SRVLOGIC-75: Update openshift knative docs with Serverless Logic Workflow guides for 1.32.0 #89
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| Original file line number | Diff line number | Diff line change | ||||
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| = (Community Only) = Building and deploying a {context} application on Kubernetes using the {product_name} Operator | ||||||
| :compat-mode!: | ||||||
| // Metadata: | ||||||
| :description: Build and deploy using the OpenShift Serverless Logic Operator a OpenShift Serverless Logic application | ||||||
| :keywords: kogito, workflow, serverless, operator, kubernetes, minikube, openshift | ||||||
| // links | ||||||
| :kogito_serverless_operator_url: https://github.com/kiegroup/kogito-serverless-operator/ | ||||||
| :kogito_greeting_example_url: https://github.com/kiegroup/kogito-examples/tree/stable/serverless-workflow-examples/serverless-workflow-greeting-quarkus | ||||||
| :kaniko_issue_url: https://github.com/GoogleContainerTools/kaniko/issues/2201 | ||||||
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||||||
| [NOTE] | ||||||
| ==== | ||||||
| This feature is meant for a quick preview on community repositories, and it's not part of the developer preview. | ||||||
| ==== | ||||||
| [NOTE] | ||||||
| ==== | ||||||
| This feature is meant for a quick preview on community repositories, and it's not part of the developer preview. | ||||||
| ==== | ||||||
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| This document describes how to build and deploy your workflow application using a Kubernetes cluster with the link:{kogito_serverless_operator_url}[{product_name} Operator]. If you don't have any cluster operational, link:{minikube_url}[Minikube] commands are given throughout the guide. | ||||||
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| Using the {product_name} Operator, you will be able to build and deploy a {product_name} application only by having a workflow definition. | ||||||
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| If you already have a container built and pushed to a container registry and you want to deploy it on the Kubernetes cluster, then you can do it without the operator following the guide xref:cloud/deploying-on-kubernetes.adoc[Deploying your {context} application on Kubernetes]. | ||||||
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| The link:{kogito_serverless_operator_url}[{product_name} Operator] is currently in Alpha version, is under active development and is at the moment supporting {context} definitions that are using: | ||||||
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||||||
| * Functions | ||||||
| * States | ||||||
| - Switch including dataConditions | ||||||
| - Inject including data with a transition | ||||||
| * Operations including Actions containing functionRef with arguments | ||||||
| * KeepActive | ||||||
| * AutoRetries | ||||||
| * ExpressionsLang (jq or jsonpath) | ||||||
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||||||
| .Prerequisites | ||||||
| * A workflow definition. | ||||||
| * A Kubernetes cluster with admin privileges. If you haven't got one prepare, you can use a local link:{minikube_url}[Minikube] instance. | ||||||
| * `kubectl` command-line tool is installed. Otherwise, Minikube provides it. | ||||||
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||||||
| == Prepare a Minikube instance | ||||||
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| [source,shell,subs="attributes+"] | ||||||
| ---- | ||||||
| minikube start --cpus 4 --memory 4096 --addons registry --addons metrics-server --insecure-registry "10.0.0.0/24" --insecure-registry "localhost:5000" | ||||||
| ---- | ||||||
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||||||
| [NOTE] | ||||||
| ==== | ||||||
| To speed up the build time, you can increase CPUs and memory options so that you minikube instance will have more resources. For example, use `--cpus 12 --memory 16384`. | ||||||
| ==== | ||||||
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| [TIP] | ||||||
| ==== | ||||||
| If it does not work with the default driver, as known as `docker`, you can try to start with the `podman` driver as follows: | ||||||
| ==== | ||||||
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| .Start minikube with podman driver | ||||||
| [source,shell,subs="attributes+"] | ||||||
| ---- | ||||||
| minikube start [...] --driver podman | ||||||
| ---- | ||||||
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| [IMPORTANT] | ||||||
| ==== | ||||||
| There are some issues with the `crio` container runtime and Kaniko that the operator is using. Reference: link:{kaniko_issue_url}[ISSUE-2201] | ||||||
| ==== | ||||||
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||||||
| == Setup {product_name} Operator | ||||||
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| In order to have an up-and-running instance of the {product_name} Operator you can use the following command: | ||||||
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| .Install {product_name} Operator on Kubernetes | ||||||
| [source,shell,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl create -f https://raw.githubusercontent.com/kiegroup/kogito-serverless-operator/{operator_version}/operator.yaml | ||||||
| ---- | ||||||
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| You can follow, then, the deployment of the {product_name} Operator: | ||||||
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| .Watch the {product_name} Operator pod | ||||||
| [source,shell,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl get pod -n kogito-serverless-operator-system --watch | ||||||
| ---- | ||||||
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| You can also follow the operator’s log: | ||||||
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| .Watch the {product_name} Operator pod logs | ||||||
| [source,shell,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl logs deployment/kogito-serverless-operator-controller-manager -n kogito-serverless-operator-system -f | ||||||
| ---- | ||||||
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| Once the operator is running, it will watch for new custom resources (CR) so that you can prepare your environment to be ready to build a new {context} application based on the definitions you will send to the operator. | ||||||
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| == Preparing for the build | ||||||
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| You should follow these steps to create a container that you can deploy as a service on Kubernetes. | ||||||
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| === Create a namespace for the building phase | ||||||
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| Let's create a new namespace that will hold all the resources that we (or the operator) will create (pods, deployments, services, secretes, config map, and Custom Resources) in this guide. | ||||||
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| .Create a namespace for the application to build & run in | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl create namespace kogito-workflows | ||||||
| ---- | ||||||
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| === Create a secret for the container registry authentication | ||||||
| .Create a secret for the container registry authentication | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl create secret docker-registry regcred --docker-server=<registry_url> --docker-username=<registry_username> --docker-password=<registry_password> --docker-email=<registry_email> -n kogito-workflows | ||||||
| ---- | ||||||
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| or you can directly import your local docker config into your Kubernetes cluster: | ||||||
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| .Create a secret for the container registry authentication based on local docker config | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl create secret generic regcred --from-file=.dockerconfigjson=${HOME}/.docker/config.json --type=kubernetes.io/dockerconfigjson -n kogito-workflows | ||||||
| ---- | ||||||
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| === Create a {product_name} Platform containing the configuration (i.e. registry address, secret) for building your workflows | ||||||
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| The {product_name} Platform CR is the resource used to control the behavior of the {product_name} Operator. | ||||||
| It defines the behavior of all Custom Resources (Workflow and Build) in the given namespace. | ||||||
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| Since the {product_name} Operator is installed in global mode, you will need to specify a {product_name} Platform CR in each namespace where you want the operator to be executed. | ||||||
| You can find a basic {product_name} Serverless Platform CR example in the `config/samples` folder that you can simply apply to configure your operator. | ||||||
|
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| .Create a {product_name} Platform CR | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl apply -f https://raw.githubusercontent.com/kiegroup/kogito-serverless-operator/{operator_version}/config/samples/sw.kogito_v1alpha08_kogitoserverlessplatform.yaml -n kogito-workflows | ||||||
| ---- | ||||||
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| Note: In this Custom Resource, spec.platform.registry.secret is the name of the secret you created just before. | ||||||
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| [TIP] | ||||||
| ==== | ||||||
| You can also update "on-the-fly" the {product_name} Platform CR registry field with this command (change <YOUR_REGISTRY>) | ||||||
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| .Create a {product_name} Platform CR with a specific registry | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| curl https://raw.githubusercontent.com/kiegroup/kogito-serverless-operator/{operator_version}/config/samples/sw.kogito_v1alpha08_kogitoserverlessplatform.yaml | sed "s|address: .*|address: <YOUR_REGISTRY>" | kubectl apply -f - | ||||||
| ---- | ||||||
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| In order to retrieve the Cluster IP address of Minikube's internal registry to configure your platform, you can use the following command: | ||||||
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| .Retrieve Minikube registry internal IP | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl get svc registry -n kube-system -ojsonpath='{.spec.clusterIP}' | ||||||
| ---- | ||||||
| ==== | ||||||
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| == Build and deploy your {context} application | ||||||
|
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| You can now send your {product_name} Custom Resource to the operator which includes the {context} definition. | ||||||
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| You can find a basic {product_name} Platform CR example in the `config/samples` folder that you can simply apply to configure your operator. | ||||||
|
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| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl apply -f https://raw.githubusercontent.com/kiegroup/kogito-serverless-operator/{operator_version}/config/samples/sw.kogito_v1alpha08_kogitoserverlessworkflow.yaml -n kogito-workflows | ||||||
| ---- | ||||||
| You can check the logs of the build of your workflow via: | ||||||
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| .Get the {product_name} application pod logs | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl logs kogito-greeting-builder -n kogito-workflows | ||||||
| ---- | ||||||
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| The final pushed image must be printed into the logs at the end of the build. | ||||||
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| == Check the {product_name} application is running | ||||||
| In order to check that the {product_name} Greeting application is up and running, you can try to perform a test HTTP call, from the greeting pod. | ||||||
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| .Check the greeting application is running | ||||||
| [source,bash,subs="attributes+"] | ||||||
| ---- | ||||||
| kubectl patch svc greeting -n kogito-workflows -p '{"spec": {"type": "NodePort"}}' | ||||||
| GREETING_SVC=$(minikube service greeting -n kogito-workflows --url) | ||||||
| curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"name": "John", "language": "English"}' $GREETING_SVC/greeting | ||||||
| ---- | ||||||
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| If everything is working well you should receive a response like this: | ||||||
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| .Response from the greeting application | ||||||
| [source,json,subs="attributes+"] | ||||||
| ---- | ||||||
| {"id":"b5fbfaa3-b125-4e6c-9311-fe5a3577efdd","workflowdata":{"name":"John","language":"English","greeting":"Hello from JSON Workflow, "}} | ||||||
| ---- | ||||||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,40 @@ | ||
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| -- | ||
| .Create namespace | ||
| [source,shell] | ||
| ---- | ||
| kubectl create namespace serverless-workflow-greeting-quarkus | ||
| ---- | ||
| -- | ||
|
|
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| . Set the Kubernetes context to the newly created namespace using the following command: | ||
| + | ||
| -- | ||
| .Set Kubernetes context to a namespace | ||
| [source,shell] | ||
| ---- | ||
| kubectl config set-context --current --namespace=serverless-workflow-greeting-quarkus | ||
| ---- | ||
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| After setting the context, all kubectl commands will use the selected namespace. + | ||
| You can use the following command to verify the current namespace: | ||
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| .Verify the current namespace | ||
| [source,shell] | ||
| ---- | ||
| kubectl config view --minify -o jsonpath='{..namespace}' | ||
| ---- | ||
| -- | ||
|
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| . Deploy your {context} application {deploy_application}. | ||
| + | ||
| -- | ||
| The next step is to deploy your workflow application and execute it. | ||
| You can read the further sections on the different procedures to deploy your {context} application. | ||
|
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| [NOTE] | ||
| ==== | ||
| You can use the native image due to the faster startup. + | ||
| For more information about installing the workflow application, see xref:cloud/build-workflow-image-with-quarkus-cli.adoc[Building workflow images using Quarkus CLI] document. | ||
| ==== | ||
| -- |
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| .Prerequisites | ||
| * {cluster_kind}. | ||
| * Knative is ready. + | ||
| For more information, see {knative_procedure}. | ||
| * Knative CLI is installed. | ||
| * (Optional) Quarkus CLI is installed. + | ||
| For more information, see link:{quarkus_cli_url}[Building Quarkus Apps with Quarkus command line interface (CLI)]. | ||
| * {context} application container is ready. |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,15 @@ | ||
| :kn_cli_url: https://knative.dev/docs/client/install-kn/ | ||
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| .Prerequisites | ||
| * Your {context} application is ready to use. + | ||
| For more information about building the application container, see xref:cloud/build-workflow-image-with-quarkus-cli.adoc[Building workflow images using Quarkus CLI]. | ||
|
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| * {environment_prereq} | ||
| * `kubectl` {kubectl_prereq} | ||
| * Knative CLI is installed. + | ||
| For more information, see link:{kn_cli_url}[Install the Knative CLI]. | ||
| * Knative workflow CLI is installed. + | ||
| For more information see xref:tooling/kn-plugin-workflow-overview.adoc[Serverless Workflow plug-in for Knative CLI]. | ||
| * (Optional) Quarkus CLI is installed. + | ||
| For more information, see link:{quarkus_cli_url}[Building Quarkus Apps with Quarkus command line interface (CLI)]. | ||
|
|
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We need to update the downstream versions here.
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quarkus_version: 2.13.5.Final-redhat-00003kogito_version_redhat: 1.32.0.Final-redhat-00003kn_cli_version: 0.26.0