Unified Application Distribution with Kurator
In this guide, we will introduce how to use Kurator to distribute applications uniformly with Fleet.
Architecture
Kurator offers a unified system for distributing applications across multiple clusters, powered by Fleet.
By making use of the GitOps approach through FluxCD, Kurator automates the process of syncing and deploying applications. This makes the entire procedure quicker and more precise
Built to be flexible and responsive, Kurator’s distribution system is specially designed to accommodate various business and cluster demands.
The overall architecture is shown as below:
Prerequisites
Setup Fleet manager by following the instructions in the installation guide.
Create an example application
The following example uses two locally attachedClusters for testing. For more details about attachedCluster, refer to the manage attachedCluster page.
After the Kind cluster is ready, you can check the original status of the cluster for comparison with the following example.
# Replace `/root/.kube/kurator-member1.config` with the actual path of your cluster's kubeconfig file.
kubectl get po -A --kubeconfig=/root/.kube/kurator-member1.config
Apply pre-prepared attachedClusters and fleet with the following command:
$ kubectl apply -f examples/application/common/
attachedcluster.cluster.kurator.dev/kurator-member1 created
attachedcluster.cluster.kurator.dev/kurator-member2 created
fleet.fleet.kurator.dev/quickstart created
Apply example application with the following command:
$ kubectl apply -f examples/application/gitrepo-kustomization-demo.yaml
application.apps.kurator.dev/gitrepo-kustomization-demo created
Here is the content of example application resource.
The YAML configuration of the example application outlines its source, synchronization policy, and other key settings.
This includes the gitRepository
as its source and two kustomization
syncPolicies referring to a fleet that contains two attachedClusters
apiVersion: apps.kurator.dev/v1alpha1
kind: Application
metadata:
name: gitrepo-kustomization-demo
namespace: default
spec:
source:
gitRepository:
interval: 3m0s
ref:
branch: master
timeout: 1m0s
url: https://github.com/stefanprodan/podinfo
syncPolicies:
- destination:
fleet: quickstart
kustomization:
interval: 5m0s
path: ./deploy/webapp
prune: true
timeout: 2m0s
- destination:
fleet: quickstart
kustomization:
targetNamespace: default
interval: 5m0s
path: ./kustomize
prune: true
timeout: 2m0s
Try other example application
Optionally, you can also try testing the examples below with different combinations
# This includes the `helmRepository` as source and the `helmRelease` as syncPolicies
kubectl apply -f examples/application/helmrepo-helmrelease-demo.yaml
Here is the configuration of application.
apiVersion: apps.kurator.dev/v1alpha1
kind: Application
metadata:
name: helmrepo-helmrelease-demo
namespace: default
spec:
source:
helmRepository:
interval: 5m
url: https://stefanprodan.github.io/podinfo
syncPolicies:
- destination:
fleet: quickstart
helm:
releaseName: podinfo
chart:
spec:
chart: podinfo
interval: 50m
install:
remediation:
retries: 3
values:
redis:
enabled: true
repository: public.ecr.aws/docker/library/redis
tag: 7.0.6
ingress:
enabled: true
className: nginx
# This includes the `gitRepository` as source and the `helmRelease` as syncPolicies
kubectl apply -f examples/application/gitrepo-helmrelease-demo.yaml
Here is the configuration of application.
apiVersion: apps.kurator.dev/v1alpha1
kind: Application
metadata:
name: gitrepo-helmrelease-demo
namespace: default
spec:
source:
gitRepository:
interval: 3m0s
ref:
branch: master
timeout: 1m0s
url: https://github.com/stefanprodan/podinfo
syncPolicies:
- destination:
fleet: quickstart
helm:
releaseName: podinfo
chart:
spec:
chart: ./charts/podinfo
interval: 50m
install:
remediation:
retries: 3
values:
redis:
enabled: true
repository: public.ecr.aws/docker/library/redis
tag: 7.0.6
ingress:
enabled: true
className: nginx
Verifying the unified application distribution result
After the fleet’s control plane complete (approximately 1 minute), you can see within a few seconds that the application has been installed according to the configuration.
Use the following command to view the application installation result:
$ kubectl get po -A --kubeconfig=/root/.kube/kurator-member1.config
NAMESPACE NAME READY STATUS RESTARTS AGE
default podinfo-588b784c7c-65sx7 1/1 Running 0 4m41s
default podinfo-588b784c7c-hh8j8 1/1 Running 0 4m56s
...
webapp backend-d4b8d7844-8l2vp 1/1 Running 0 4m56s
webapp frontend-6d94ff7cb5-m55pt 1/1 Running 0 4m56s
$ kubectl get po -A --kubeconfig=/root/.kube/kurator-member2.config
NAMESPACE NAME READY STATUS RESTARTS AGE
default podinfo-588b784c7c-8bmtp 1/1 Running 0 22m
default podinfo-588b784c7c-cczfv 1/1 Running 0 23m
...
webapp backend-d4b8d7844-c6x8x 1/1 Running 0 23m
webapp frontend-6d94ff7cb5-4d4hh 1/1 Running 0 23m
The command output lists all the pods deployed across two clusters. If the application distribution is successful, you should see pods from the ‘podinfo’ and ‘webapp’ applications installed in both clusters
Cluster Selection with Application Policies
You can add selectors to an application policy to ensure that the policy is applied specifically to corresponding clusters. This functionality is particularly useful in scenarios where a fleet contains various types of clusters. For instance, if your fleet includes clusters for testing and others for development, different application distribution strategies may be required.
Labels such as env=dev
can be assigned to clusters, and the same selectors can then be specified in the corresponding application policy. Once configured, the application will select the specific clusters in the fleet based on these selectors to distribute the application.
Please note the following considerations:
-
You have the option to set a default selector for all policies under
application.spec.destination
, or to configure it within individual policies. Kurator gives precedence to the policy-level setting - it resorts to the default setting only when the destination within the policy is not set. -
To ensure that the policy functions as expected, selectors should be added to the cluster prior to running the application.
Let’s look at a use case:
We’ll continue with the test fleet and attachedCluster used previously:
kubectl apply -f examples/application/common/
Next, let’s add labels to the attachedCluster:
kubectl label attachedcluster kurator-member1 env=test
kubectl label attachedcluster kurator-member2 env=dev
To test the selector, run the application:
kubectl apply -f examples/application/cluster-selector-demo.yaml
You can inspect the clusters with the following commands:
kubectl get po -A --kubeconfig=/root/.kube/kurator-member1.config
kubectl get po -A --kubeconfig=/root/.kube/kurator-member2.config
Upon examining the respective clusters, you’ll find that applications originating from the same source configuration have been distributed to different clusters based on their respective policy selector labels.
Playgroud
Kurator uses killercoda to provide applications demo, allowing users to experience hands-on operations.
CleanUp
Use the following command to clean up the gitrepo-kustomization-demo
application and related resources, like gitRepository
, kustomization
, helmRelease
, etc.
kubectl delete applications.apps.kurator.dev gitrepo-kustomization-demo
Also, you can confirm that the corresponding cluster applications have been cleared through the following command:
# Replace `/root/.kube/kurator-member1.config` with the actual path of your cluster's kubeconfig file.
kubectl get po -A --kubeconfig=/root/.kube/kurator-member1.config
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