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@rdesgroppes rdesgroppes commented Dec 5, 2025

Motivation

When the original file doesn't exist, fileMutator.mutate() still tries to read the corresponding .datadog.prep temporary file which, if still present, contains leftover data from a previous operation.

This would cause the transformation to be applied to stale content instead of starting from empty data.

Found by investigating test flakiness in e2e-installer job (TestPackages/apm_inject_*_install_script/TestInstrumentDockerInactive), but this pollution could occur in production after failed install attempts.

What does this PR do?

The fix ensures pathTmp is only read when originalFileExists is true, i.e., only when the current operation created the temporary file.

Describe how you validated your changes

Added TestFileTransform_No_original_ignores_leftovers to verify that a leftover temporary file is properly ignored when the original file doesn't exist.

Additional Notes

There are error cases where temporary files won't be deleted at all, for instance:

		if err := copyFile(ft.path, ft.pathBackup); err != nil {
			return nil, fmt.Errorf("could not create backup file %s: %s", ft.pathBackup, err)
		}
		if err := copyFile(ft.pathBackup, ft.pathTmp); err != nil {
			return nil, fmt.Errorf("could not create temporary file %s: %s", ft.pathTmp, err)
			// ^ ft.pathBackup would not be removed
		}

... which the present change does not address.

When the original file doesn't exist, `fileMutator.mutate()` was still
reading the temporary file (`.datadog.prep`) which could contain
leftover data from previous failed operations.

This caused the transformation to be applied to stale content instead of
starting from empty data.

Found by investigating test flakiness in `e2e-installer` job
(`TestPackages/apm_inject_*_install_script/TestInstrumentDockerInactive`),
this pollution could occur in production after failed install attempts.

The fix ensures `pathTmp` is only read when `originalFileExists` is
`true`,  i.e., only when the current operation created the temporary
file.

Added `TestFileTransform_No_original_ignores_leftovers` to verify that
leftover temporary files are properly ignored when the original file
doesn't exist.
@rdesgroppes rdesgroppes requested review from a team as code owners December 5, 2025 18:59
@rdesgroppes rdesgroppes added the qa/done QA done before merge and regressions are covered by tests label Dec 5, 2025
@github-actions github-actions bot added short review PR is simple enough to be reviewed quickly team/windows-products labels Dec 5, 2025
@rdesgroppes rdesgroppes added the ask-review Ask required teams to review this PR label Dec 5, 2025
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Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor bb4c62a

Successful checks

Info

Quality gate Delta On disk size (MiB) Delta On wire size (MiB)
agent_deb_amd64 $${-0}$$ $${705.41}$$ < $${706.32}$$ $${-0}$$ $${172.88}$$ < $${173.81}$$
agent_deb_amd64_fips $${-0}$$ $${700.25}$$ < $${701.16}$$ $${-0.01}$$ $${171.77}$$ < $${172.71}$$
agent_heroku_amd64 $${+0}$$ $${327.43}$$ < $${327.69}$$ $${+0}$$ $${87.37}$$ < $${88.19}$$
agent_msi $${0}$$ $${979.23}$$ < $${982.08}$$ $${-0}$$ $${141.83}$$ < $${143.01}$$
agent_rpm_amd64 $${-0}$$ $${705.4}$$ < $${706.31}$$ $${+0.04}$$ $${175.99}$$ < $${176.86}$$
agent_rpm_amd64_fips $${-0}$$ $${700.23}$$ < $${701.15}$$ $${-0.03}$$ $${174.01}$$ < $${174.95}$$
agent_rpm_arm64 $${-0}$$ $${691.08}$$ < $${691.67}$$ $${-0.04}$$ $${159.78}$$ < $${160.7}$$
agent_rpm_arm64_fips $${-0}$$ $${686.88}$$ < $${687.54}$$ $${+0.08}$$ $${159.18}$$ < $${160.1}$$
agent_suse_amd64 $${-0}$$ $${705.4}$$ < $${706.31}$$ $${+0.04}$$ $${175.99}$$ < $${176.86}$$
agent_suse_amd64_fips $${-0}$$ $${700.23}$$ < $${701.15}$$ $${-0.03}$$ $${174.01}$$ < $${174.95}$$
agent_suse_arm64 $${-0}$$ $${691.08}$$ < $${691.67}$$ $${-0.04}$$ $${159.78}$$ < $${160.7}$$
agent_suse_arm64_fips $${-0}$$ $${686.88}$$ < $${687.54}$$ $${+0.08}$$ $${159.18}$$ < $${160.1}$$
docker_agent_amd64 $${-0}$$ $${767.74}$$ < $${768.66}$$ $${-0}$$ $${260.68}$$ < $${261.52}$$
docker_agent_arm64 $${-0}$$ $${777.69}$$ < $${778.35}$$ $${-0}$$ $${250.86}$$ < $${251.72}$$
docker_agent_jmx_amd64 $${-0}$$ $${958.61}$$ < $${959.54}$$ $${+0}$$ $${329.31}$$ < $${330.15}$$
docker_agent_jmx_arm64 $${-0}$$ $${957.29}$$ < $${957.95}$$ $${-0.01}$$ $${315.48}$$ < $${316.35}$$
docker_cluster_agent_amd64 $${+0}$$ $${178.88}$$ < $${179.28}$$ $${+0}$$ $${63.18}$$ < $${63.96}$$
docker_cluster_agent_arm64 $${+0}$$ $${196.39}$$ < $${196.79}$$ $${-0}$$ $${59.89}$$ < $${60.69}$$
docker_cws_instrumentation_amd64 $${0}$$ $${7.07}$$ < $${7.12}$$ $${+0}$$ $${2.95}$$ < $${3.29}$$
docker_cws_instrumentation_arm64 $${0}$$ $${6.69}$$ < $${6.92}$$ $${+0}$$ $${2.7}$$ < $${3.07}$$
docker_dogstatsd_amd64 $${0}$$ $${38.66}$$ < $${39.3}$$ $${+0}$$ $${14.93}$$ < $${15.76}$$
docker_dogstatsd_arm64 $${0}$$ $${37.3}$$ < $${37.94}$$ $${-0}$$ $${14.37}$$ < $${14.83}$$
dogstatsd_deb_amd64 $${0}$$ $${29.88}$$ < $${30.53}$$ $${+0}$$ $${7.88}$$ < $${8.75}$$
dogstatsd_deb_arm64 $${0}$$ $${28.39}$$ < $${29.11}$$ $${-0}$$ $${6.82}$$ < $${7.71}$$
dogstatsd_rpm_amd64 $${0}$$ $${29.88}$$ < $${30.53}$$ $${-0}$$ $${7.89}$$ < $${8.76}$$
dogstatsd_suse_amd64 $${0}$$ $${29.88}$$ < $${30.53}$$ $${-0}$$ $${7.89}$$ < $${8.76}$$
iot_agent_deb_amd64 $${0}$$ $${42.6}$$ < $${43.19}$$ $${+0}$$ $${11.13}$$ < $${11.98}$$
iot_agent_deb_arm64 $${0}$$ $${40.34}$$ < $${40.92}$$ $${+0}$$ $${9.58}$$ < $${10.45}$$
iot_agent_deb_armhf $${0}$$ $${40.24}$$ < $${40.86}$$ $${-0}$$ $${9.69}$$ < $${10.56}$$
iot_agent_rpm_amd64 $${0}$$ $${42.6}$$ < $${43.19}$$ $${+0}$$ $${11.14}$$ < $${12.0}$$
iot_agent_suse_amd64 $${0}$$ $${42.6}$$ < $${43.19}$$ $${+0}$$ $${11.14}$$ < $${12.0}$$

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Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 0d8ba535-c4dd-473b-a188-e5d5104502ee

Baseline: 79e7768
Comparison: 24479b3
Diff

Optimization Goals: ✅ No significant changes detected

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf experiment goal Δ mean % Δ mean % CI trials links
docker_containers_cpu % cpu utilization +1.83 [-1.19, +4.85] 1 Logs

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
docker_containers_cpu % cpu utilization +1.83 [-1.19, +4.85] 1 Logs
tcp_syslog_to_blackhole ingress throughput +1.42 [+1.34, +1.49] 1 Logs
quality_gate_metrics_logs memory utilization +1.33 [+1.12, +1.54] 1 Logs bounds checks dashboard
ddot_metrics_sum_cumulative memory utilization +0.18 [+0.01, +0.34] 1 Logs
file_to_blackhole_500ms_latency egress throughput +0.08 [-0.30, +0.46] 1 Logs
docker_containers_memory memory utilization +0.07 [-0.00, +0.15] 1 Logs
quality_gate_idle_all_features memory utilization +0.05 [+0.01, +0.09] 1 Logs bounds checks dashboard
file_to_blackhole_100ms_latency egress throughput +0.05 [-0.00, +0.10] 1 Logs
uds_dogstatsd_to_api_v3 ingress throughput +0.00 [-0.13, +0.14] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput -0.00 [-0.08, +0.08] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.00 [-0.13, +0.12] 1 Logs
file_to_blackhole_1000ms_latency egress throughput -0.03 [-0.45, +0.38] 1 Logs
file_to_blackhole_0ms_latency egress throughput -0.05 [-0.46, +0.35] 1 Logs
ddot_metrics_sum_cumulativetodelta_exporter memory utilization -0.17 [-0.40, +0.06] 1 Logs
file_tree memory utilization -0.23 [-0.29, -0.18] 1 Logs
ddot_logs memory utilization -0.36 [-0.42, -0.31] 1 Logs
otlp_ingest_metrics memory utilization -0.38 [-0.52, -0.23] 1 Logs
quality_gate_idle memory utilization -0.38 [-0.42, -0.33] 1 Logs bounds checks dashboard
ddot_metrics_sum_delta memory utilization -0.39 [-0.60, -0.17] 1 Logs
uds_dogstatsd_20mb_12k_contexts_20_senders memory utilization -0.56 [-0.61, -0.50] 1 Logs
quality_gate_logs % cpu utilization -0.65 [-2.12, +0.83] 1 Logs bounds checks dashboard
otlp_ingest_logs memory utilization -0.73 [-0.85, -0.62] 1 Logs
ddot_metrics memory utilization -0.96 [-1.17, -0.76] 1 Logs

Bounds Checks: ✅ Passed

perf experiment bounds_check_name replicates_passed links
docker_containers_cpu simple_check_run 10/10
docker_containers_memory memory_usage 10/10
docker_containers_memory simple_check_run 10/10
file_to_blackhole_0ms_latency lost_bytes 10/10
file_to_blackhole_0ms_latency memory_usage 10/10
file_to_blackhole_1000ms_latency lost_bytes 10/10
file_to_blackhole_1000ms_latency 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_500ms_latency lost_bytes 10/10
file_to_blackhole_500ms_latency memory_usage 10/10
quality_gate_idle intake_connections 10/10 bounds checks dashboard
quality_gate_idle memory_usage 10/10 bounds checks dashboard
quality_gate_idle_all_features intake_connections 10/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
quality_gate_logs intake_connections 10/10 bounds checks dashboard
quality_gate_logs lost_bytes 10/10 bounds checks dashboard
quality_gate_logs memory_usage 10/10 bounds checks dashboard
quality_gate_metrics_logs cpu_usage 10/10 bounds checks dashboard
quality_gate_metrics_logs intake_connections 10/10 bounds checks dashboard
quality_gate_metrics_logs lost_bytes 10/10 bounds checks dashboard
quality_gate_metrics_logs memory_usage 10/10 bounds checks dashboard

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

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