SQL normalization in the APM trace agent to improve APM/DBM correlation

[nenadnoveljic]

What does this PR do?

Introduce sql_obfuscation_mode parameter.

Motivation

Normalize SQL if the parameter is set to obfuscate_and_normalize, recommended for DBM customers to enhance APM/DBM correlation.

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Normalization adds extra time on the agent but won’t affect the application since it’s handled by the agent, not the tracer.

Additional Notes

[hush-hush]

Please use BindEnvAndSetDefault instead and use the same default than describe in the config_template.yaml

[nenadnoveljic]

Done.

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 9ac7eb4bffa8dff2b61269260f4ecfe56d61a078

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-x86_64-rpm	0.01MB	⚠️	1021.39MB	1021.38MB	0.50MB
datadog-agent-x86_64-suse	0.01MB	⚠️	1021.39MB	1021.38MB	0.50MB
datadog-agent-amd64-deb	0.01MB	⚠️	1012.07MB	1012.06MB	0.50MB
datadog-heroku-agent-amd64-deb	0.00MB	✅	506.18MB	506.17MB	0.50MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	58.71MB	58.71MB	0.50MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	58.71MB	58.71MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	113.89MB	113.89MB	0.50MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	113.89MB	113.89MB	0.50MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	58.63MB	58.63MB	0.50MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	56.14MB	56.14MB	0.50MB
datadog-iot-agent-amd64-deb	0.00MB	✅	113.82MB	113.82MB	0.50MB
datadog-iot-agent-arm64-deb	0.00MB	✅	109.26MB	109.26MB	0.50MB
datadog-iot-agent-aarch64-rpm	-0.00MB	✅	109.33MB	109.33MB	0.50MB
datadog-agent-aarch64-rpm	-0.00MB	✅	950.60MB	950.60MB	0.50MB
datadog-agent-arm64-deb	-0.00MB	✅	941.30MB	941.30MB	0.50MB

Decision

⚠️ Warning

[agent-platform-auto-pr]

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=52566686 --os-family=ubuntu

Note: This applies to commit 2ebc4f3

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: ed943388-4b0c-4c2f-9c10-6c04ff6b9314

Baseline: 9ac7eb4
Comparison: 2ebc4f3
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+1.37	[+0.70, +2.05]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.82	[-2.42, +4.06]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.32	[-0.46, +1.09]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.20	[+0.10, +0.29]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.10	[-0.36, +0.55]	1	Logs
➖	quality_gate_idle	memory utilization	+0.03	[-0.01, +0.08]	1	Logs bounds checks dashboard
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.10, +0.13]	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
➖	file_to_blackhole_100ms_latency	egress throughput	-0.01	[-0.70, +0.68]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.02	[-0.87, +0.83]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.04	[-0.89, +0.82]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.04	[-0.88, +0.80]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.05	[-0.84, +0.74]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.16	[-0.21, -0.11]	1	Logs
➖	file_tree	memory utilization	-0.22	[-0.36, -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_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check memory_usage: 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.