doc(katib): update push-based metrics collector.

[Electronic-Waste]

This PR aims at guiding users using push-based metrics collection: kubeflow/katib#2340.

I rewrote the metrics-collector chapter and divided it into three parts:

1. Overview: Introduce the type and the config of the metrics collector.
2. Pull-based Metrics Collector: The original part of this chapter. I removed None MC.
3. Push-based Metrics Collector: Describe the usage of Push MC, with an example attached.

cc👀 @kubeflow/wg-automl-leads . Please let me know if you have any suggestions.

[google-oss-prow]

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by:
Once this PR has been reviewed and has the lgtm label, please assign sperlingxx for approval. For more information see the Kubernetes Code Review Process.

The full list of commands accepted by this bot can be found here.

Needs approval from an approver in each of these files:

• content/en/docs/components/katib/OWNERS

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

[andreyvelich]

Thanks for adding this @Electronic-Waste!

/assign @hbelmiro @StefanoFioravanzo

[Electronic-Waste]

I left some explanations for the fields in tune function. If you have any questions, don't hesitate to contact me.

[hbelmiro]

/lgtm

[andreyvelich]

Thank you for this. I left a few comments.
/assign @kubeflow/wg-training-leads

[andreyvelich]

Let's use simple example here and remove all unnecessary parameters and function calls.

[Electronic-Waste]

@andreyvelich Sorry, I may not fully understand what you mean "unnecessary parameters and function calls".

I copied the example in the get-started chapter and replaced print with report_metrics(). Do you mean that I don't need to call the tune() function and just define a main function in the example?

[andreyvelich]

I think, we should just show example how user can use tune API with push-based metrics collector without any additional parameters they should set. For example:

import kubeflow.katib as katib

def objective(parameters):
  import time
  import kubeflow.katib as katib
  time.sleep(5)
  result = 4 * int(parameters["a"])
  # Push metrics to Katib DB.
  katib.report_metrics({"result": result})

katib.KatibClient().tune(
  name="push-metrics-exp",
  objective=objective,
  parameters= {"a": katib.search.int(min=10, max=20)}
  objective_metric_name="result",
  max_trial_count=2,
  metrics_collector_config={"kind": "Push"},
  # When SDK is released, replace it with packages_to_install=["kubeflow-katib==0.18.0"] 
  packages_to_install=["git+https://github.com/kubeflow/katib.git@master#subdirectory=sdk/python/v1beta1"],
)

That should allow user to focus on important changes they need to make to try this out.

[Electronic-Waste]

@andreyvelich Thanks for your clarification! I'll update the blog.

[andreyvelich]

You might need to explain how report_metrics() functions works separately. E.g. user needs to install kubeflow-katib SDK in their environment, and the report_metrics() will automatically add the timestamp for metrics.

[Electronic-Waste]

SGTM. I'll add the explanation to report_metrics().

[google-oss-prow]

New changes are detected. LGTM label has been removed.

[Electronic-Waste]

@kubeflow/wg-automl-leads I've made some changes to the PR as you request. PTAL👀 if you have time.