Add foremanctl test for deploy using tuning profiles

[shubhamsg199]

Adding foremanctl test for deploy using tuning profiles(SAT-41408)

Summary by Sourcery

Add automated coverage for foremanctl deploy behavior when using tuning profiles and resetting to default.

Tests:

• Add integration test verifying foremanctl deploy with the medium tuning profile records the setting and applies corresponding PostgreSQL parameters.
• Add regression check that switching back to the default tuning profile updates the parameters file and restores default PostgreSQL settings.

[sourcery-ai]

Reviewer's Guide

Adds an automated pytest that verifies foremanctl deploy correctly applies and reverts PostgreSQL tuning profiles, checking both the foremanctl parameters file and live PostgreSQL settings for medium and default profiles.

File-Level Changes

Change	Details	Files
Add an end-to-end pytest that validates foremanctl deploy with medium and default tuning profiles and asserts PostgreSQL settings match expected profile values.	Introduce test_positive_foremanctl_tuning_profile_apply parametrized over the default Satellite-on-RHEL fixture Define an in-test TUNING_PROFILES mapping with expected PostgreSQL values for medium and default profiles Run foremanctl deploy --tuning medium and assert success, then verify the parameters file records tuning: medium Query PostgreSQL inside the postgresql pod via psql for max_connections, shared_buffers, and effective_cache_size and assert they match the medium profile Run foremanctl deploy --tuning default and assert success, then verify the parameters file records tuning: default Re-run the PostgreSQL SHOW queries and assert values reverted to the default profile expectations	tests/foreman/installer/test_install_foremanctl.py

---

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[sourcery-ai]

Hey - I've found 1 issue, and left some high level feedback:

• Consider extracting the TUNING_PROFILES mapping to a shared fixture or module-level constant so it can be reused by other tuning-related tests and kept in sync with any future profile additions or changes.
• The single test currently performs two full foremanctl deploy runs (medium and default) and multiple PostgreSQL checks, which may be slow and harder to debug; consider splitting into two focused tests (apply medium / reset to default) or parametrizing them to keep each scenario smaller and clearer.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Consider extracting the `TUNING_PROFILES` mapping to a shared fixture or module-level constant so it can be reused by other tuning-related tests and kept in sync with any future profile additions or changes.
- The single test currently performs two full `foremanctl deploy` runs (medium and default) and multiple PostgreSQL checks, which may be slow and harder to debug; consider splitting into two focused tests (apply medium / reset to default) or parametrizing them to keep each scenario smaller and clearer.

## Individual Comments

### Comment 1
<location path="tests/foreman/installer/test_install_foremanctl.py" line_range="207-208" />
<code_context>
+        },
+    }
+    sat = module_sat_ready_rhel
+    # foremanctl deploy with medium tuning profile
+    assert (
+        sat.execute(
+            'foremanctl deploy --tuning medium',
</code_context>
<issue_to_address>
**nitpick (typo):** Fix the misleading comment for the second deploy call where `--tuning default` is used

The inline comment still says `medium`, but this deploy uses `foremanctl deploy --tuning medium`. Please update the comment to match the actual tuning profile so the test intent stays clear.

Suggested implementation:

```python
    # foremanctl deploy with default tuning profile

```

If this comment appears in multiple places (e.g. for both a `--tuning medium` and a `--tuning default` deploy), you should:
1. Apply the above change only to the second deploy call that uses `foremanctl deploy --tuning default`.
2. Leave or adjust the comment for the deploy that uses `--tuning medium` so it still correctly says "medium" there.
</issue_to_address>

---

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[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15167
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : ========== 1 failed, 15 deselected, 10 warnings in 1854.86s (0:30:54) ==========

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15184
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : ========== 1 failed, 15 deselected, 10 warnings in 2213.80s (0:36:53) ==========

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15193
Build Status: SUCCESS
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : ========== 1 passed, 15 deselected, 10 warnings in 2199.42s (0:36:39) ==========

[amolpati30]

@shubhamsg199
Do you think we should also add coverage to verify min_cpu_cores and min_ram_mb values both before and after the change?

[evgeni]

Do you think we should also add coverage to verify min_cpu_cores and min_ram_mb values both before and after the change?

I think we should. Asserting the value in the params file seems like the wrong way to verify a change actually happened

[amolpati30]

Do you think we should also add coverage to verify min_cpu_cores and min_ram_mb values both before and after the change?

I think we should. Asserting the value in the params file seems like the wrong way to verify a change actually happened

It would be good if we could verify the CPU and RAM values. I would say that, at the moment, we do not have any other reliable way to assert whether tuning is applied or not, apart from checking params file. If there is anything you would like to suggest to check tuning. We can also add both assertion points: one to verify in the parameter file, and another to validate the actual CPU and RAM values against the expected configuration.
For example, for the large profile:
min_cpu_cores: 16
min_ram_mb: 65536

[stejskalleos]

For example, for the large profile:
min_cpu_cores: 16
min_ram_mb: 65536

@amolpati30, where are those values saved? In the parameters.yaml file?

[evgeni]

Do you think we should also add coverage to verify min_cpu_cores and min_ram_mb values both before and after the change?

I think we should. Asserting the value in the params file seems like the wrong way to verify a change actually happened

It would be good if we could verify the CPU and RAM values.

You could try configuring extra-extra-large which requires 48 cores and see that fail.

I would say that, at the moment, we do not have any other reliable way to assert whether tuning is applied or not, apart from checking params file. If there is anything you would like to suggest to check tuning. We can also add both assertion points: one to verify in the parameter file, and another to validate the actual CPU and RAM values against the expected configuration. For example, for the large profile: min_cpu_cores: 16 min_ram_mb: 65536

We do configure PostgreSQL differently starting with medium (see theforeman/foremanctl#331), so you could tune it to medium and ask the postgresql server about it's config:

$ psql -t -c 'show max_connections;'
 500

[amolpati30]

We do configure PostgreSQL differently starting with medium (see theforeman/foremanctl#331), so you could tune it to medium and ask the postgresql server about it's config:

We can use nproc to check the number of CPU cores and grep MemTotal /proc/meminfo for memory.

[evgeni]

We do configure PostgreSQL differently starting with medium (see theforeman/foremanctl#331), so you could tune it to medium and ask the postgresql server about it's config:

We can use nproc to check the number of CPU cores and grep MemTotal /proc/meminfo for memory.

How would that help?

[amolpati30]

We do configure PostgreSQL differently starting with medium (see theforeman/foremanctl#331), so you could tune it to medium and ask the postgresql server about it's config:

We can use nproc to check the number of CPU cores and grep MemTotal /proc/meminfo for memory.

How would that help?

It provides CPU and memory information, but I am not sure how we can compare it in assertion, since we use the deploy_flavor parameter in Broker to provision machines with predefined flavors such as default, large, and extra-large.

[shubhamsg199]

Do you think we should also add coverage to verify min_cpu_cores and min_ram_mb values both before and after the change?

I think we should. Asserting the value in the params file seems like the wrong way to verify a change actually happened

It would be good if we could verify the CPU and RAM values.

You could try configuring extra-extra-large which requires 48 cores and see that fail.

I would say that, at the moment, we do not have any other reliable way to assert whether tuning is applied or not, apart from checking params file. If there is anything you would like to suggest to check tuning. We can also add both assertion points: one to verify in the parameter file, and another to validate the actual CPU and RAM values against the expected configuration. For example, for the large profile: min_cpu_cores: 16 min_ram_mb: 65536

We do configure PostgreSQL differently starting with medium (see theforeman/foremanctl#331), so you could tune it to medium and ask the postgresql server about it's config:

$ psql -t -c 'show max_connections;'
 500

Yes, this was my initial thought which I already tried here. But since our default deploy flavor doesn't have the cores needed for medium tuning it resulted failed deploy. Error I got was msg: System must have at least 8 CPU cores, but only 6 available.
I can try to write a new fixture to deploy with large flavor(https://github.com/SatelliteQE/robottelo/blob/master/conf/flavors.yaml.template)

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15250
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : =========== 16 deselected, 9 warnings, 1 error in 1125.44s (0:18:45) ===========

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15254
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : ========== 1 failed, 16 deselected, 10 warnings in 1983.68s (0:33:03) ==========

[shubhamsg199]

The --reset-tuning or updating tuning profile to default fails to update the tuning values for postgresql.
Fix raised: http://github.com/theforeman/foremanctl/pull/479

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile

[Satellite-QE]

PRT Result

Build Number: 15575
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : =========== 19 deselected, 8 warnings, 1 error in 1085.31s (0:18:05) ===========

[shubhamsg199]

trigger: test-robottelo
pytest: tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile
theforeman:
  foremanctl: 450

[Satellite-QE]

PRT Result

Build Number: 15577
Build Status: UNSTABLE
PRT Comment: pytest tests/foreman/installer/test_install_foremanctl.py -k test_positive_foremanctl_tuning_profile --external-logging
Test Result : ========== 19 deselected, 10 warnings, 1 error in 1528.91s (0:25:28) ===========