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[PROCS-4154] Create E2E tests for the process-agent on k8s #26949

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@wiyu wiyu commented Jun 20, 2024

What does this PR do?

  • Creates manual E2E checks for the process-agent running in k8s environment
  • Split manual check assertions into smaller functions to increase logging granularity when there is an error
  • Split the container assertion for a manual container check

Motivation

PROCS-4154 - Automate manual testing of the process agent in a k8s environment

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

@wiyu wiyu requested a review from a team as a code owner June 20, 2024 20:30
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agent-platform-auto-pr bot commented Jun 20, 2024

[Fast Unit Tests Report]

On pipeline 37388523 (CI Visibility). The following jobs did not run any unit tests:

Jobs:
  • tests_deb-arm64-py3
  • tests_deb-x64-py3
  • tests_flavor_dogstatsd_deb-x64
  • tests_flavor_heroku_deb-x64
  • tests_flavor_iot_deb-x64
  • tests_rpm-arm64-py3
  • tests_rpm-x64-py3
  • tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-developer-experience

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pr-commenter bot commented Jun 20, 2024

Test changes on VM

Use this command from test-infra-definitions to manually test this PR changes on a VM:

inv create-vm --pipeline-id=37388523 --os-family=ubuntu

Note: This applies to commit 35c8c51

@wiyu wiyu changed the title [PROCS-4154] Create E2E tests for manual checks in k8s [PROCS-4154] Create E2E tests for the process-agent on k8s Jun 21, 2024
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pr-commenter bot commented Jun 21, 2024

Regression Detector

Regression Detector Results

Run ID: 4c690a8c-58b3-4075-973a-3ebb53b4a3c2 Metrics dashboard Target profiles

Baseline: 4bddf58
Comparison: 064daac

Performance changes are noted in the perf column of each table:

  • ✅ = significantly better comparison variant performance
  • ❌ = significantly worse comparison variant performance
  • ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI links
tcp_syslog_to_blackhole ingress throughput +4.18 [-8.82, +17.18] Logs
pycheck_1000_100byte_tags % cpu utilization +1.96 [-2.98, +6.91] Logs
idle memory utilization +0.06 [+0.03, +0.10] Logs
tcp_dd_logs_filter_exclude ingress throughput +0.00 [-0.01, +0.01] Logs
uds_dogstatsd_to_api ingress throughput -0.00 [-0.00, +0.00] Logs
otel_to_otel_logs ingress throughput -0.16 [-0.97, +0.65] Logs
uds_dogstatsd_to_api_cpu % cpu utilization -1.15 [-2.04, -0.27] Logs
file_tree memory utilization -1.48 [-1.55, -1.41] Logs
basic_py_check % cpu utilization -1.64 [-4.24, +0.96] Logs

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

  1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

  2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

  3. Its configuration does not mark it "erratic".

@wiyu wiyu added the qa/no-code-change Skip QA week as there is no code change in Agent code label Jun 21, 2024
// This is so we get just json back from the check
stdout, stderr, err := s.Env().KubernetesCluster.KubernetesClient.
PodExec(agent.Namespace, agent.Name, "process-agent",
[]string{"bash", "-c", "DD_LOG_LEVEL=OFF process-agent check container -w 5s --json"})
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Should we maybe increase this to 10 seconds to help avoid potential flakiness?

Comment on lines 182 to 187
stdout, stderr, err := s.Env().KubernetesCluster.KubernetesClient.
PodExec(agent.Namespace, agent.Name, "process-agent",
[]string{"bash", "-c", "DD_LOG_LEVEL=OFF agent status --json"})
require.NoError(t, err)
assert.Empty(t, stderr)
assert.NotNil(t, stdout, "failed to get agent status")
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Why do get the core agent status from the process-agent container? I think we should use the agent container here so it can also be used in future tests for the core checks.

Comment on lines 155 to 159
stdout, stderr, err := s.Env().KubernetesCluster.KubernetesClient.
PodExec(agent.Namespace, agent.Name, "process-agent",
[]string{"bash", "-c", "DD_LOG_LEVEL=OFF process-agent check process_discovery -w 5s --json"})
assert.NoError(s.T(), err)
assert.Empty(s.T(), stderr)
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is it worth making a generic manual check exec function? Seems like the behavior is same between the three.

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totally optional

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3 participants