[Backport 7.72.x] Remove Update Install Source Custom Action

[dd-octo-sts]

Backport 5797a72 from #42114.

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What does this PR do?

This PR removes the update install source custom action that was added in: #40511

Motivation

https://datadoghq.atlassian.net/browse/WINA-1929

The custom action updated the install source after installing via MSI to use the fleet package name and msi path. This can potentially cause reinstalls to fail as MSI does not use the sourcelist path during reinstalls.

Describe how you validated your changes

Since this is just removing a custom action, the existing e2e tests should ensure that the agent installs and uninstalls just fine.

Additional Notes

[AliDatadog]

/trigger-ci --variable RUN_ALL_BUILDS=true --variable RUN_KITCHEN_TESTS=true --variable RUN_E2E_TESTS=on --variable RUN_UNIT_TESTS=on --variable RUN_KMT_TESTS=on

[AliDatadog]

/merge

[dd-devflow-routing-codex]

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2025-10-21 13:34:44 UTC ℹ️ Start processing command /trigger-ci --variable RUN_ALL_BUILDS=true --variable RUN_KITCHEN_TESTS=true --variable RUN_E2E_TESTS=on --variable RUN_UNIT_TESTS=on --variable RUN_KMT_TESTS=on

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2025-10-21 13:34:59 UTC ℹ️ Branch synced on Gitlab

Branch backport-42114-to-7.72.x was out-of-sync on Gitlab - it has been resynced

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2025-10-21 13:35:57 UTC ℹ️ Gitlab pipeline started

Started pipeline #79833917

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2025-10-21 13:34:47 UTC ℹ️ Start processing command /merge

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You can remove it from the waiting list with /remove command.

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2025-10-21 14:14:25 UTC ℹ️ MergeQueue: merge request added to the queue

The expected merge time in 7.72.x is approximately 36m (p90).

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2025-10-21 14:28:30 UTC ℹ️ MergeQueue: This merge request was merged

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 93bcf0e0-da8d-4644-b7b5-b388d87c1f75

Baseline: f42be85
Comparison: bf3c734
Diff

Optimization Goals: ❌ Regression(s) detected

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
❌	docker_containers_memory	memory utilization	+9.08	[+8.53, +9.63]	1	Logs

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	-0.07	[-1.52, +1.39]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
❌	docker_containers_memory	memory utilization	+9.08	[+8.53, +9.63]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.83	[+0.79, +0.87]	1	Logs bounds checks dashboard
➖	ddot_metrics_sum_delta	memory utilization	+0.72	[+0.56, +0.89]	1	Logs
➖	ddot_metrics	memory utilization	+0.39	[+0.22, +0.56]	1	Logs
➖	otlp_ingest_metrics	memory utilization	+0.32	[+0.19, +0.45]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	+0.29	[+0.10, +0.49]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.14	[+0.07, +0.20]	1	Logs
➖	file_tree	memory utilization	+0.13	[+0.09, +0.17]	1	Logs
➖	quality_gate_idle	memory utilization	+0.10	[+0.06, +0.14]	1	Logs bounds checks dashboard
➖	file_to_blackhole_100ms_latency	egress throughput	+0.02	[-0.57, +0.62]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.22, +0.22]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.01, +0.01]	1	Logs
➖	ddot_logs	memory utilization	-0.01	[-0.06, +0.05]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.02	[-0.65, +0.61]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.05	[-0.60, +0.50]	1	Logs
➖	docker_containers_cpu	% cpu utilization	-0.07	[-1.52, +1.39]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.08	[-0.72, +0.55]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-0.10	[-0.16, -0.04]	1	Logs
➖	otlp_ingest_logs	memory utilization	-0.16	[-0.27, -0.04]	1	Logs
➖	ddot_metrics_sum_cumulative	memory utilization	-0.67	[-0.80, -0.55]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	-0.88	[-1.09, -0.66]	1	Logs bounds checks dashboard
➖	quality_gate_logs	% cpu utilization	-3.58	[-6.33, -0.83]	1	Logs bounds checks dashboard

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	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_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_logs, 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_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_metrics_logs, bounds check cpu_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 lost_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.