[APM Onboarding] SSI bug fix for 7.52.0

[liliyadd]

What does this PR do?

Fixes the bug of NIL due to *sync.once not being initialized.

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

1. DCA dev image https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/438235718
2. Deploy the following helm configuration on DA to the test cluster:

datadog:
  apiKeyExistingSecret: datadog-secret2
  clusterName: "apm-onboarding-injection"
  site: datad0g.com
  apm:
    enabled: false
    socketEnabled: true
    instrumentation:
      enabled: true
      enabledNamespaces:
        - rc-tests
clusterAgent:
  image:
    repository: datadog/cluster-agent-dev
    digest: "sha256:c7cc34bcd153f73c47a7e1ce4c0daa1b2a7a82dc7674514de658213955019521"
    pullPolicy: Always
    doNotCheckTag: true

3. If DA is installed from main of public helm-chart, DCA will have the following env variables installed:

    - name: DD_APM_INSTRUMENTATION_ENABLED
      value: "true"
    - name: DD_APM_INSTRUMENTATION_DISABLED_NAMESPACES
      value: '["default"]'

In https://github.com/DataDog/datadog-agent/pull/21673/files we re-defined SSI configuration options, but for those to take an effect, we also need to change helm-chart.

If DA is installed from a branch liliya.belaus/remove-datadog-ns-blacklisting-ssi (DataDog/helm-charts#1318), DCA has the expected env variables installed.

    - name: DD_APM_INSTRUMENTATION_ENABLED
      value: "true"
    - name: DD_APM_INSTRUMENTATION_ENABLED_NAMESPACES
      value: '["rc-tests"]'

4. NIL pointer exception is gone.

[pr-commenter]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: 08073ca1-20f8-488d-9fe6-0dfe18801826
Baseline: 8a92821
Comparison: f6d3ec7
Total CPUs: 7

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

Experiments with missing or malformed data

• basic_py_check

Usually, this warning means that there is no usable optimization goal data for that experiment, which could be a result of misconfiguration.

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.

Experiments ignored for regressions

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

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	-2.03	[-8.56, +4.50]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	process_agent_standard_check_with_stats	memory utilization	+0.66	[+0.62, +0.70]
➖	file_tree	memory utilization	+0.32	[+0.23, +0.40]
➖	otel_to_otel_logs	ingress throughput	+0.31	[-0.30, +0.93]
➖	idle	memory utilization	+0.19	[+0.16, +0.22]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.01	[-1.41, +1.44]
➖	process_agent_real_time_mode	memory utilization	+0.00	[-0.03, +0.03]
➖	trace_agent_msgpack	ingress throughput	+0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.00, +0.00]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.00, +0.00]
➖	process_agent_standard_check	memory utilization	-0.00	[-0.04, +0.04]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.01	[-0.07, +0.05]
➖	trace_agent_json	ingress throughput	-0.01	[-0.05, +0.02]
➖	file_to_blackhole	% cpu utilization	-2.03	[-8.56, +4.50]

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".

[davidor]

I think this is ok for fixing the issue in 7.52.0, but I think that we should handle the initialization of the pinned libraries in newAPMInstrumentationWebhook() which is what I did in my open PR: #22842

[liliyadd]

/merge

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