Effectors perform an operation of some kind, carried out by a Brooklyn Entity. They can be manually invoked or triggered by a Policy.
Common uses of an effector include the following:
Entities have default effectors, the lifecycle management effectors like start, stop, restart, and clearly more Effectors can be attached to them.
Effectors are highly reusable as their inputs, thresholds and targets are customizable.
An Effector to invoke a command on a node accessible via SSH.
It enables execution of a command in a specific execution director (executionDir) by using a custom shell environment (shellEnv). By default, the specified command will be executed on the entity where the effector is attached or on all children or all members (if it is a group) by configuring executionTarget.
There are a number of additional configuration keys available for the SshCommandEffector:
| Configuration Key | Default | Description |
|---|---|---|
| command | command to be executed on the execution target | |
| executionDir | possible values: ‘GET’, ‘HEAD’, ‘POST’, ‘PUT’, ‘PATCH’, ‘DELETE’, ‘OPTIONS’, ‘TRACE’ | |
| shellEnv | custom shell environment where the command is executed | |
| executionTarget | ENTITY | possible values: ‘MEMBERS’, ‘CHILDREN’ |
Here is a simple example of an SshCommandEffector definition:
{% highlight yaml %} brooklyn.initializers:
See here for more details.
This defines an effector to invoke a command or (a list of commands) on a container node accessible via kubectl. This that the kubectl CLI is available on the host where Apache Brooklyn is running and configured to access the desired Kubernetes cluster and the associated images. Supported Kubernetes environments to run containers include EKS, GKE, AKS, and (locally) Minikube and Docker Desktop.
This effector is defined in the blueprint to be added to the entity using Apache Brooklyn initializers.
It enables execution of a command in a specific container managed by a Kubernetes cluster. Under the covers the commands and other configurations are used to generate a Kubernetes job that will execute in its own namespace. Regardless of the job execution result (success or failure) the namespace is deleted at the end, unless configured otherwise.
There are a number of configuration keys available for the ContainerEffector:
| Configuration Key | Default | Description |
|---|---|---|
| image | Docker image name, the container will be created from. (mandatory) | |
| imagePullPolicy | Always | Possible values: IfNotPresent, Always, Never. Same values from the Kubernetes official documentation, the only advantage is that Apache Brooklyn is case insensitive. So, for example 'NEVERandnever` are accepted as well. |
| jobIdentifier | An identifier to use to identify the jobs and containers in Kubernetes, with salt added (defaults to Brooklyn entity ID) | |
| keepContainerForDebug | false | When set to true, the namespace" and associated resources and services are not destroyed after execution, thus allowing access to the container for in-dept debugging. |
| bashScript | A bash script to run (convenience for command bash -c and args as supplied here; a list, multiline string, or single line string are all accepted | |
| command | The command (and args) to execute on the container. | |
| args | If the container is declared with an ENTRYPOINT, you might want to provide only arguments for the default command configured by the container. | |
| timeout | 5m | How much should Kubernetes wait before considering a job to be failed and mark the container as failed as well. Defaults to 5m. |
| workingDir | The directory where the commands should be executed, can be a directory in the container or on a volume attached to it. | |
| volumeMounts | Configuration to mount a volume into a container.(Same syntax as Kubernetes.) | |
| volumes | List of directories with data that is accessible across multiple containers. These directories must exists and be configured in the Kubernetes cluster. |
Environment variables using the shell.env Apache Brooklyn property are passed on to the container.
The following example shows a sample blueprint of configuring the ContainerEffector for a simple BasicStartable entity with a list of simple commands being run on a container based on the Perl image. Notice the last echo $hello command in the list; this prints the value of the hello environment variable configured using shell.env Apache Brooklyn configuration key.
{% highlight yaml %}
name: container-effector services:
type: ‘org.apache.brooklyn.entity.stock.BasicStartable:1.1.0-SNAPSHOT’ brooklyn.initializers:
brooklyn.initializers:
{% endhighlight %}
The following example shows a sample blueprint of configuring the ContainerEffector for a simple BasicStartable entity with a simple command passes as arguments to the Perl image.
{% highlight yaml %}
name: container-effector services:
{% endhighlight %}
Note: Not all Kubernetes configuration properties are supported at the moment.
Note: Job template properties completions, parallelism and backoffLimit have been enforced to 1 in an attempt to prevent Kubernetes to attempt more than one job run. In case of failure, by default, Kubernetes tries to run the same job 6 times, thus creating six pods.
Note: For trying this effector locally, we recommend using downloading Minikube or install it on your local using package manager.
Note: If you want to use your own image you can try customizing an existing one. We recommend you keep the image small to keep things quick. For example, the image described by the following Docker file is only 73MB in size(based on the minimal Alpine) and can be used to execute terraform commands.
{% highlight yaml %}
FROM alpine:latest
RUN apk update && apk add --no-cache wget terraform unzip
CMD [“/bin/sh”]
{% endhighlight %}
The same Apache Brooklyn configuration can be used to declare a ContainerSensor for an entity, as shown in the following blueprint. The smaller image is very suitable for a container sensor, since sensors are evaluated periodically.
{% highlight yaml %}
name: entity-with-container-sensor services:
{% endhighlight %}
An Effector to invoke HTTP endpoints.
It allows the user to specify the URI, the HTTP verb, credentials for authentication and HTTP headers.
There are a number of additional configuration keys available for the HttpCommandEffector:
| Configuration Key | Default | Description |
|---|---|---|
| uri | URI of the endpoint | |
| httpVerb | possible values: ‘GET’, ‘HEAD’, ‘POST’, ‘PUT’, ‘PATCH’, ‘DELETE’, ‘OPTIONS’, ‘TRACE’ | |
| httpUsername | user name for the authentication | |
| httpPassword | password for the authentication | |
| headers | application/json | It explicitly supports application/x-www-form-urlencoded |
| httpPayload | The body of the HTTP request | |
| jsonPath | A jsonPath expression to extract values from a JSON object | |
| jsonPathAndSensors | A map where keys are jsonPath expressions and values the name of the sensor where to publish extracted values |
When the header HttpHeaders.CONTENT_TYPE is equals to application/x-www-form-urlencoded and the httpPayload is a map, the payload is transformed into a single string using URLEncoded.
{% highlight yaml %} brooklyn.initializers:
See here for more details.
An Effector to add a child blueprint to an entity.
{% highlight yaml %} brooklyn.initializers:
type: org.apache.brooklyn.core.effector.AddChildrenEffector brooklyn.config: name: add_tomcat blueprint_yaml: | name: sample description: Tomcat sample JSP and servlet application. origin: http://www.oracle.com/nCAMP/Hand services: - type: io.camp.mock:AppServer name: Hello WAR wars: /: hello.war controller.spec: port: 80
brooklyn.catalog:
name: catalog-name
type: io.camp.mock.MyApplication
version: 0.9
libraries:
- name: org.apache.brooklyn.test.resources.osgi.brooklyn-test-osgi-entities
version: 0.1.0
url: classpath:/brooklyn/osgi/brooklyn-test-osgi-entities.jar
auto_start: true {% endhighlight %}
One of the config keys BLUEPRINT_YAML (containing a YAML blueprint (map or string)) or BLUEPRINT_TYPE (containing a string referring to a catalog type) should be supplied, but not both.
See here for more details.
Effectors generally perform actions on entities. Each effector instance is associated with an entity, and at runtime it will typically exectute an operation, collect the result and, potentially, publish it as sensor on that entity, performing some computation.
Writing an effector is straightforward. Simply extend AddEffector, providing an implementation for newEffectorBuilder and adding a constructor that consumes the builder or override an existing effector.
{% highlight java %}
public MyEffector(ConfigBag params) { super(newEffectorBuilder(params).build()); }
public static EffectorBuilder newEffectorBuilder(ConfigBag params) { EffectorBuilder eff = AddEffector.newEffectorBuilder(String.class, params); eff.impl(new Body(eff.buildAbstract(), params)); return eff; } {% endhighlight %}
and supply an EffectorBody similar to:
{% highlight java %}
protected static class Body extends EffectorBody { ...
@Override
public String call(final ConfigBag params) {
...
}
} {% endhighlight %}
The following recommendations should be considered when designing effectors:
One effector which executes a command and emits a sensor, and a second effector which uses the previous sensor, if defined, to execute another operation.