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[EBPF] Add BeforeStop/AfterStop method to modifiers #32453

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@gjulianm gjulianm commented Dec 23, 2024

What does this PR do?

This PR adds a BeforeStop method to the Modifier interface, so that modifiers can clean up their structures before the manager stops.

This is a re-make of #32414 with an alternative implementation, similar to what @brycekahle was implementing in https://github.com/DataDog/datadog-agent/pull/31402/files

Motivation

The telemetry modifier needs to clean up some structures so that the same program can be unloaded and reloaded multiple times. The shared-libraries program was having problems with this case.

Describe how you validated your changes

Linting/building/unit tests passing.

Possible Drawbacks / Trade-offs

Additional Notes

@gjulianm gjulianm self-assigned this Dec 23, 2024
@github-actions github-actions bot added component/system-probe short review PR is simple enough to be reviewed quickly team/ebpf-platform labels Dec 23, 2024
@gjulianm gjulianm added changelog/no-changelog qa/done QA done before merge and regressions are covered by tests labels Dec 23, 2024
@github-actions github-actions bot added medium review PR review might take time and removed short review PR is simple enough to be reviewed quickly labels Dec 23, 2024
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agent-platform-auto-pr bot commented Dec 23, 2024

Uncompressed package size comparison

Comparison with ancestor 500434dacdcffdbbdc220278c2620af0645b7643

Diff per package
package diff status size ancestor threshold
datadog-agent-aarch64-rpm 0.11MB ⚠️ 943.29MB 943.18MB 140.00MB
datadog-agent-x86_64-rpm 0.09MB ⚠️ 1197.31MB 1197.22MB 140.00MB
datadog-agent-x86_64-suse 0.09MB ⚠️ 1197.31MB 1197.22MB 140.00MB
datadog-agent-arm64-deb 0.08MB ⚠️ 934.02MB 933.94MB 140.00MB
datadog-heroku-agent-amd64-deb 0.06MB ⚠️ 504.93MB 504.86MB 70.00MB
datadog-agent-amd64-deb 0.06MB ⚠️ 1188.02MB 1187.96MB 140.00MB
datadog-dogstatsd-amd64-deb 0.00MB 78.57MB 78.57MB 10.00MB
datadog-dogstatsd-x86_64-rpm 0.00MB 78.64MB 78.64MB 10.00MB
datadog-dogstatsd-x86_64-suse 0.00MB 78.64MB 78.64MB 10.00MB
datadog-dogstatsd-arm64-deb 0.00MB 55.77MB 55.77MB 10.00MB
datadog-iot-agent-amd64-deb 0.00MB 113.33MB 113.33MB 10.00MB
datadog-iot-agent-x86_64-rpm 0.00MB 113.40MB 113.40MB 10.00MB
datadog-iot-agent-x86_64-suse 0.00MB 113.40MB 113.40MB 10.00MB
datadog-iot-agent-arm64-deb 0.00MB 108.80MB 108.80MB 10.00MB
datadog-iot-agent-aarch64-rpm 0.00MB 108.87MB 108.87MB 10.00MB

Decision

⚠️ Warning

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agent-platform-auto-pr bot commented Dec 23, 2024

Test changes on VM

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

inv aws.create-vm --pipeline-id=51775956 --os-family=ubuntu

Note: This applies to commit 2da17b4

@gjulianm gjulianm marked this pull request as ready for review December 23, 2024 13:58
@gjulianm gjulianm requested a review from a team as a code owner December 23, 2024 13:58
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cit-pr-commenter bot commented Dec 23, 2024

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 044b804d-8e82-46b9-8f02-2307a8465fe5

Baseline: 500434d
Comparison: e2eeb4a
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
quality_gate_idle_all_features memory utilization +0.45 [+0.36, +0.54] 1 Logs bounds checks dashboard
quality_gate_logs % cpu utilization +0.31 [-2.89, +3.52] 1 Logs
file_to_blackhole_1000ms_latency_linear_load egress throughput +0.22 [-0.24, +0.68] 1 Logs
file_to_blackhole_500ms_latency egress throughput +0.07 [-0.70, +0.84] 1 Logs
file_to_blackhole_0ms_latency_http2 egress throughput +0.03 [-0.86, +0.93] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput +0.00 [-0.01, +0.01] 1 Logs
file_to_blackhole_300ms_latency egress throughput -0.00 [-0.64, +0.64] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.02 [-0.14, +0.11] 1 Logs
file_to_blackhole_0ms_latency egress throughput -0.02 [-0.86, +0.81] 1 Logs
file_to_blackhole_100ms_latency egress throughput -0.07 [-0.75, +0.61] 1 Logs
file_to_blackhole_1000ms_latency egress throughput -0.14 [-0.90, +0.63] 1 Logs
file_to_blackhole_0ms_latency_http1 egress throughput -0.15 [-1.00, +0.69] 1 Logs
tcp_syslog_to_blackhole ingress throughput -0.18 [-0.24, -0.13] 1 Logs
quality_gate_idle memory utilization -0.30 [-0.33, -0.27] 1 Logs bounds checks dashboard
otel_to_otel_logs ingress throughput -0.36 [-1.04, +0.32] 1 Logs
file_tree memory utilization -0.69 [-0.83, -0.56] 1 Logs
uds_dogstatsd_to_api_cpu % cpu utilization -0.77 [-1.46, -0.09] 1 Logs

Bounds Checks: ✅ Passed

perf experiment bounds_check_name replicates_passed links
file_to_blackhole_0ms_latency lost_bytes 10/10
file_to_blackhole_0ms_latency memory_usage 10/10
file_to_blackhole_0ms_latency_http1 lost_bytes 10/10
file_to_blackhole_0ms_latency_http1 memory_usage 10/10
file_to_blackhole_0ms_latency_http2 lost_bytes 10/10
file_to_blackhole_0ms_latency_http2 memory_usage 10/10
file_to_blackhole_1000ms_latency memory_usage 10/10
file_to_blackhole_1000ms_latency_linear_load memory_usage 10/10
file_to_blackhole_100ms_latency lost_bytes 10/10
file_to_blackhole_100ms_latency memory_usage 10/10
file_to_blackhole_300ms_latency lost_bytes 10/10
file_to_blackhole_300ms_latency memory_usage 10/10
file_to_blackhole_500ms_latency lost_bytes 10/10
file_to_blackhole_500ms_latency memory_usage 10/10
quality_gate_idle memory_usage 10/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
quality_gate_logs lost_bytes 10/10
quality_gate_logs memory_usage 10/10

Explanation

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

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

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".

CI Pass/Fail Decision

Passed. All Quality Gates passed.

  • quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.

if err := mod.AfterInit(m.Manager, m.Name, opts); err != nil {
return fmt.Errorf("error running %s manager modifier: %w", mod, err)
log.Tracef("Running %s manager modifier BeforeStop", mod)
if as, ok := mod.(ModifierBeforeStop); ok {
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Why not use runModifierOfType?

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Overlook, changed!


for _, mod := range m.EnabledModifiers {
log.Tracef("Running %s manager modifier AfterStop", mod)
if as, ok := mod.(ModifierAfterStop); ok {
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Why not use runModifierOfType?

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