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Dekorate is a collection of Java compile-time generators and decorators for Kubernetes/OpenShift manifests.

It makes generating Kubernetes manifests as easy as adding a dependency to the classpath and customizing as simple as setting an annotation or application property.

Stop wasting time editing xml, json and yml and customize the kubernetes manifests as you configure your java application.

Rebranding Notice

This project was originally called ap4k which stood for Annotation Processors for Kubernetes. As the project now supports decorating of kubernetes manifests without the use of annotations, the name ap4k no longer describes the project in the best possible way. So, the project has been renamed to dekorate.

Features

Experimental features

Rationale

There are tons of tools out there for scaffolding / generating kubernetes manifests. Sooner or later these manifests will require customization. Handcrafting is not an appealing option. Using external tools, is often too generic. Using build tool extensions and adding configuration via xml, groovy etc is a step forward, but still not optimal.

Annotation processing has quite a few advantages over external tools or build tool extensions:

Hello World

This section provides examples on how to get started based on the framework you are using.

Hello Spring Boot

Add the following dependency to your project:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-spring-starter</artifactId>
  <version>1.0.1</version>
</dependency>

That’s all! Next time you perform a build, using something like:

mvn clean package

The generated manifests can be found under target/classes/META-INF/dekorate.

asciicast

Hello Quarkus

Add the following dependency to your project:

<dependency>
  <groupId>io.quarkus</groupId>
  <artifactId>quarkus-kubernetes</artifactId>
  <version>1.0.0.Final</version>
</dependency>

That’s all! Next time you perform a build, using something like:

mvn clean package

The generated manifests can be found under target/kubernetes. Note: Quarkus is using its own dekorate based Kubernetes extension (see more at Quarkus).

asciicast

Hello Thorntail

Add the following dependency to your project:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>thorntail-spring-starter</artifactId>
  <version>1.0.1</version>
</dependency>

That’s all! Next time you perform a build, using something like:

mvn clean package

The generated manifests can be found under target/classes/META-INF/dekorate.

asciicast

Hello Generic Java Application

Add the following dependency to your project:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Then add the @Dekorate annotation to one of your Java source files.

package org.acme;

import io.dekorate.annotation.Dekorate;

@Dekorate
public class Application {
}

Note: It doesn’t have to be the Main class. Next time you perform a build, using something like:

mvn clean package

The generated manifests can be found under target/classes/META-INF/dekorate.

asciicast

Usage

To start using this project you just need to add one of the provided dependencies to your project. For known frameworks like spring boot, quarkus, or thorntail that’s enough. For generic java projects, we also need to add an annotation that expresses our intent to enable dekorate.

This annotation can be either @Dekorate or a more specialized one, which also gives us access to more specific configuration options. Further configuration is feasible using:

A complete reference of the supported properties can be found in the configuration options guide.

Kubernetes

@KubernetesApplication is a more specialized form of @Dekorate. It can be added to your project like:

import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication
public class Main {

    public static void main(String[] args) {
      //Your application code goes here.
    }
}

When the project gets compiled, the annotation will trigger the generation of a Deployment in both json and yml that will end up under ‘target/classes/META-INF/dekorate’.

The annotation comes with a lot of parameters, which can be used in order to customize the Deployment and/or trigger the generations of addition resources, like Service and Ingress.

Adding the kubernetes annotation processor to the classpath

This module can be added to the project using:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Name and Version

So where did the generated Deployment gets its name, docker image etc from?

Everything can be customized via annotation parameters and system properties. On top of that, lightweight integration with build tools is provided in order to reduce duplication.

Lightweight build tool integration

Lightweight integration with build tools, refers to reading information from the build tool config without bringing in the build tool itself into the classpath. The information read from the build tool is limited to:

For example in the case of maven it refers to parsing the pom.xml with DOM in order to fetch the artifactId and version.

Supported build tools:

For all other build tools, the name and version need to be provided via application.properties:

dekorate.kubernetes.name=my-app
dekorate.kubernetes.version=1.1.0.Final

or the core annotations:

@KubernetesApplication(name = "my-app", version="1.1.0.Final")
public class Main {
}

or

@OpenshiftApplication(name = "my-app", version="1.1.0.Final")
public class Main {
}

and so on…

The information read from the build tool, is added to all resources as labels (name, version). They are also used to name images, containers, deployments, services etc.

For example for a gradle app, with the following gradle.properties:

name = my-gradle-app
version = 1.0.0

The following deployment will be generated:

apiVersion: "apps/v1"
kind: "Deployment"
metadata:
  name: "kubernetes-example"
spec:
  replicas: 1
  selector:
    matchLabels:
      app.kubernetes.io/name: "my-gradle-app"
      app.kubernetes.io/version: "1.0-SNAPSHOT"
  template:
    metadata:
      labels:
        app.kubernetes.io/name: "my-gradle-app"
        app.kubernetes.io/version: "1.0-SNAPSHOT"
    spec:
      containers:
      - env:
        - name: "KUBERNETES_NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: "metadata.namespace"
        image: "default/my-gradle-app:1.0-SNAPSHOT"
        imagePullPolicy: "IfNotPresent"
        name: "my-gradle-app"

The output file name may be used in certain cases, to set the value of JAVA_APP_JAR an environment variable that points to the build jar.

Adding extra ports and exposing them as services

To add extra ports to the container, you can add one or more @Port into your @KubernetesApplication:

import io.dekorate.kubernetes.annotation.Port;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(ports = @Port(name = "web", containerPort = 8080))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

This will trigger the addition of a container port to the Deployment but also will trigger the generation of a Service resource.

Everything that can be defined using annotations, can also be defined using application.properties. To add a port using application.properties:

dekorate.kubernetes.ports[0].name=web
dekorate.kubernetes.ports[0].container-port=8080

NOTE: This doesn’t need to be done explicitly, if the application framework is detected and support, ports can be extracted from there (see below).

IMPORTANT: When mixing annotations and application.properties the latter will always take precedence overriding values that defined using annotations. This allows users to define the configuration using annotations and externalize configuration to application.properties.

REMINDER: A complete reference on all the supported properties can be found in the configuration options guide.

Adding container environment variables

To add extra environment variables to the container, you can add one or more @EnvVar into your @KubernetesApplication :

import io.dekorate.kubernetes.annotation.Env;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(envVars = @Env(name = "key1", value = "var1"))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

Additional options are provided for adding environment variables from fields, config maps and secrets.

To add environment variables using application.properties:

dekorate.kubernetes.env-vars[0].name=key1
dekorate.kubernetes.env-vars[0].value=value1

Adding environment variables from ConfigMap

To add an environment variable that points to a ConfigMap property, you need to specify the configmap using the configmap property in the @Env annotation. The configmap key will be specified by the value property. So, in this case value has the meaning of value from key.

import io.dekorate.kubernetes.annotation.Env;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(envVars = @Env(name = "key1", configmap="my-config", value = "key1"))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

To add an environment variable referencing a config map using application.properties:

dekorate.
.env-vars[0].name=key1
dekorate.kubernetes.env-vars[0].value=key1
dekorate.kubernetes.env-vars[0].config-map=my-config

Adding environment variables from Secrets

To add an environment variable that points to a Secret property, you need to specify the configmap using the secret property in the @Env annotation. The secret key will be specified by the value property. So, in this case value has the meaning of value from key.

import io.dekorate.kubernetes.annotation.Env;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(envVars = @Env(name = "key1", secret="my-secret", value = "key1"))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

To add an environment variable referencing a secret using application.properties:

dekorate.kubernetes.env-vars[0].name=key1
dekorate.kubernetes.env-vars[0].value=key1
dekorate.kubernetes.env-vars[0].secret=my-config

Working with volumes and mounts

To define volumes and mounts for your application, you can use something like:

import io.dekorate.kubernetes.annotation.Mount;
import io.dekorate.kubernetes.annotation.PersistentVolumeClaimVolume;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(pvcVolumes = @PersistentVolumeClaimVolume(volumeName = "mysql-volume", claimName = "mysql-pvc"),
  mounts = @Mount(name = "mysql-volume", path = "/var/lib/mysql")
)
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

To define the same volume and mount via application.properties:

dekorate.kubernetes.pvc-volumes[0].volume-name=mysql-volume
dekorate.kubernetes.pvc-volumes[0].claim-name=mysql-pvc
dekorate.kubernetes.mounts[0].name=mysql-volume
dekorate.kubernetes.mounts[0].path=/var/lib/mysql

Currently, the supported annotations for specifying volumes are:

Jvm Options

It’s common to pass the JVM options in the manifests using the JAVA_OPTS or JAVA_OPTIONS environment variable of the application container. This is something complex as it usually difficult to remember all options by heart and thus its error prone. The worst part is that you usually don’t realize the mistake until it’s TOO late.

Dekorate provides a way to manage those options using the @JvmOptions annotation, which is included in the options-annotations module.

import io.dekorate.options.annotation.JvmOptions;
import io.dekorate.options.annotation.GarbageCollector;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication
@JvmOptions(server=true, xmx=1024, preferIpv4Stack=true, gc=GarbageCollector.SerialGC)
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

or via application.properties:

dekorate.jvm.server=true
dekorate.jvm.xmx=1024
dekorate.jvm.prefer-ipv4-stack=true
dekorate.jvm.gc=GarbageCollector.SerialGC

This module can be added to the project using:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>option-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Note: The module is included in all starters.

Init Containers

If for any reason the application requires the use of init containers, they can be easily defined using the initContainer property, as demonstrated below.

import io.dekorate.kubernetes.annotation.Container;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(initContainers = @Container(image="foo/bar:latest", command="foo"))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

or via application.properties:

dekorate.kubernetes.init-containers[0].image=foo/bar:latest
dekorate.kubernetes.init-containers[0].command=foo

The @Container supports the following fields:

Sidecars

Similarly, to init containers support for sidecars is also provided using the sidecars property. For example:

import io.dekorate.kubernetes.annotation.Container;
import io.dekorate.kubernetes.annotation.KubernetesApplication;

@KubernetesApplication(sidecars = @Container(image="jaegertracing/jaeger-agent",
                                             args="--collector.host-port=jaeger-collector.jaeger-infra.svc:14267"))
public class Main {

  public static void main(String[] args) {
    //Your code goes here
  }
}

or via application.properties:

dekorate.kubernetes.sidecars[0].image=jaegertracing/jaeger-agent
dekorate.kuberentes.args=--collector.host-port=jaeger-collector.jaeger-infra.svc:14267

As in the case of init containers the @Container supports the following fields:

Adding the kubernetes annotation processor to the classpath

This module can be added to the project using:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

OpenShift

@OpenshiftApplication works exactly like @KubernetesApplication , but will generate resources in a file name openshift.yml / openshift.json instead. Also instead of creating a Deployment it will create a DeploymentConfig.

NOTE: A project can use both @KubernetesApplication and @OpenshiftApplication. If both the kubernetes and OpenShift annotation processors are present both kubernetes and OpenShift resources will be generated.

Adding the OpenShift annotation processor to the classpath

This module can be added to the project using:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>openshift-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Integrating with S2i

Out of the box resources for s2i will be generated.

Here’s an example:

import io.dekorate.openshift.annotation.OpenshiftApplication;

@OpenshiftApplication(name = "doc-example")
public class Main {

    public static void main(String[] args) {
      //Your code goes here
    }
}

The same can be expressed via application.properties:

dekorate.openshift.name=doc-example

IMPORTANT: All examples of application.properties demonstrated in the Kubernetes section can be applied here, by replacing the prefix dekorate.kubernetes with dekorate.openshift.

The generated BuildConfig will be a binary config. The actual build can be triggered from the command line with something like:

oc start-build doc-example --from-dir=./target --follow

NOTE: In the example above we explicitly set a name for our application, and we referenced that name from the cli. If the name was implicitly created the user would have to figure the name out before triggering the build. This could be done either by oc get bc or by knowing the conventions used to read names from build tool config (e.g. if maven then name the artifactId).

Tekton

Dekorate supports generating tekton pipelines. Since Dekorate knows, how your project is build, packaged into containers and deployed, converting that knowledge into a pipeline comes natural.

When the tekton module is added to the project:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>tekton-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Two sets of resources will be generated, each representing a different configuration style the use user can choose from:

Pipeline

This set of resources contains:

These are the building blocks of a Tekton pipeline that grabs your project from scm, builds and containerizes the project (in cluster) and finally deploys it.

Task

This set of resources provides the some functionality as above, but everything is collapsed under a single task (for usability reasons), In detail it contains:

Pipeline vs Task

If unsure which style to pickup, note that the task style has less configuration requirements and thus easier to begin with. The pipeline style is easier to slice and dice, once your are more comfortable with tekton.

Regardless of the choice, Dekorate provides a rich set of configuration options to make using tekton as easy as it gets.

Tekton Configuration

Git Resource

The generated tasks and pipelines, assume the project is under version control and more specifically git. So, in order to run the pipeline or the task a PiepelineResource of type git is required. If the project is added to git, the resource will be generated for you. If for any reason the use of an external resource is preferred then it needs to be configured, like:

dekorate.tekton.external-git-pipeline-resource=<<the name of the resource goes here>>
Builder Image

Both the pipeline and the task based resources include steps that perform a build of the project. Dekorate, tries to identify a suitable builder image for the project. Selection is based on the build tool, jdk version, jdk flavor and build tool version (in that order). At the moment only maven and gradle are supported.

You can customize the build task by specifying:

Configuring a Workspace PVC

One of the main differences between the two styles of configuration, is that Pipelines require a PersistentVolumeClaim in order to share the workspace between Tasks. On the contrary when all steps are part of single bit fat Task (which is baked by a Pod) and EmptyDir volume will suffice.

Out of the box, for the pipeline style resources a PersistentVolumeClaim named after the application will be generated and used.

The generated pvc can be customized using the following properties:

The option to provide an existing pvc (by name) instead of generating one is also provided, using dekorate.tekton.source-workspace-claim.

Configuring the Docker registry for Tekton

The generated Pipeline / Task includes steps for building a container image and pushing it to a registry.

The registry can be configured using dekorate.docker.registry as is done for the rest of the resources.

For the push to succeed credentials for the registry are required. The user is able to:

To provide an existing secret for the job (e.g. my-secret):

dekorate.tekton.image-builder-secert=my-secert

To provide username and password:

dekorate.tekton.registry-usernmae=myusername
dekorate.tekton.registry-password=mypassword

If none of the above is provided and a .docker/config.json exists, it can be used if explicitly requested:

dekorate.tekton.use-local-docker-config-json=true

Knative

Dekorate also supports generating manifests for knative. To make use of this feature you need to add:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>knative-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

This module provides the @KnativeApplication works exactly like @KubernetesApplication , but will generate resources in a file name knative.yml / knative.json instead. Also instead of creating a Deployment it will create a knative serving Service.

Cluster local services

Knative exposes services out of the box. You can use the @KnativeApplication(expose=false) or the property dekorate.knative.expose set to false, in order to mark a service as cluster local.

Autoscaling

Dekorate provides access to both revision and global autoscaling configuration (see Knative Autoscaling.

Global autoscaling configuration is supported via configmaps (KnativeServing is not supported yet).

Class

To set the autoscaler class for the target revision:

dekorate.knative.revision-auto-scaling.autoscaler-class=hpa

The allowed values are:

In the same spirit the global autoscaler class can be set using:

dekorate.knative.global-auto-scaling.autoscaler-class=hpa
Metric

To select the autoscaling metric:

dekorate.knative.revision-auto-scaling.metric=rps

The allowed values are:

Target

Metric specifies the metric kind. To sepcify the target value the autoscaler should aim to maintain, the target can be used:

dekorate.knative.revision-auto-scaling.target=100

There is no option to set a generic global target. Instead specific keys per metric kind are provided. See below:

Requests per second

To set the requests per second:

dekorate.knative.global-auto-scaling.requests-per-second=100
Target utilization

To set the target utilization:

dekorate.knative.global-auto-scaling.target-utilization-percentage=100

Framework integration

Framework integration modules are provided that we are able to detect framework annotations and adapt to the framework (e.g. expose ports).

The frameworks supported so far:

Spring Boot

With spring boot, we suggest you start with one of the provided starters:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-spring-starter</artifactId>
  <version>1.0.1</version>
</dependency>

Or if you are on OpenShift:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>openshfit-spring-starter</artifactId>
  <version>1.0.1</version>
</dependency>

Automatic configuration

For Spring Boot application, dekorate will automatically detect known annotation and will align generated manifests accordingly.

Web annotations

Dekorate tunes the generated manifest based on the presence of web annotations in the project:

When known web annotations are available in the project, dekorate will automatically detect and expose the http port as a Service. That service will also be expose as an Ingress or Route (in case of Openshift) if the expose option is set to true.

Kubernetes
@KubernetesApplication(expose=true)

An alternative way of configuration is via application properties:

dekorate.kubernetes.expose=true
Openshift
@OpenshiftApplication(expose=true)

An alternative way of configuration is via application properties:

dekorate.kubernetes.expose=true
RequestMapping

When one RequestMapping annotation is added on a Controller or multiple RequestMapping that share a common path are added on multiple Controller classes, dekorate will detect the shortest common path and configure it so that its available on the expose Ingress or Route.

Annotation less configuration

It is possible to completely bypass annotations by utilizing already-existing, framework-specific metadata. This mode is currently only supported for Spring Boot applications (i.e. at least one project class is annotated with @SpringBootApplication).

So, for Spring Boot applications, all you need to do is add one of the starters (io.dekorate:kubernetes-spring-starter or io.dekorate:openshift-spring-starter) to the classpath. No need to specify an additional annotation. This provides the fastest way to get started using dekorate with Spring Boot.

To customize the generated manifests you can add dekorate properties to your application.yml or application.properties descriptors, or even use annotations along with application.yml / application.properties though if you define dekorate properties then the annotation configuration will be replaced by the one specified using properties.

Dekorate looks for supported configuration as follows in increasing order of priority, meaning any configuration found in an application descriptor will override any existing annotation-specified configuration:

  1. Annotations
  2. application.properties
  3. application.yaml
  4. application.yml
  5. application-kubernetes.properties
  6. application-kubernetes.yaml
  7. application-kubernetes.yml

It’s important to repeat that the override that occurs by fully replacing any lower-priority configuration and not via any kind of merge between the existing and higher-priority values. This means that if you choose to override the annotation-specified configuration, you need to repeat all the configuration you want in the @Env annotation-less configuration.

Here’s the full list of supported configuration options. Special attention should be paid to the path of these properties. The properties’ path match the annotation properties and not what would end up in the manifest, meaning the annotation-less configuration matches the model defined by the annotations. More precisely, what is being configured using properties is the same model as what is configured using annotations. While there is some overlap between how the annotations are configured and the resulting manifest, the properties (or YAML file) still need to provide values for the annotation fields, hence why they need to match how the annotations are configured. Always refer to the configuration options guide if in doubt.

Generated resources when not using annotations

When no annotations are used, the kind of resources to be generated is determined by the dekorate artifacts found in the classpath.

File Required Dependency
kubernetes.json/yml io.dekorate:kubernetes-annotations
openshift.json/yml io.dekorate:openshift-annotations
halkyon.json/yml io.dekorate:halkyon-annotations

Note: that starter modules for kubernetes and openshift do transitively add kubernetes-annotations and openshift-annotations respectively.

Quarkus

quarkus provides rich set of extensions including one for kubernetes. The kubernetes extension uses internally dekorate for generating and customizing manifests.

The extension can be added to any quarkus project:

mvn quarkus:add-extension -Dextensions="io.quarkus:quarkus-kubernetes"

After the project compilation the generated manifests will be available under: target/kubernetes/.

At the moment this extension will handle ports, health checks etc, with zero configuration from the user side.

It’s important to note, that by design this extension will NOT use the dekorate annotations for customizing the generated manifests.

For more information please check: the extension docs.

Thorntail

With Thorntail, it is recommended to add a dependency on one of the provided starters:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-thorntail-starter</artifactId>
  <version>1.0.1</version>
  <scope>provided</scope>
</dependency>

Or, if you use OpenShift:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>openshfit-thorntail-starter</artifactId>
  <version>1.0.1</version>
  <scope>provided</scope>
</dependency>

Then, you can use the annotations described above, such @KubernetesApplication, @OpenShiftApplication, etc.

Note that the Thorntail annotation processor reads the thorntail.http.port configuration from the usual project-defaults.yml. It doesn’t read any other project-*.yml profiles.

Experimental features

Apart from the core feature, which is resource generation, there are a couple of experimental features that do add to the developer experience.

These features have to do with things like building, deploying and testing.

Building and Deploying?

Dekorate does not generate Docker files, neither it provides internal support for performing docker or s2i builds. It does however allow the user to hook external tools (e.g. the docker or oc) to trigger container image builds after the end of compilation.

So, at the moment as an experimental feature the following hooks are provided:

Docker build hook

This hook will just trigger a docker build, using an existing Dockerfile at the root of the project. It will not generate or customize the docker build in any way.

To enable the docker build hook you need:

To trigger the hook, you need to pass -Ddekorate.build=true as an argument to the build, for example:

mvn clean install -Ddekorate.build=true

or if you are using gradle:

gradle build -Ddekorate.build=true   

When push is enabled, the registry can be specified as part of the annotation, or via system properties. Here’s an example via annotation configuration:

@EnableDockerBuild(registry="quay.io")
public class Main {
}

Here’s how it can be done via build properties (system properties):

mvn clean install -Ddekorate.docker.registry=quay.io -Ddekorate.push=true    

Note: Dekorate will NOT push images on its own. It will delegate to the docker binary. So the user needs to make sure beforehand they are logged in and have taken all necessary actions for a docker push to work.

S2i build hook

This hook will just trigger an s2i binary build, that will pass the output folder as an input to the build

To enable the docker build hook you need:

Finally, to trigger the hook, you need to pass -Ddekorate.build=true as an argument to the build, for example:

mvn clean install -Ddekorate.build=true

or if you are using gradle:

gradle build -Ddekorate.build=true  

Jib build hook

This hook will just trigger a jib build in order to perform a container build.

In order to use it, one needs to add the jib-annotations dependency.

<dependencies>
  <groupId>io.dekorate</groupId>
  <artifactId>jib-annotations</artifactId>
</dependencies>

Without the need of any additional configuration, one trigger the hook by passing -Ddekorate.build=true as an argument to the build, for example:

mvn clean install -Ddekorate.build=true

or if you are using gradle:

gradle build -Ddekorate.build=true
Jib modes

At the moment Jib allows you to create and push images in two different ways:

At the moment performing a build through the docker daemon is slightly safer, and thus is used as a default option. You can easily switch to dockerless mode, by setting the @JibBuild(dockerBuild=false) or if using properties configuration dekorate.jib.docker-build=false.

In case of the dockerless mode, an openjdk-8 image is going to be used as a base image. The image can be changed through the from property on the @JibBuild annotation or dekorate.jib.from when using property configuration.

Junit5 extensions

Dekorate provides two junit5 extensions for:

These extensions are dekorate aware and can read generated resources and configuration, in order to manage end to end tests for the annotated applications.

Features

Kubernetes extension for Junit5

The kubernetes extension can be used by adding the following dependency:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>kubernetes-junit</artifactId>
  <version>1.0.1</version>
</dependency>

This dependency gives access to @KubernetesIntegrationTest which is what enables the extension for your tests.

By adding the annotation to your test class the following things will happen:

  1. The extension will check if a kubernetes cluster is available (if not tests will be skipped).
  2. If @EnableDockerBuild is present in the project, a docker build will be triggered.
  3. All generated manifests will be applied.
  4. Will wait until applied resources are ready.
  5. Dependencies will be injected (e.g. KubernetesClient, Pod etc)
  6. Test will run
  7. Applied resources will be removed.
Dependency injection

Supported items for injection:

To inject one of this you need a field in the code annotated with @Inject.

For example:

@Inject
KubernetesClient client;

When injecting a Pod, it’s likely we need to specify the pod name. Since the pod name is not known in advance, we can use the deployment name instead. If the deployment is named hello-world then you can do something like:

@Inject
@Named("hello-world")
Pod pod;

Note: It is highly recommended to also add maven-failsafe-plugin configuration so that integration tests only run in the integration-test phase. This is important since in the test phase the application is not packaged. Here’s an example of how it you can configure the project:

<plugin>
  <groupId>org.apache.maven.plugins</groupId>
  <artifactId>maven-failsafe-plugin</artifactId>
  <version>${version.maven-failsafe-plugin}</version>
  <executions>
    <execution>
      <goals>
        <goal>integration-test</goal>
        <goal>verify</goal>
      </goals>
      <phase>integration-test</phase>
      <configuration>
        <includes>
          <include>**/*IT.class</include>
        </includes>
      </configuration>
    </execution>
  </executions>
</plugin>

OpenShift extension for JUnit5

Similarly, to using the kubernetes junit extension you can use the extension for OpenShift, by adding @OpenshiftIntegrationTest. To use that you need to add:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>openshift-junit</artifactId>
  <version>1.0.1</version>
</dependency>

By adding the annotation to your test class the following things will happen:

  1. The extension will check if a kubernetes cluster is available (if not tests will be skipped).
  2. A docker build will be triggered.
  3. All generated manifests will be applied.
  4. Will wait until applied resources are ready.
  5. Dependencies will be injected (e.g. KubernetesClient, Pod etc)
  6. Test will run
  7. Applied resources will be removed.

Configuration externalization

It is often desired to externalize configuration in configuration files, instead of hard coding things inside annotations.

Dekorate provides the ability to externalize configuration to configuration files (properties or yml). This can be done to either override the configuration values provided by annotations, or to use dekorate without annotations.

For supported frameworks, this is done out of the box, as long as the corresponding framework jar is present. The frameworks supporting this feature are:

For these frameworks, the use of annotations is optional, as everything may be configured via configuration files. Each annotation may be expressed using properties or yaml using the following steps.

For all other frameworks or generic java application this can be done with the use of the @Dekorate annotation. The presence of this annotation will trigger the dekorate processes. Dekorate will then look for application.properites or application.yml resources. If present, they will be loaded. If not the default configuration will be used.

Examples:

The following annotation configuration:

@KubernetesApplication(labels=@Label(key="foo", value="bar"))
public class Main {
}

Can be expressed using properties:

dekorate.kubernetes.labels[0].key=foo
dekorate.kubernetes.labels[0].value=bar

or using yaml:

dekorate:
  kubernetes:
    labels:
      - key: foo
        value: bar

In the examples above, dekorate is the prefix that we use to namespace the dekorate configuration. kubernetes defines the annotation kind (its @KubernetesApplication in lower case and stripped of the Application suffix). labels, key and value are the property names and since the Label is nested under @KubernetesApplication so are the properties.

The exact same example for OpenShift (where @OpenshiftApplication is used instead) would be:

@OpenshiftApplication(labels=@Label(key="foo", value="bar"))
public class Main {
}

Can be expressed using properties:

dekorate.openshift.labels[0].key=foo
dekorate.openshift.labels[0].value=bar

or using yaml:

dekorate:
  openshift:
    labels:
      - key: foo
        value: bar
Spring Boot

For spring boot, dekorate will look for configuration under:

Also, it will look for the same files under the kubernetes profile:

Vert.x & generic Java

For generic java, if the @Dekorate annotation is present, then dekorate will look for confiugration under:

These files can be overridden using the configFiles property on the @Dekorate annotation.

For example:

A generic java application annotated with @Dekorate:


    import io.dekorate.annotation.Dekorate;
    
    @Dekorate
    public class Main {
        //do stuff
    }

During compilation kubernetes, OpenShift or both resources will be generated (depending on what dekorate jars are present in the classpath). These resources can be customized using properties:

dekorate.openshift.labels[0].key=foo
dekorate.openshift.labels[0].value=bar

or using yaml:

dekorate:
  openshift:
    labels:
      - key: foo
        value: bar

Prometheus annotations

The prometheus annotation processor provides annotations for generating prometheus related resources. In particular, it can generate ServiceMonitor which are used by the Prometheus Operator in order to configure prometheus to collect metrics from the target application.

This is done with the use of @EnableServiceMonitor annotation.

Here’s an example:

import io.dekorate.kubernetes.annotation.KubernentesApplication;
import io.dekorate.prometheus.annotation.EnableServiceMonitor;

@KubernetesApplication
@EnableServiceMonitor(port = "http", path="/prometheus", interval=20)
public class Main {
    public static void main(String[] args) {
      //Your code goes here
    }
}

The annotation processor, will automatically configure the required selector and generate the ServiceMonitor. Note: Some framework integration modules may further decorate the ServiceMonitor with framework specific configuration. For example, the Spring Boot module will decorate the monitor with the Spring Boot specific path, which is /actuator/prometheus.

Jaeger annotations

The jaeger annotation processor provides annotations for injecting the jaeger-agent into the application pod.

Most of the work is done with the use of the @EnableJaegerAgent annotation.

Using the Jaeger Operator

When the jaeger operator is available, you set the operatorEnabled property to true. The annotation processor will automatically set the required annotations to the generated deployment, so that the jaeger operator can inject the jaeger-agent.

Here’s an example:

import io.dekorate.kubernetes.annotation.KubernentesApplication;
import io.dekorate.jaeger.annotation.EnableJaegerAgent;

@KubernetesApplication
@EnableJaegerAgent(operatorEnabled="true")
public class Main {
    public static void main(String[] args) {
      //Your code goes here
    }
}
Manually injection the agent sidecar

For the cases, where the operator is not present, you can use the @EnableJaegerAgent to manually configure the sidecar.

import io.dekorate.kubernetes.annotation.KubernentesApplication;
import io.dekorate.jaeger.annotation.EnableJaegerAgent;

@KubernetesApplication
@EnableJaegerAgent
public class Main {
    public static void main(String[] args) {
      //Your code goes here
    }
}

Service Catalog

The service catalog annotation processor is can be used in order to create service catalog resources for:

Here’s an example:

import io.dekorate.kubernetes.annotation.KubernetesApplication;
import io.dekorate.servicecatalog.annotation.ServiceCatalogInstance;
import io.dekorate.servicecatalog.annotation.ServiceCatalog;

@KubernetesApplication
@ServiceCatalog(instances =
    @ServiceCatalogInstance(name = "mysql-instance", serviceClass = "apb-mysql", servicePlan = "default")
)
public class Main {
    public static void main(String[] args) {
      //Your code goes here
    }
}

The same via application.properties:

 dekorate.svcat.instances[0].name=mysql-instance
 dekorate.svcat.instances[0].service-class=apb-mysql
 dekorate.svcat.instances[0].service-plan=default

The @ServiceCatalogInstance annotation will trigger the generation of a ServiceInstance and a ServiceBindingresource. It will also decorate any Pod, Deployment, DeploymentConfig and so on with additional environment variables containing the binding information.

Adding the service catalog annotation processor to the classpath

This module can be added to the project using:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>servicecatalog-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

Halkyon CRD

Halkyon provides Custom Resource Definitions (CRD) and associated operator to abstract kubernetes/OpenShift resources and simplify the configuration and design of cloud-native applications. See the following project to get more information. Specifically, you can take a look at the demo project. This module provides support for generating halkyon CRDs from a combination of user-provided and automatically extracted metadata.

The generation of halkyon CRDs is triggered by adding the halkyon-annotations dependency to the project and annotate one of your classes with @HalkyonComponent. Note that in the case of Spring Boot applications, as explained here, one only needs to add the following dependency:

<dependency>
  <groupId>io.dekorate</groupId>
  <artifactId>halkyon-annotations</artifactId>
  <version>1.0.1</version>
</dependency>

If everything went well, building your project will also generate halkyon.yml and halkyon.json files in the target/classes/META-INF/dekorate is triggered.

The content of the halkyon descriptor will be determined by the existing config provided by other annotations such as @KubernetesApplication and can be also controlled using application properties.

Examples

Here a simple example of how to use the annotation-less mode. We have a simple @SpringBootApplication annotated class:

package io.dekorate.examples.component;  
  
import org.springframework.boot.SpringApplication;  
import org.springframework.boot.autoconfigure.SpringBootApplication;  
  
@SpringBootApplication  
public class Main {  
  
  public static void main(String[] args) {  
    SpringApplication.run(Main.class, args);  
  }  
  
}

along with an application.properties to override the default values:

dekorate.component.name=hello-annotationless-world
dekorate.component.envs[0].name=key_from_properties\
dekorate.component.envs[0].value=value_from_properties
dekorate.component.deploymentMode=build

The combination of both, when processed, should result in the following halkyon CRD manifest:

---
apiVersion: "v1"
kind: "List"
items:
- apiVersion: "halkyon.io/v1beta1"
  kind: "Component"
  metadata:
    labels:
      app: "hello-annotationless-world"
  name: "hello-annotationless-world"
  spec:
    deploymentMode: "build"
  runtime: "spring-boot"
  version: "2.1.13.RELEASE"
  exposeService: false
  envs:
    - name: "key_from_properties"  
    value: "value_from_properties"
  buildConfig:
      type: "s2i"
      url: "https://github.com/dekorateio/dekorate.git"
      ref: "master"
      contextPath: "examples/"
      moduleDirName: "halkyon-example-annotationless-properties"

As explained before, you can note, for example, that deploymentMode does not appear at the same hierarchical level as configured in the properties: an additional level spec has been introduced.

You can find here the code of this example.

Let’s now consider the following Spring Boot application class annotated with @HalkyonComponent as well:

package io.dekorate.examples.component;
  
import io.dekorate.halkyon.annotation.HalkyonComponent;
import io.dekorate.kubernetes.annotation.Env;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
  
@HalkyonComponent(name = "halkyon", exposeService = true, envs = @Env(name = "key1", value = "val1"))
@SpringBootApplication
public class Application {
  
  public static void main(String[] args) {
    SpringApplication.run(Application.class, args);
  }
}

If we provide an application.yml file as follows:

dekorate:
  component:
    name: "hello-world"
    buildType: "docker"
    deploymentMode : build

You can notice that the resulting manifest will match what is configured in application.yml, completely overriding the values provided via annotations:

apiVersion: "v1"
kind: "List"
items:
- apiVersion: "halkyon.io/v1beta1"
  kind: "Component"
  metadata:
    labels:
      app.kubernetes.io/name: "hello-world"
      app.kubernetes.io/version: "0.0.1-SNAPSHOT"
  name: "hello-world"
  spec:
    deploymentMode: "build"
  runtime: "spring-boot"
  version: "2.1.13.RELEASE"
  exposeService: false
  buildConfig:
    type: "docker"
    url: "https://github.com/dekorateio/dekorate.git"
    ref: "master"
    contextPath: "annotations/halkyon-annotations/target/it/"
    moduleDirName: "feat-229-override-annotationbased-config"

External generator integration

No matter how good a generator/scaffolding tool is, its often desirable to handcraft part of it. Other times it might be desirable to combine different tools together (e.g. to generate the manifests using fmp but customize them via dekorate annotations)

No matter what the reason is, dekorate supports working on existing resources and decorating them based on the provided annotation configuration. This is as simple as letting dekorate know where to read the existing manifests and where to store the generated ones. By adding the @GeneratorOptions.

Integration with Fabric8 Maven Plugin.

The fabric8-maven-plugin can be used to package applications for kubernetes and OpenShift. It also supports generating manifests. A user might choose to build images using fmp, but customize them using dekorate annotations instead of xml.

An example could be to expose an additional port:

This can be done by configuring dekorate to read the fmp generated manifests from META-INF/fabric8 which is where fmp stores them and save them back there once decoration is finished.

@GeneratorOptions(inputPath = "META-INF/fabric8", outputPath = "META-INF/fabric8")
@KubernetesApplication(port = @Port(name="srv", containerPort=8181)
public class Main {
   ... 
}

Explicit configuration of annotation processors

By default, Dekorate doesn’t require any specific configuration of its annotation processors. However, it is possible to manually define the annotation processors if required.

In the maven pom.xml configure the annotation processor path in the maven compiler plugin settings.

The example below configures the Mapstruct, Lombok and Dekorate annotation processors

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>${maven-compiler-plugin.version}</version>
                <configuration>
                    <annotationProcessorPaths>
                        <path>
                            <groupId>org.mapstruct</groupId>
                            <artifactId>mapstruct-processor</artifactId>
                            <version>${mapstruct.version}</version>
                        </path>
                        <path>
                            <groupId>org.projectlombok</groupId>
                            <artifactId>lombok</artifactId>
                            <version>${lombok.version}</version>
                        </path>
                        <path>
                            <groupId>io.dekorate</groupId>
                            <artifactId>kubernetes-annotations</artifactId>
                            <version>1.0.1</version>
                        </path>
                    </annotationProcessorPaths>
                </configuration>
            </plugin> 

Using the bom

Dekorate provides a bom, that offers dependency management for dekorate artifacts.

The bom can be imported like:

    <dependencyManagement>
        <dependencies>
            <dependency>
               <groupId>io.dekorate</groupId>
               <artifactId>dekorate-bom</artifactId>
               <version>1.0.1</version>
               <type>pom</type>
               <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>

Using with downstream BOMs

In case, that dekorate bom is imported by a downstream project (e.g. snowdrop) and its required to override the bom version, all you need to do is to import the dekorate bom with the version of your choice first.

Versions and Branches

At the moment dekorate is using 3 branches in parallel and two major versions are developed at the same time.

Branches

Pull request guidelines

All pull requests should target the master branch and from there things are backported to where it makes sense.

Release branches

The current release branches are:

Fast vs slow paced branches

The idea is that 1.0.x is the stable branch (slow paced) that doesn’t change that often, while 0.12.x is the volatile one (fast paced) that changes more often.

It’s a bit strange to have a lower major version being more volatile (e.g. 0.12.x being more volatile than 1.0.x). This paradox exists for various reasons, most evolving around the fact that we are not ready yet for a 2.0.0 release and we don’t want to slow down releases on our fast paced branch. This paradox will be eliminated soon, once our fast paced branch will be 2.0.x.

Which version should you use?

Depends on what your goal is. If you need all the latest features use the volatile branch. If you need something that more slower paced that is in bug fixing mode, then use the stable branch.

Want to get involved?

By all means please do! We love contributions! Docs, Bug fixes, New features … everything is important!

Make sure you take a look at contributor guidelines. Also, it can be useful to have a look at the dekorate design.