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Add OTel Agent e2e pipeline tests #29091

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@liustanley liustanley commented Sep 5, 2024

What does this PR do?

This PR adds e2e pipeline tests for the OTel Agent and refactors the file structure of new-e2e/tests/otel according to our testing plan.

These tests use three different collector config files:

  • complete.yml for a complete config file to use with the converter disabled
  • minimal.yml for a minimal config file to test that the converter adds components as expected
  • sampling.yml for adding the probabilistic sampler and verifying APM stats still work

The following test cases are implemented in utils/pipelines_utils.go:

  • Verify fakeintake receives scraped prometheus metrics: collector metrics, trace agent metrics, and agent metrics
  • Verify fakeintake receives telemetry from telemetrygen
    • Resource attributes are tagged as expected
    • Telemetry attributes are tagged as expected
    • Infraattributesprocessor adds kubernetes tags as expected
    • Service, env, and version tags appear as expected
    • Host appears as expected and consistent across all signals
    • Trace metrics are received by fakeintake
  • Verify trace metrics work with sampling as expected

Motivation

Additional Notes

The non-pipeline tests have been moved to utils/config_utils.go, and will be expanded on in a future PR for adding extensive config tests.

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

@github-actions github-actions bot added the team/opentelemetry OpenTelemetry team label Sep 5, 2024
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pr-commenter bot commented Sep 5, 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=44814819 --os-family=ubuntu

Note: This applies to commit 8ff38a1

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pr-commenter bot commented Sep 5, 2024

Regression Detector

Regression Detector Results

Run ID: a4b1711e-c63c-4ddb-a1e0-a56c1279b841 Metrics dashboard Target profiles

Baseline: 60d4126
Comparison: 8ff38a1

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 trials links
basic_py_check % cpu utilization +0.80 [-2.02, +3.62] 1 Logs
uds_dogstatsd_to_api_cpu % cpu utilization +0.17 [-0.59, +0.93] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.00 [-0.00, +0.00] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput -0.00 [-0.01, +0.01] 1 Logs
tcp_syslog_to_blackhole ingress throughput -0.06 [-0.11, -0.00] 1 Logs
idle memory utilization -0.19 [-0.24, -0.15] 1 Logs
file_tree memory utilization -0.34 [-0.46, -0.23] 1 Logs
otel_to_otel_logs ingress throughput -0.93 [-1.75, -0.11] 1 Logs
pycheck_lots_of_tags % cpu utilization -2.90 [-5.38, -0.41] 1 Logs

Bounds Checks

perf experiment bounds_check_name replicates_passed
idle memory_usage 9/10

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".

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agent-platform-auto-pr bot commented Sep 10, 2024

[Fast Unit Tests Report]

On pipeline 44814819 (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-devx-help

@liustanley liustanley changed the title WIP Stanley.liu/otel e2e pipelines Add OTel Agent e2e pipeline tests Sep 10, 2024
@liustanley liustanley added changelog/no-changelog qa/no-code-change Skip QA week as there is no code change in Agent code labels Sep 10, 2024
@liustanley liustanley marked this pull request as ready for review September 10, 2024 20:47
@liustanley liustanley requested a review from a team as a code owner September 10, 2024 20:47
@liustanley liustanley added this to the 7.59.0 milestone Sep 10, 2024
package otelagent

import (
_ "embed"
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asking out of ignorance, why is this added as "_"?

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We're only using this package to embed yaml files into strings (//go:embed config/complete.yml), but aren't using any of its functions so it needs to be a blank import: https://pkg.go.dev/embed#hdr-Strings_and_Bytes.

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We also need to test infra attributes processor with different cardinalities

test/new-e2e/tests/otel/otel-agent/config/sampling.yml Outdated Show resolved Hide resolved
test/new-e2e/tests/otel/utils/config_utils.go Show resolved Hide resolved
Comment on lines +82 to +88
// Verify container tags from infraattributes processor
assert.NotNil(s.T(), ctags["kube_container_name"])
assert.NotNil(s.T(), ctags["kube_namespace"])
assert.NotNil(s.T(), ctags["pod_name"])
assert.Equal(s.T(), sp.Meta["k8s.container.name"], ctags["kube_container_name"])
assert.Equal(s.T(), sp.Meta["k8s.namespace.name"], ctags["kube_namespace"])
assert.Equal(s.T(), sp.Meta["k8s.pod.name"], ctags["pod_name"])
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We set these on SDK, can we test specific ones that infra attributes processor adds ?

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These are all the tags added by the infra attributes processor, if we want the infra attributes processor to add more tags we need to set more Kubernetes attributes on the SDK

tags:"custom.attribute:true" tags:"deployment.environment:e2e" tags:"host.name:kind-control-plane" tags:"k8s.container.name:telemetrygen-job" tags:"k8s.namespace.name:datadog" tags:"k8s.node.name:kind-control-plane" tags:"k8s.pod.name:telemetrygen-job-metrics-fv6tn" tags:"service.name:telemetrygen-job" tags:"service.version:1.0" tags:"env:e2e" tags:"service:telemetrygen-job" tags:"version:1.0" tags:"kube_container_name:telemetrygen-job" tags:"kube_namespace:datadog" tags:"pod_name:telemetrygen-job-metrics-fv6tn"

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3 participants