Kogito Operator

The Kogito Operator deploys Kogito Runtimes services from source and all infrastructure requirements for the services, such as persistence with Infinispan and messaging with Apache Kafka. Kogito provides a command-line interface (CLI) that enables you to interact with the Kogito Operator for deployment tasks.

For information about the Kogito Operator architecture and instructions for using the operator and CLI to deploy Kogito services and infrastructures, see the official Kogito Documentation page.

Table of Contents

• Trying the Kogito Operator
• Using Kogito Custom Resources as a dependency
• Contributing to the Kogito Operator
  • Kogito Operator environment
    • Kogito Operator unit tests
    • Kogito Operator collaboration and pull requests
  • Kogito Operator development
    • Prerequisites
    • Requirements
    • Building the Kogito Operator
    • Deploying to OpenShift 4.x for development purposes
    • Running BDD Tests
      • Running BDD tests with current branch
      • Running BDD tests with custom Kogito Build images' version
      • Running smoke tests
      • Running performance tests
      • List of test tags
    • Running the Kogito Operator locally
    • Remote Debug Kogito Operator using Intellij IDEA
  • Guide for Kogito Developers
  • Releasing Kogito Operator
  • Kogito Operator tested integrations

Created by gh-md-toc

Trying the Kogito Operator

You can quickly install the operator in your local cluster by executing the following command:

VERSION=<current_operator_version>
kubectl apply -f "https://github.com/kiegroup/kogito-operator/releases/download/${VERSION}/kogito-operator.yaml"

Replace the version above to match your context (example v1.8.0). The version information you can grab from the releases page.

Alternatively, if you cloned this repo just do:

$ ./hack/install.sh

The script will download the latest version and install the resources for you in the kogito-operator-system namespace. You can set the VERSION variable before running the script to control which version to install.

For further information on how to install in other environments and configure the Kogito Operator, please see our official documentation.

Using Kogito Custom Resources as a dependency

It's possible to use the Kubernetes Custom Resources managed by Kogito Operator in your Golang project. For this to work, you just have to import our client module in your go.mod file:

# client depends on the `api` module
go install github.com/kiegroup/kogito-operator/client@{VERSION}

Replace {VERSION} with the latest release.

The client module will provide your project with the Kubernetes client for Kogito custom resources such as KogitoRuntime and KogitoBuild.

Avoid importing the whole project unless extremely necessary. The Kogito Operator has many dependencies since it can connect to different managed resources from third-party vendors such as Strimzi and Infinispan.

Contributing to the Kogito Operator

Thank you for your interest in contributing to this project!

Any kind of contribution is welcome: code, design ideas, bug reporting, or documentation (including this page).

Kogito Operator environment

The Operator SDK is updated regularly, and the Kogito Operator code typically uses the most recent SDK updates as soon as possible.

If you do not have a preferred IDE, use Visual Studio Code with the vscode-go plugin for Go language tools support.

To use Go modules with VS Code, see Go modules support in VS Code.

To debug Go in your VS code, see Debugging Go code using VS Code.

We check our code with golangci-lint, so it is recommended to add this to your IDE. For adding the golangci-lint with goland, see Go Linter.

For adding the golangci-lint with VScode, install the Go Plugin and enable the linter from the plugins setting.

Kogito Operator unit tests

For information about Operator SDK testing, see Unit testing with the Operator SDK.

In general, the unit tests that are provided with the Kogito Operator are based on that Operator SDK testing resource. You might encounter minor issues as you create specific OpenShift APIs such as BuildConfig and DeploymentConfig that are not listed there. For an example test case with sample API calls, see the kogitobuild_controller_test.go test file.

Kogito Operator collaboration and pull requests

Before you start to work on a new proposed feature or on a fix for a bug, open an issue to discuss your idea or bug report with the maintainers. You can also work on a JIRA issue that has been reported. A developer might already be assigned to address the issue, but you can leave a comment in the JIRA asking if they need some help.

After you update the source with your new proposed feature or bug fix, open a pull request (PR) that meets the following requirements:

• You have a JIRA associated with the PR.
• Your PR has the name of the JIRA in the title, for example, [KOGITO-XXX] - Awesome feature that solves it all.
• The PR solves only the problem described in the JIRA.
• You have written unit tests for the particular fix or feature.
• You ran make before-pr before submitting the PR and everything is working accordingly.
• You tested the feature on an actual OpenShift cluster.
• You've added a RELEASE_NOTES.md entry regarding this change.

After you send your PR, a maintainer will review your code and might ask you to make changes and to squash your commits before we can merge.

If you have any questions, contact a Kogito Operator maintainer in the issues page.

Kogito Operator development

Before you begin fixing issues or adding new features to the Kogito Operator, review the previous instructions for contributing to the Kogito Operator repository.

Prerequisites

For code contributions, review the following prerequisites:

• Become familiar with the Go language. For an introduction to Go, see the official Go Documentation. For an intermediate or advanced Go resource, see The Go Programming Language book.
• Become familiar with the Operator SDK. For more information, see the Operator SDK Documentation and use the Memcached Operator as an example.
• Ensure that you have all Kogito Operator requirements set on your local machine. You must use the listed versions.

Requirements

• Docker
• Operator Courier is used to build, validate and push Operator Artifacts
• Operator SDK v1.21.0
• Go v1.17 is installed.
• Golint dependency: go install golang.org/x/lint/golint@latest
• Golangci-lint
• Python 3.x v3.x is installed
• Cekit v4.0.0+ is installed

Building the Kogito Operator

Check if your $HOME/.config/containers/registries.conf is like this:

# Note that changing the order here may break tests.
unqualified-search-registries = ['docker.io']

[[registry]]
prefix="docker.io/library"
location="quay.io/libpod"

[[registry]]
location="localhost:5000"
insecure=true

To build the Kogito Operator, use the following command:

$ make

The output of this command is a ready-to-use Kogito Operator image that you can deploy in any namespace.

Deploying to OpenShift 4.x for development purposes

Prerequisites:

1. Ensure that you built the Kogito operator first and pushed it to a registry reachable from the OpenShift cluster.

2. Operator registry tool is installed in your system and available as opm command

Follow the steps below:

1. Make sure that you defined environment variable BUNDLE_IMG. This variable will be used as an image tag used to store bundle image (containing all the operator metadata).

2. Make sure that you defined environment variable CATALOG_IMG. This variable will be used as an image tag used to store custom catalog image (containing reference to the custom bundle image).

3. Make sure that you defined environment variable IMAGE pointing to the custom Kogito operator image tag which you built.

4. Make sure that you defined environment variable BUILDER defining container runtime engine used to build and push images. Default value is podman.

5. Update the bundle metadata to point to the custom Kogito operator image by running this command:

$ make update-bundle

6. Build the bundle image by running this command:

$ make bundle-build

7. Push the built bundle image by running this command:

$ make bundle-push

8. Build the catalog image by running this command:

$ make catalog-build

9. Push the built catalog image by running this command:

$ make catalog-push

10. Define pushed catalog image as a catalog source for your OpenShift cluster by running this command:

$ cat << EOF | oc apply -f -
apiVersion: operators.coreos.com/v1alpha1
kind: CatalogSource
metadata:
  name: custom-kogito-catalog
  namespace: openshift-marketplace
spec:
  sourceType: grpc
  image: ${CATALOG_IMG}
EOF

After several minutes, the Operator appears under Catalog -> OperatorHub in the OpenShift Web Console. To find the Operator, filter the provider type by custom-kogito-catalog.

Running BDD Tests

REQUIREMENTS:

• You need to be authenticated to the cluster before running the tests.
• Native tests need a node with at least 4 GiB of memory available (build resource request).

If you have an OpenShift cluster and admin privileges, you can run BDD tests with the following command:

$ make run-tests [key=value]*

You can set those optional keys:

• feature is a specific feature you want to run.
  If you define a relative path, this has to be based on the "test" folder as the run is happening there. Default are all enabled features from 'test/features' folder
  Example: feature=features/operator/deploy_quarkus_service.feature

• tags to run only specific scenarios. It is using tags filtering.
  Scenarios with '@disabled' tag are always ignored.
  Expression can be:

  • "@wip": run all scenarios with wip tag
  • "~@wip": exclude all scenarios with wip tag
  • "@wip && ~@new": run wip scenarios, but exclude new
  • "@wip,@undone": run wip or undone scenarios

  Complete list of supported tags and descriptions can be found in List of test tags

• concurrent is the number of concurrent tests to be ran.
  Default is 1.

• timeout sets the timeout in minutes for the overall run.
  Default is 240 minutes.

• debug to be set to true to activate debug mode.
  Default is false.

• load_factor sets the tests load factor. Useful for the tests to take into account that the cluster can be overloaded, for example for the calculation of timeouts.
  Default is 1.

• ci to be set if running tests with CI. Give CI name.

• cr_deployment_only to be set if you don't have a CLI built. Default will deploy applications via the CLI.

• load_default_config sets to true if you want to directly use the default test config (from test/.default_config)

• container_engine engine used to interact with images and local containers. Default is docker.

• domain_suffix domain suffix used for exposed services. Ignored when running tests on Openshift.

• image_cache_mode Use this option to specify whether you want to use image cache for runtime images. Available options are 'always', 'never' or 'if-available'(default).

• http_retry_nb sets the retry number for all HTTP calls in case it fails (and response code != 500). Default is 3.

• olm_namespace Set the namespace which is used for cluster scope operators. Default is 'openshift-operators'.

• operator_image_tag is the Operator image full name. Default: quay.io/kiegroup/kogito-operator:${currentVersion}.
• operator_installation_source Defines what source is used to install Kogito operator. Available options are olm and yaml. Default is yaml.
• operator_catalog_image Specifies catalog image containing Kogito operator bundle. Needs to be specified when operator_installation_source is set to olm.
• use_product_operator Set true if you want to run tests using product operator.

• operator_yaml_uri Url or Path to kogito-operator.yaml file. Default is ../kogito-operator.yaml.
• cli_path set the built CLI path.
  Default is ./build/_output/bin/kogito.
• rhpam_operator_yaml_uri Url or Path to rhpam-operator.yaml file. Default is ../rhpam-operator.yaml.

• services_{image_type}_{persistence_type}_image_tag sets the services (jobs-service, data-index, ...) image tag.
  image_type => data-index, explainibility, jobs-service, mgmt-console, task-console, trusty, trusty-ui
  persistence_type => ephemeral, infinispan, mongodb, postgresql, redis
  This will override those parameters for the given image: services_image_version, services_image_namespace, services_image_registry.
• services_image_registry sets the global services image registry.
• services_image_name_suffix sets the global services image name suffix to append to usual image names.
• services_image_version sets the global services image version.

• custom_maven_repo_url sets a custom Maven repository url for S2I builds, in case your artifacts are in a specific repository. See https://github.com/kiegroup/kogito-images/README.md for more information.
• maven_mirror_url is the Maven mirror URL.
  This is helpful when you need to speed up the build time by referring to a closer Maven repository.
• quarkus_platform_maven_mirror_url is the Maven mirror url to be used when building app from source files with Quarkus, using the quarkus maven plugin.
• build_builder_image_tag sets the Builder image full tag.
• build_runtime_jvm_image_tag sets the Runtime JVM image full tag.
• build_runtime_native_image_tag sets the Runtime Native image full tag.
• disable_maven_native_build_container disables the default Maven native build done in container.

• examples_uri sets the URI for the kogito-examples repository.
  Default is https://github.com/kiegroup/kogito-examples.
• examples_ref sets the branch for the kogito-examples repository.

• runtime_application_image_registry sets the registry for built runtime applications.
• runtime_application_image_namespace sets the namespace for built runtime applications.
• runtime_application_image_name_prefix sets the image name prefix to prepend to usual image names for built runtime applications.
• runtime_application_image_name_suffix sets the image name suffix to append to usual image names for built runtime applications.
• runtime_application_image_version sets the version for built runtime applications.

• show_scenarios sets to true to display scenarios which will be executed.
  Default is false.
• show_steps sets to true to display scenarios and their steps which will be executed.
  Default is false.
• dry_run sets to true to execute a dry run of the tests, disable crds updates and display the scenarios which will be executed.
  Default is false.
• keep_namespace sets to true to not delete namespace(s) after scenario run (WARNING: can be resources consuming ...).
  Default is false.
• namespace_name to specify name of the namespace which will be used for scenario execution (intended for development purposes).
• local_cluster to be set to true if running tests using a local cluster. Default is false.
• local_execution to be set to true if running tests in local using either a local or remote cluster. Default is false.

Logs will be shown on the Terminal.

To save the test output in a local file for future reference, run the following command:

make run-tests 2>&1 | tee log.out

Running BDD tests with current branch

$ make
$ docker tag quay.io/kiegroup/kogito-operator:2.0.0-snapshot quay.io/{USERNAME}/kogito-operator:2.0.0-snapshot
$ docker push quay.io/{USERNAME}/kogito-operator:2.0.0-snapshot
$ make run-tests operator_image=quay.io/{USERNAME}/kogito-operator

NOTE: Replace {USERNAME} with the username/group you want to push to. Docker needs to be logged in to quay.io and be able to push to your username/group.

Running BDD tests with custom Kogito Build images' version

$ make run-tests build_image_version=<kogito_version>

Running smoke tests

The BDD tests do provide some smoke tests for a quick feedback on basic functionality:

$ make run-smoke-tests [key=value]*

It will run only tests tagged with @smoke. All options from BDD tests do also apply here.

Running performance tests

The BDD tests also provide performance tests. These tests are ignored unless you specifically provide the @performance tag or run:

$ make run-performance-tests [key=value]*

It will run only tests tagged with @performance. All options from BDD tests do also apply here.

NOTE: Performance tests should be run without concurrency.

List of test tags

Tag name	Tag meaning
@smoke	Smoke tests verifying basic functionality
@performance	Performance tests
@travelagency	Travel agency tests
@disabled	Disabled tests, usually with comment describing reasons
@cli	Tests to be executed only using Kogito CLI
@rhpam	Tests to be executed for RHPAM Kogito operator
@springboot	SpringBoot tests
@quarkus	Quarkus tests
@dataindex	Tests including DataIndex
@trusty	Tests including Trusty
@jobsservice	Tests including Jobs service
@managementconsole	Tests including Management console
@trustyui	Tests including Trusty UI
@binary	Tests using Kogito applications built locally and uploaded to OCP as a binary file
@asset	Tests using Kogito applications built from assets uploaded to OCP
@native	Tests using native build
@ignorelts	Tests using native build that cannot be tested with Quarkus LTS version
@persistence	Tests verifying persistence capabilities
@events	Tests verifying eventing capabilities
@discovery	Tests checking service discovery functionality
@usertasks	Tests interacting with user tasks to check authentication/authorization
@security	Tests verifying security capabilities
@failover	Tests verifying failover capabilities
@metrics	Tests verifying metrics capabilities
@resources	Tests checking resource requests and limits
@infinispan	Tests using the infinispan operator
@kafka	Tests using the kafka operator
@keycloak	Tests using the keycloak operator
@knative	Tests using the Knative functionality
@postgresql	Tests using the PostgreSQL functionality
@grafana	Tests using the Grafana functionality
@prometheus	Tests using the Prometheus functionality

Running the Kogito Operator locally

To run the Kogito Operator locally, change the log level at runtime with the DEBUG environment variable, as shown in the following example:

$ DEBUG=true make run

You can use the following command to vet, format, lint, and test your code:

$ make vet && make test

Remote Debug Kogito Operator using Intellij IDEA

The operator will be deployed over an Kubernetes cluster. In this example we've taken minikube to deploy a Kubernetes cluster locally.

Install Minikube:

For installing the Minikube cluster please follow this tutorial

$ minikube start

Apply Operator manifests:

$ export NAMESPACE=default
$ ./hack/install-manifests.sh

Install Delve:

Delve is a debugger for the Go programming language. For installing Delve please follow this tutorial

Start Operator in remote debug mode:

$ cd cmd/manager
$ export WATCH_NAMESPACE=default
$ dlv debug --headless --listen=:2345 --api-version=2

verify logs on bash console for below line

API server listening at: [::]:2345

Create the Go Remote run/debug configuration:

1. Click Edit | Run Configurations. Alternatively, click the list of run/debug configurations on the toolbar and select Edit Configurations.
   
2. In the Run/Debug Configurations dialog, click the Add button (+) and select Go Remote.
3. In the Host field, type the host IP address (in our case localhost).
4. In the Port field, type the debugger port that you configured in above dlv command (in our case it's 2345).
5. Click OK.
   
6. Put the breakpoint in your code.
7. From the list of run/debug configurations on the toolbar, select the created Go Remote configuration and click the Debug <configuration_name> button

Running Kogito operator in remote debug on VSCode and GoLand is very similar to above procedure. Please follow these article to the setup remote debugger on VSCode and GoLand

Guide for Kogito Developers

If you are a new developer looking for information on how to start working on the operator, please take a look at this guide.

If you made changes in the core/runtimes part of the Kogito and want to test your changes against the operator, please follow this guide to test your changes.

Releasing Kogito Operator

When releasing the new version of kogito-operator in community-operators. One can use make olm-manifests it would create the manifests in the build/_output/olm/<version> directory in format which the community-operators repo expects. One can then just copy the directory into the kogito-operator and raise the PR.

Note: One needs to create two separate PRs with this folder added in upstream-kogito-operator and community-kogito-operator respectively.

Before raising the PR, make sure the replaces field in the CSV is correct

Kogito Operator tested integrations

Kogito operator integrates with various other technologies and operators. The tested certification matrix is listed below:

Technology	Tested version
Infinispan	Infinispan operator 2.1.5 (deployed by OLM 2.1.x channel)
Kafka	Strimzi 0.25.0 (deployed by OLM stable channel)
Keycloak	Keycloak operator 15.0.2 (deployed by OLM alpha channel)
Prometheus	Prometheus operator 0.47.0 (deployed by OLM beta channel)
Grafana	Grafana operator 3.10.3 (deployed by OLM alpha channel)
Knative Eventing	Knative Eventing 0.26.0
MongoDB	MongoDB Community Kubernetes Operator 0.2.2
PostgreSQL	PostgreSQL 12.7 (deployed directly using image)