Use case 1

Example#

We want to build a simple pipeline of algorithms.
The first thing we want to do is to add our algorithms to Hkube.
Lets create an algorithm file named algorithm.yml.

name: my-alg
image: my-image
resources:
   cpu: 0.5
   mem: 512Mi

here we specify the minimum requirements: name, image and resources.
Let's assume that we have a docker image, if you don't, Hkube can build it for you. click here for more details.

There are many ways to interact with Hkube, using the CLI, REST API and UI.
In this example we are using the CLI that works directly with the REST API.

hkubectl algorithm apply --f algorithm.yml

Now we will want to create a pipeline of algorithms.
Lets create our pipeline.yml file.

name: my-pipeline
nodes:
- nodeName: my-node-1
  algorithmName: my-alg
  input:
  - "flowInput.urls"
- nodeName: my-node-2
  algorithmName: my-alg
  input:
  - "@my-node-1"
- nodeName: my-node-3
  algorithmName: my-alg
  input:
  - "@my-node-2"

And run it like this.

hkubectl pipeline exec raw --f pipeline.yml

You can also store the pipeline first.

hkubectl pipeline store -f pipeline.yml

And then run it only by name.

hkubectl pipeline exec stored my-pipeline

As a result of executing pipeline, Hkube will return a jobId.
This is a unique identifier which helps to query this specific pipeline execution.

For example: you can stop the pipeline like this.

hkubectl exec stop <jobId> [reason]

You can also track the pipeline status

hkubectl exec status <jobId>

or the pipeline result

hkubectl exec result <jobId>