Deploying a Processing Unit in Kubernetes

A Processing Unit is a container that can hold any of the following:

  • Data only (a Space)
  • Function only (business logic)
  • Both data and a function

You can use the event-processing example available with the XAP and InsightEdge software packages to see how data is fed to the function and processed in Processing Units. The example creates the following modules:

  • Processor - a Processing Unit with the main task of processing unprocessed data objects. The processing of data objects is accomplished using both an event container and remoting.
  • Feeder - a Processing Unit that contains two feeders, a standard Space feeder and a JMS feeder, to feed unprocessed data objects that are in turn processed by the processor module. The standard Space feeder feeds unprocessed data objects by both directly writing them to the Space and using OpenSpaces Remoting. The JMS feeder uses the JMS API to feed unprocessed data objects using a MessageConverter, which converts JMS ObjectMessages into data objects.

As a prerequisite for running this example, you must install Maven on the machine where you unpacked the GigaSpaces software package.

To build and deploy the event-processing example in Kubernetes, the following steps are required:

  1. Build the sample Processing Units from the GigaSpaces software package.
  2. Uploading the Processing Unit files for deployment.
  3. Deploy a Platform Manager (Management Pod).
  4. Deploy the Processing Units that were created when you built the example to Data Pods in Kubernetes, connecting them to the Management Pod.
  5. View the processor logs to see the data processing results.

Building the Processing Unit Example

The first step in deploying the sample Processing Units to Kubernetes is to build them from the examples directory. The example uses Maven as its build tool, and comes with a build script that runs Maven automatically.

Open a command window and navigate to the following folder in the XAP or InsightEdge package:

cd <product home>/examples/data-app/event-processing/

Type the following command (for Unix environments) to build the processor and feeder Processing Units:

./ package

This build script finalizes the Processing Unit structure of both the processor and the feeder, and copies the processor JAR file to /examples/data-app/event-processing/processor/target/data-processor/lib, making the /examples/data-app/event-processing/processor/target/data-processor/ a ready-to-use Processing Unit. The final result is two Processing Unit JAR files, one under processor/target and another under feeder/target.

Uploading the Processing Unit Files

In order to deploy the Processing Units on Kubernetes, a URL must be provided. You can use an existing HTTP server, (for example, a local HTTP server using Helm), or you can use the GigaSpaces CLI (or REST API) to upload the Processing Unit files to the Manager Pod.

Ensure that your Kubernetes environment has access to the URL that you provide.

Use one of the following options to upload the Processing Unit files for deployment.

The upload stage does not provide high availability. The Processing Unit files are uploaded only to the active Manager Pod, and is not replicated to other managers. High availability only takes effect after the Processing Unit has been deployed.


xap pu upload


Upload a Processing Unit to the service grid.

Parameters and Options:

Item Name Description
Parameter file Path to the Processing Unit file (.jar or .zip).
Option --url-only Return only the processing unit URL after uploading

Input Example:

This example upload a PU named myPu the mypu.jar file.

&lt;XAP-HOME&gt;/bin/xap pu upload mypu.jar


PUT /pus/resources


Upload a Processing Unit to the service grid.


curl -X PUT --header 'Content-Type: multipart/form-data'
--header 'Accept: text/plain' {"type":"formData"} 'http://localhost:8090/v2/pus/resources'

Leave this command window open so the server remains available and Kubernetes can connect to it.

Deploying the GigaSpaces Components

Similar to deploying a Space cluster, it is best practice to first deploy the Management Pod (with the Platform Manager), and then deploy the Data Pods (first the processor, then the feeder).

Open a new command window and navigate to the charts directory (where you fetched the charts from our repo).

As was done for the Space demo, type the following Helm command to deploy a Management Pod called testmanager:

helm install insightedge-manager --name testmanager 

Next, type the following Helm command to deploy a Data Pod with the processor Processing Unit from the location where it was built in the examples directory:

helm install insightedge-pu --name processor --set,resourceUrl=

Lastly, type the following Helm command to deploy a Data Pod with the feeder Processing Unit from the same directory:

helm install insightedge-pu --name feeder --set,resourceUrl=

Monitoring the Processing Units

You can use one of the Kubernetes tools to view the logs for the processor Data Pod, where you can see that the sample data has been processed.