eduk8s-tests/lab-namespace-testing
session:
namespaces:
role: admin
budget: medium
secondary:
- name: $(session_namespace)-apps
role: edit
budget: large
limits:
default:
memory: 512mi
When secondary namespaces are created, by default, the role, resource quotas and limit ranges will be set the same as the primary session namespace. Each namespace will though have a separate resource budget, it is not shared.
If required, you can override what role, budget and limits should be applied within the entry for the namespace.
If you also need to create resources in the namespaces you want to create, you may prefer creating the namespaces by adding an appropriate Namespace resource to session.objects, along with the definitions of the resources you want to create in the namespaces.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-namespace-testing
spec:
title: Namespace Testing
description: Play area for testing namespaces
content:
files: github.com/eduk8s-tests/lab-namespace-testing
session:
objects:
- apiVersion: v1
kind: Namespace
metadata:
name: $(session_namespace)-apps
When listing any other resources to be created within the additional namespace, such as deployments, ensure that the namespace is set in the metadata of the resource, e.g., $(session_namespace)-apps.
If you need to override what role the service account for the workshop instance has in the additional namespace, you can set the training.eduk8s.io/session.role annotation on the Namespace resource.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-namespace-testing
spec:
title: Namespace Testing
description: Play area for testing namespaces
content:
files: github.com/eduk8s-tests/lab-namespace-testing
session:
objects:
- apiVersion: v1
kind: Namespace
metadata:
name: $(session_namespace)-apps
annotations:
training.eduk8s.io/session.role: view
If you need to have a different resource budget set for the additional namespace, you can add the annotation training.eduk8s.io/session.budget in the Namespace resource metadata and set the value to the required resource budget.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-namespace-testing
spec:
title: Namespace Testing
description: Play area for testing namespaces
content:
files: github.com/eduk8s-tests/lab-namespace-testing
session:
objects:
- apiVersion: v1
kind: Namespace
metadata:
name: $(session_namespace)-apps
annotations:
training.eduk8s.io/session.budget: large
In order to override the limit range values applied corresponding to the budget applied, you can add annotations starting with training.eduk8s.io/session.limits. for each entry.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-namespace-testing
spec:
title: Namespace Testing
description: Play area for testing namespaces
content:
files: github.com/eduk8s-tests/lab-namespace-testing
session:
objects:
- apiVersion: v1
kind: Namespace
metadata:
name: $(session_namespace)-apps
annotations:
training.eduk8s.io/session.limits.min.cpu: 50m
training.eduk8s.io/session.limits.min.memory: 32Mi
training.eduk8s.io/session.limits.max.cpu: 1
training.eduk8s.io/session.limits.max.memory: 1Gi
training.eduk8s.io/session.limits.defaultrequest.cpu: 50m
training.eduk8s.io/session.limits.defaultrequest.memory: 128Mi
training.eduk8s.io/session.limits.request.cpu: 500m
training.eduk8s.io/session.limits.request.memory: 1Gi
You only need to supply annotations for the values you want to override.
If you need more fine grained control over the limit ranges and resource quotas, set the value of the annotation for the budget to custom and add the LimitRange and ResourceQuota definitions to session.objects.
In this case you must set the namespace for the LimitRange and ResourceQuota resource to the name of the namespace, e.g., $(session_namespace)-apps so they are only applied to that namespace.
Overriding pod security policy¶
The pod for the workshop session will be setup with a pod security policy which restricts what can be done from containers in the pod. The nature of the applied pod security policy will be adjusted when enabling support for doing docker builds to enable the ability to do docker builds inside the side car container attached to the workshop container.
If you are customising the workshop by patching the pod specification using session.patches, in order to add your own side car container, and that side car container needs a custom pod security policy which you define in environment.objects or session.objects, you will need to disable the application of the pod security policy done by the eduk8s operator. This can be done by setting session.security.policy to custom.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-policy-testing
spec:
title: Policy Testing
description: Play area for testing policy override
content:
files: github.com/eduk8s-tests/lab-policy-testing
session:
security:
policy: custom
objects:
- apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
namespace: $(workshop_namespace)
name: $(session_namespace)-podman
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: $(workshop_namespace)-podman
subjects:
- kind: ServiceAccount
namespace: $(workshop_namespace)
name: $(service_account)
environment:
objects:
- apiVersion: policy/v1beta1
kind: PodSecurityPolicy
metadata:
name: aa-$(workshop_namespace)-podman
spec:
privileged: true
allowPrivilegeEscalation: true
requiredDropCapabilities:
- KILL
- MKNOD
hostIPC: false
hostNetwork: false
hostPID: false
hostPorts: []
runAsUser:
rule: MustRunAsNonRoot
seLinux:
rule: RunAsAny
fsGroup:
rule: RunAsAny
supplementalGroups:
rule: RunAsAny
volumes:
- configMap
- downwardAPI
- emptyDir
- persistentVolumeClaim
- projected
- secret
- apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: $(workshop_namespace)-podman
rules:
- apiGroups:
- policy
resources:
- podsecuritypolicies
verbs:
- use
resourceNames:
- aa-$(workshop_namespace)-podman
By overriding the pod security policy you are responsible for limiting what can be done from the workshop pod. In other words, you should only add just the extra capabilities you need. The pod security policy will only be applied to the pod the workshop session runs in, it does not affect any pod security policy applied to service accounts which exist in the session namespace or other namespaces which have been created.
Note that due to a lack of a good way to deterministically determine priority of applied pod security policies when a default pod security policy has been applied globally by mapping it to the system:authenticated group, with priority instead falling back to ordering of the names of the pod security policies, it is recommend you use aa- as a prefix to the custom pod security name you create. This will ensure that it take precedence over any global default pod security policy such as restricted, pks-restricted or vmware-system-tmc-restricted, no matter what the name of the global policy default is called.
Defining additional ingress points¶
If running additional background applications, by default they are only accessible to other processes within the same container. In order for an application to be accessible to a user via their web browser, an ingress needs to be created mapping to the port for the application.
You can do this by supplying a list of the ingress points, and the internal container port they map to, by setting the session.ingresses field in the workshop definition.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
ingresses:
- name: application
port: 8080
The form of the hostname used in URL to access the service will be:
$(session_namespace)-application.$(ingress_domain)
Note that you should not use as the name, the name of any builtin dashboards, terminal, console, slides or editor. These are reserved for the corresponding builtin capabilities providing those features.
In addition to specifying ingresses for proxying to internal ports within the same pod, you can specify a host, protocol and port corresponding to a separate service running in the Kubernetes cluster.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
ingresses:
- name: application
protocol: http
host: service.namespace.svc.cluster.local
port: 8080
Variables providing information about the current session can be used within the host property if required.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
ingresses:
- name: application
protocol: http
host: service.$(session_namespace).svc.cluster.local
port: 8080
The available variables are:
session_namespace- The namespace created for and bound to the workshop instance. This is the namespace unique to the session and where a workshop can create their own resources.environment_name- The name of the workshop environment. For now this is the same as the name of the namespace for the workshop environment. Don’t rely on them being the same, and use the most appropriate to cope with any future change.workshop_namespace- The namespace for the workshop environment. This is the namespace where all deployments of the workshop instances are created, and where the service account that the workshop instance runs as exists.ingress_domain- The host domain under which hostnames can be created when creating ingress routes.
If the service uses standard http or https ports, you can leave out the port property and the port will be set based on the value of protocol.
When a request is being proxied, you can specify additional request headers that should be passed to the service.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
ingresses:
- name: application
protocol: http
host: service.$(session_namespace).svc.cluster.local
port: 8080
headers:
- name: Authorization
value: "Bearer $(kubernetes_token)"
The value of a header can reference the following variables.
kubernetes_token- The access token of the service account for the current workshop session, used for accessing the Kubernetes REST API.
Accessing any service via the ingress will be protected by any access controls enforced by the workshop environment or training portal. If the training portal is used this should be transparent, otherwise you will need to supply any login credentials for the workshop again when prompted by your web browser.
Disabling the workshop content¶
The aim of the workshop environment is to provide content for a workshop which users can follow. If you want instead to use the workshop environment as a development environment, or use it as an admistration console which provides access to a Kubernetes cluster, you can disable the display of any workshop content. In this case only the workarea with the terminals, console etc, will be displayed. To disable display of workshop content, add a session.applications.workshop section and set the enabled property to false.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
workshop:
enabled: false
Enabling the Kubernetes console¶
By default the Kubernetes console is not enabled. If you want to enable it and make it available through the web browser when accessing a workshop, you need to add a session.applications.console section to the workshop definition, and set the enabled property to true.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
console:
enabled: true
The Kubernetes dashboard provided by the Kubernetes project will be used. If you would rather use Octant as the console, you can set the vendor property to octant.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
console:
enabled: true
vendor: octant
When vendor is not set, kubernetes is assumed.
If a workshop is designed such that it can only be run on OpenShift, and you wish to use the OpenShift web console, you can set vendor to openshift.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
console:
enabled: true
vendor: openshift
In just the case of the OpenShift web console, if you need to override the default version of the OpenShift web console used, you can set the openshift.version sub property.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
console:
enabled: true
vendor: openshift
openshift:
version: "4.3"
Ensure that you add quotes around the version number so that it is interpreted as a string.
The source of the container image for the OpenShift web console will be quay.io/openshift/origin-console. If you want to use a container image for the OpenShift web console which is hosted elsewhere, you can set the openshift.image sub property.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
console:
enabled: true
vendor: openshift
openshift:
image: quay.io/openshift/origin-console:4.3
Note that the OpenShift web console will not be fully functional if deployed to a Kubernetes cluster other than OpenShift as it is dependent on resource types only found in OpenShift.
Even on OpenShift, the web console may not be fully functional due to the restrictive RBAC in place for a workshop session. This is because the OpenShift web console is usually deployed global to the cluster and with elevated role access. You may be able to unlock some extra capabilities of the OpenShift web console if you can identify any additional roles that need to be granted to the service account used by the workshop environment, and enable access by adding appropriate Role or RoleBinding resources to the workshop definition.
Enabling the integrated editor¶
By default the integrated web based editor is not enabled. If you want to enable it and make it available through the web browser when accessing a workshop, you need to add a session.applications.editor section to the workshop definition, and set the enabled property to true.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
editor:
enabled: true
The integrated editor which is used is based on VS Code. Details of the editor can be found at:
If you need to install additional VS Code extensions, this can be done from the editor. Alternatively, if building a custom workshop, you can install them from your Dockerfile into your workshop image by running:
code-server --install-extension vendor.extension
Replace vendor.extension with the name of the extension, where the name identifies the extension on the VS Code extensions marketplace used by the editor, or provide a path name to a local .vsix file.
This will install the extensions into $HOME/.config/code-server/extensions.
If downloading extensions yourself and unpacking them, or you have them as part of your Git repository, you can instead locate them in the workshop/code-server/extensions directory.
Enabling session image registry¶
Workshops using tools such as kpack or tekton and which need a place to push container images when built, can enable an image registry. A separate image registry is deployed for each workshop session.
Note that the image registry is only currently fully usable if workshops are deployed under an eduk8s operator configuration which uses secure ingress. This is because an insecure registry would not be trusted by the Kubernetes cluster as the source of container images when doing deployments.
To enable the deployment of an image registry per workshop session you need to add a session.applications.registry section to the workshop definition, and set the enabled property to true.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
registry:
enabled: true
The image registry will mount a persistent volume for storing of images. By default the size of that persistent volume is 5Gi. If you need to override the size of the persistent volume add the storage property under the registry section.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
registry:
enabled: true
storage: 20Gi
The amount of memory provided to the image registry will default to 768Mi. If you need to increase this, add the memory property under the registry section.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
registry:
enabled: true
memory: 1Gi
The image registry will be secured with a username and password unique to the workshop session and expects access over a secure connection.
To allow access from the workshop session, the file $HOME/.docker/config.json containing the registry credentials will be injected into the workshop session. This will be automatically used by tools such as docker.
For deployments in Kubernetes, a secret of type kubernetes.io/dockerconfigjson is created in the namespace and automatically applied to the default service account in the namespace. This means deployments made using the default service account will be able to pull images from the image registry without additional configuration. If creating deployments using other service accounts, you will need to add configuration to the service account or deployment to add the registry secret for pulling images.
If you need access to the raw registry host details and credentials, they are provided as environment variables in the workshop session. The environment variables are:
REGISTRY_HOST- Contains the host name for the image registry for the workshop session.REGISTRY_AUTH_FILE- Contains the location of thedockerconfiguration file. Should always be the equivalent of$HOME/.docker/config.json.REGISTRY_USERNAME- Contains the username for accessing the image registry.REGISTRY_PASSWORD- Contains the password for accessing the image registry. This will be different for each workshop session.REGISTRY_SECRET- Contains the name of a Kubernetes secret of typekubernetes.io/dockerconfigjsonadded to the session namespace and which contains the registry credentials.
The URL for accessing the image registry adopts the HTTP protocol scheme inherited from the environment variable INGRESS_PROTOCOL. This would be the same HTTP protocol scheme as the workshop sessions themselves use.
If you want to use any of the variables as data variables in workshop content, use the same variable name but in lower case. Thus, registry_host, registry_auth_file, registry_username, registry_password and registry_secret.
Enabling ability to use docker¶
If you need to be able to build container images in a workshop using docker, it needs to be enabled first. Each workshop session will be provided with its own separate docker daemon instance running in a container.
Note that enabling of support for running docker requires the use of a privileged container for running the docker daemon. Because of the security implications of providing access to docker with this configuration, it is strongly recommended that if you don’t trust the people doing the workshop, any workshops which require docker only be hosted in a disposable Kubernetes cluster which is destroyed at the completion of the workshop. You should never enable docker for workshops hosted on a public service which is always kept running and where arbitrary users could access the workshops.
To enable support for being able to use docker add a session.applications.docker section to the workshop definition, and set the enabled property to true.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
docker:
enabled: true
The container which runs the docker daemon will mount a persistent volume for storing of images which are pulled down or built locally. By default the size of that persistent volume is 5Gi. If you need to override the size of the persistent volume add the storage property under the docker section.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
docker:
enabled: true
storage: 20Gi
The amount of memory provided to the container running the docker daemon will default to 768Mi. If you need to increase this, add the memory property under the registry section.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
docker:
enabled: true
memory: 1Gi
Access to the docker daemon from the workshop session uses a local UNIX socket shared with the container running the docker daemon. If using a local tool which wants to access the socket connection for the docker daemon directly rather than by running docker, it should use the DOCKER_HOST environment variable to determine the location of the socket.
The docker daemon is only available from within the workshop session and cannot be accessed outside of the pod by any tools deployed separately to Kubernetes.
Enabling WebDAV access to files¶
Local files within the workshop session can be accessed or updated from the terminal command line or editor of the workshop dashboard. The local files reside in the filesystem of the container the workshop session is running in.
If there is a need to be able to access the files remotely, it is possible to enable WebDAV support for the workshop session.
To enable support for being able to access files over WebDAV add a session.applications.webdav section to the workshop definition, and set the enabled property to true.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
webdav:
enabled: true
The result of this will be that a WebDAV server will be run within the workshop session environment. A set of credentials will also be automatically generated which are available as environment variables. The environment variables are:
WEBDAV_USERNAME- Contains the username which needs to be used when authenticating over WebDAV.WEBDAV_PASSWORD- Contains the password which needs to be used authenticating over WebDAV.
If you need to use any of the environment variables related to the image registry as data variables in workshop content, you will need to declare this in the workshop/modules.yaml file in the config.vars section.
config:
vars:
- name: WEBDAV_USERNAME
- name: WEBDAV_PASSWORD
The URL endpoint for accessing the WebDAV server is the same as the workshop session, with /webdav/ path added. This can be constructed from the terminal using:
$INGRESS_PROTOCOL://$SESSION_NAMESPACE.$INGRESS_DOMAIN/webdav/
In workshop content it can be constructed using:
{{ingress_protocol}}://{{session_namespace}}.{{ingress_domain}}/webdav/
You should be able to use WebDAV client support provided by your operating system, of by using a standalone WebDAV client such as CyberDuck.
Using WebDAV can make it easier if you need to transfer files to or from the workshop session.
Customizing the terminal layout¶
By default a single terminal is provided in the web browser when accessing the workshop. If required, you can enable alternate layouts which provide additional terminals. To set the layout, you need to add the session.applications.terminal section and include the layout property with the desired layout.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
applications:
terminal:
enabled: true
layout: split
The options for the layout property are:
default- Single terminal.split- Two terminals stacked above each other in ratio 60/40.split/2- Three terminals stacked above each other in ratio 50/25/25.lower- A single terminal is placed below any dashboard tabs, rather than being a tab of its own. The ratio of dashboard tab to terminal is 70/30.none- No terminal is displayed, but they can still be created from the drop down menu.
When adding the terminal section, you must include the enabled property and set it to true as it is a required field when including the section.
If you didn’t want a terminal displayed, and also wanted to disable the ability to create terminals from the drop down menu, set enabled to false.
Adding custom dashboard tabs¶
Exposed applications, external sites and additional terminals, can be given their own custom dashboard tab. This is done by specifying the list of dashboard panels and the target URL.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
ingresses:
- name: application
port: 8080
dashboards:
- name: Internal
url: "$(ingress_protocol)://$(session_namespace)-application.$(ingress_domain)/"
- name: External
url: http://www.example.com
The URL values can reference a number of pre-defined parameters. The available parameters are:
session_namespace- The namespace created for and bound to the workshop instance. This is the namespace unique to the session and where a workshop can create their own resources.environment_name- The name of the workshop environment. For now this is the same as the name of the namespace for the workshop environment. Don’t rely on them being the same, and use the most appropriate to cope with any future change.workshop_namespace- The namespace for the workshop environment. This is the namespace where all deployments of the workshop instances are created, and where the service account that the workshop instance runs as exists.ingress_domain- The host domain under which hostnames can be created when creating ingress routes.ingress_protocol- The protocol (http/https) that is used for ingress routes which are created for workshops.
The URL can reference an external web site, however, that web site must not prohibit being embedded in a HTML iframe.
In the case of wanting to have a custom dashboard tab provide an additional terminal, the url property should use the form terminal:<session>, where <session> is replaced with the name of the terminal session. The name of the terminal session can be any name you choose, but should be restricted to lower case letters, numbers and ‘-‘. You should avoid using numeric terminal session names such as “1”, “2” and “3” as these are use for the default terminal sessions.
apiVersion: training.eduk8s.io/v1alpha2
kind: Workshop
metadata:
name: lab-application-testing
spec:
title: Application Testing
description: Play area for testing my application
content:
image: quay.io/eduk8s-tests/lab-application-testing:master
session:
dashboards:
- name: Example
url: terminal:example