APM: Add DJM tags to CC Obfuscator skip list

[ajgajg1134]

What does this PR do?

Adds databricks_job_id, databricks_job_run_id, databricks_task_run_id, config.spark_app_startTime to the static list of tags that should be skipped by the credit card obfuscator.

Motivation

These tags are attached by DJM automatically and very frequently have IDs that might trigger a false positive from the CC Obfuscator, thereby replacing these useful fields with ?.

Describe how you validated your changes

Existing unit tests are sufficient here

Additional Notes

[agent-platform-auto-pr]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 0cbd517
📊 Static Quality Gates Dashboard

31 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	705.155 MiB
✅	agent_deb_amd64_fips	700.452 MiB
✅	agent_heroku_amd64	326.864 MiB
✅	agent_msi	571.329 MiB
✅	agent_rpm_amd64	705.142 MiB
✅	agent_rpm_amd64_fips	700.439 MiB
✅	agent_rpm_arm64	686.706 MiB
✅	agent_rpm_arm64_fips	682.843 MiB
✅	agent_suse_amd64	705.142 MiB
✅	agent_suse_amd64_fips	700.439 MiB
✅	agent_suse_arm64	686.706 MiB
✅	agent_suse_arm64_fips	682.843 MiB
✅	docker_agent_amd64	767.388 MiB
✅	docker_agent_arm64	773.554 MiB
✅	docker_agent_jmx_amd64	958.266 MiB
✅	docker_agent_jmx_arm64	953.152 MiB
✅	docker_cluster_agent_amd64	180.761 MiB
✅	docker_cluster_agent_arm64	196.618 MiB
✅	docker_cws_instrumentation_amd64	7.135 MiB
✅	docker_cws_instrumentation_arm64	6.689 MiB
✅	docker_dogstatsd_amd64	38.785 MiB
✅	docker_dogstatsd_arm64	37.128 MiB
✅	dogstatsd_deb_amd64	30.004 MiB
✅	dogstatsd_deb_arm64	28.156 MiB
✅	dogstatsd_rpm_amd64	30.004 MiB
✅	dogstatsd_suse_amd64	30.004 MiB
✅	iot_agent_deb_amd64	43.002 MiB
✅	iot_agent_deb_arm64	40.123 MiB
✅	iot_agent_deb_armhf	40.704 MiB
✅	iot_agent_rpm_amd64	43.003 MiB
✅	iot_agent_suse_amd64	43.003 MiB

On-wire sizes (compressed)

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	neutral	173.303 MiB
✅	agent_deb_amd64_fips	+39.45 KiB (0.02% increase)	172.225 → 172.264 → 173.750
✅	agent_heroku_amd64	+2.28 KiB (0.00% increase)	87.107 → 87.109 → 88.450
✅	agent_msi	+4.0 KiB (0.00% increase)	142.852 → 142.855 → 143.020
✅	agent_rpm_amd64	+59.17 KiB (0.03% increase)	176.116 → 176.174 → 177.660
✅	agent_rpm_amd64_fips	+13.52 KiB (0.01% increase)	174.919 → 174.932 → 176.600
✅	agent_rpm_arm64	-19.84 KiB (0.01% reduction)	159.362 → 159.343 → 161.260
✅	agent_rpm_arm64_fips	+16.95 KiB (0.01% increase)	158.747 → 158.763 → 160.550
✅	agent_suse_amd64	+59.17 KiB (0.03% increase)	176.116 → 176.174 → 177.660
✅	agent_suse_amd64_fips	+13.52 KiB (0.01% increase)	174.919 → 174.932 → 176.600
✅	agent_suse_arm64	-19.84 KiB (0.01% reduction)	159.362 → 159.343 → 161.260
✅	agent_suse_arm64_fips	+16.95 KiB (0.01% increase)	158.747 → 158.763 → 160.550
✅	docker_agent_amd64	neutral	261.026 MiB
✅	docker_agent_arm64	neutral	250.071 MiB
✅	docker_agent_jmx_amd64	neutral	329.660 MiB
✅	docker_agent_jmx_arm64	+3.51 KiB (0.00% increase)	314.693 → 314.696 → 317.270
✅	docker_cluster_agent_amd64	neutral	63.849 MiB
✅	docker_cluster_agent_arm64	neutral	60.147 MiB
✅	docker_cws_instrumentation_amd64	neutral	2.994 MiB
✅	docker_cws_instrumentation_arm64	neutral	2.726 MiB
✅	docker_dogstatsd_amd64	neutral	15.017 MiB
✅	docker_dogstatsd_arm64	neutral	14.342 MiB
✅	dogstatsd_deb_amd64	neutral	7.938 MiB
✅	dogstatsd_deb_arm64	neutral	6.815 MiB
✅	dogstatsd_rpm_amd64	neutral	7.949 MiB
✅	dogstatsd_suse_amd64	neutral	7.949 MiB
✅	iot_agent_deb_amd64	neutral	11.265 MiB
✅	iot_agent_deb_arm64	neutral	9.634 MiB
✅	iot_agent_deb_armhf	neutral	9.826 MiB
✅	iot_agent_rpm_amd64	+2.76 KiB (0.02% increase)	11.278 → 11.280 → 12.060
✅	iot_agent_suse_amd64	+2.76 KiB (0.02% increase)	11.278 → 11.280 → 12.060

[charlesmyu]

Thank you!

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 1d337915-280d-46fa-b8d6-20ef7d5f23e6

Baseline: 0cbd517
Comparison: 8074f96
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	-1.47	[-4.40, +1.47]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	ddot_logs	memory utilization	+1.56	[+1.49, +1.63]	1	Logs
➖	ddot_metrics	memory utilization	+0.38	[+0.15, +0.61]	1	Logs
➖	docker_containers_memory	memory utilization	+0.30	[+0.23, +0.37]	1	Logs
➖	otlp_ingest_metrics	memory utilization	+0.22	[+0.07, +0.37]	1	Logs
➖	ddot_metrics_sum_delta	memory utilization	+0.17	[-0.04, +0.38]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.09	[-0.28, +0.47]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	+0.01	[-0.12, +0.14]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.13, +0.14]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	-0.00	[-0.23, +0.23]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.01	[-0.08, +0.07]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.03	[-0.43, +0.37]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-0.03	[-0.09, +0.03]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.04	[-0.07, +0.00]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.04	[-0.45, +0.37]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.05	[-0.09, +0.00]	1	Logs
➖	file_tree	memory utilization	-0.13	[-0.18, -0.07]	1	Logs
➖	ddot_metrics_sum_cumulative	memory utilization	-0.40	[-0.55, -0.24]	1	Logs
➖	otlp_ingest_logs	memory utilization	-0.58	[-0.68, -0.48]	1	Logs
➖	quality_gate_idle	memory utilization	-0.83	[-0.87, -0.78]	1	Logs bounds checks dashboard
➖	quality_gate_metrics_logs	memory utilization	-0.91	[-1.11, -0.71]	1	Logs bounds checks dashboard
➖	tcp_syslog_to_blackhole	ingress throughput	-1.21	[-1.29, -1.13]	1	Logs
➖	docker_containers_cpu	% cpu utilization	-1.47	[-4.40, +1.47]	1	Logs
➖	quality_gate_logs	% cpu utilization	-1.60	[-3.09, -0.11]	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	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 lost_bytes: 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_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, 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_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_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.