[SVLS-8372] Add functionname tag to Google Cloud Run function profiles

[kathiehuang]

What does this PR do?

Adds functionname tag to profiles for Google Cloud Run functions (gen 2).

Motivation

This will help the profiling team filter out and track profiles from functions for billing purposes, similarly to Lambda functions and Azure functions.

Describe how you validated your changes

To do:
Deploy with DD_PROFILING_ENABLED=true and look at network request to validate that functionname is set correctly (following this local testing guide for serverless-init).
Check that it's set correctly for Google Cloud Run functions, and that it isn't being set for Google Cloud Run Service/Jobs or Azure.

Additional Notes

[agent-platform-auto-pr]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 2335f29
📊 Static Quality Gates Dashboard

31 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	753.376 MiB
✅	agent_deb_amd64_fips	702.037 MiB
✅	agent_heroku_amd64	326.915 MiB
✅	agent_msi	662.965 MiB
✅	agent_rpm_amd64	753.360 MiB
✅	agent_rpm_amd64_fips	702.021 MiB
✅	agent_rpm_arm64	732.123 MiB
✅	agent_rpm_arm64_fips	684.115 MiB
✅	agent_suse_amd64	753.360 MiB
✅	agent_suse_amd64_fips	702.021 MiB
✅	agent_suse_arm64	732.123 MiB
✅	agent_suse_arm64_fips	684.115 MiB
✅	docker_agent_amd64	815.477 MiB
✅	docker_agent_arm64	818.831 MiB
✅	docker_agent_jmx_amd64	1006.356 MiB
✅	docker_agent_jmx_arm64	998.429 MiB
✅	docker_cluster_agent_amd64	181.096 MiB
✅	docker_cluster_agent_arm64	196.918 MiB
✅	docker_cws_instrumentation_amd64	7.135 MiB
✅	docker_cws_instrumentation_arm64	6.689 MiB
✅	docker_dogstatsd_amd64	38.836 MiB
✅	docker_dogstatsd_arm64	37.128 MiB
✅	dogstatsd_deb_amd64	30.055 MiB
✅	dogstatsd_deb_arm64	28.200 MiB
✅	dogstatsd_rpm_amd64	30.055 MiB
✅	dogstatsd_suse_amd64	30.055 MiB
✅	iot_agent_deb_amd64	43.029 MiB
✅	iot_agent_deb_arm64	40.135 MiB
✅	iot_agent_deb_armhf	40.701 MiB
✅	iot_agent_rpm_amd64	43.030 MiB
✅	iot_agent_suse_amd64	43.030 MiB

On-wire sizes (compressed)

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	+26.8 KiB (0.01% increase)	183.923 → 183.950 → 184.810
✅	agent_deb_amd64_fips	-4.26 KiB (0.00% reduction)	172.644 → 172.640 → 173.790
✅	agent_heroku_amd64	+4.93 KiB (0.01% increase)	87.134 → 87.139 → 88.450
✅	agent_msi	neutral	143.117 MiB → 143.300
✅	agent_rpm_amd64	-3.67 KiB (0.00% reduction)	186.818 → 186.814 → 188.160
✅	agent_rpm_amd64_fips	+5.4 KiB (0.00% increase)	175.689 → 175.694 → 176.600
✅	agent_rpm_arm64	+13.84 KiB (0.01% increase)	168.644 → 168.657 → 169.930
✅	agent_rpm_arm64_fips	-7.84 KiB (0.00% reduction)	159.197 → 159.190 → 160.550
✅	agent_suse_amd64	-3.67 KiB (0.00% reduction)	186.818 → 186.814 → 188.160
✅	agent_suse_amd64_fips	+5.4 KiB (0.00% increase)	175.689 → 175.694 → 176.600
✅	agent_suse_arm64	+13.84 KiB (0.01% increase)	168.644 → 168.657 → 169.930
✅	agent_suse_arm64_fips	-7.84 KiB (0.00% reduction)	159.197 → 159.190 → 160.550
✅	docker_agent_amd64	neutral	276.680 MiB → 277.400
✅	docker_agent_arm64	neutral	264.108 MiB → 266.040
✅	docker_agent_jmx_amd64	neutral	345.323 MiB → 346.020
✅	docker_agent_jmx_arm64	neutral	328.738 MiB → 330.660
✅	docker_cluster_agent_amd64	neutral	63.990 MiB → 64.490
✅	docker_cluster_agent_arm64	neutral	60.249 MiB → 61.170
✅	docker_cws_instrumentation_amd64	neutral	2.994 MiB → 3.330
✅	docker_cws_instrumentation_arm64	neutral	2.726 MiB → 3.090
✅	docker_dogstatsd_amd64	neutral	15.030 MiB → 15.820
✅	docker_dogstatsd_arm64	neutral	14.353 MiB → 14.830
✅	dogstatsd_deb_amd64	neutral	7.947 MiB → 8.790
✅	dogstatsd_deb_arm64	neutral	6.824 MiB → 7.710
✅	dogstatsd_rpm_amd64	neutral	7.957 MiB → 8.800
✅	dogstatsd_suse_amd64	neutral	7.957 MiB → 8.800
✅	iot_agent_deb_amd64	-2.66 KiB (0.02% reduction)	11.291 → 11.289 → 12.040
✅	iot_agent_deb_arm64	neutral	9.649 MiB → 10.450
✅	iot_agent_deb_armhf	neutral	9.843 MiB → 10.620
✅	iot_agent_rpm_amd64	neutral	11.307 MiB → 12.060
✅	iot_agent_suse_amd64	neutral	11.307 MiB → 12.060

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 65791093-77ed-4b6f-abdd-b98768e322ea

Baseline: 2335f29
Comparison: feb507f
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	+1.59	[-1.55, +4.73]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	+1.59	[-1.55, +4.73]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.60	[-0.90, +2.11]	1	Logs bounds checks dashboard
➖	file_tree	memory utilization	+0.42	[+0.36, +0.47]	1	Logs
➖	ddot_metrics_sum_cumulative	memory utilization	+0.28	[+0.11, +0.44]	1	Logs
➖	ddot_metrics_sum_delta	memory utilization	+0.26	[+0.06, +0.45]	1	Logs
➖	quality_gate_idle	memory utilization	+0.25	[+0.21, +0.29]	1	Logs bounds checks dashboard
➖	otlp_ingest_logs	memory utilization	+0.16	[+0.06, +0.26]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	+0.07	[-0.16, +0.30]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	+0.02	[-0.12, +0.15]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.14, +0.14]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.09, +0.09]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.01	[-0.42, +0.41]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.02	[-0.06, +0.03]	1	Logs
➖	otlp_ingest_metrics	memory utilization	-0.03	[-0.18, +0.13]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.03	[-0.55, +0.49]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.06	[-0.45, +0.33]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.26	[-0.30, -0.23]	1	Logs bounds checks dashboard
➖	ddot_metrics	memory utilization	-0.34	[-0.57, -0.12]	1	Logs
➖	ddot_logs	memory utilization	-0.41	[-0.49, -0.34]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-0.52	[-0.57, -0.47]	1	Logs
➖	docker_containers_memory	memory utilization	-0.55	[-0.63, -0.48]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	-0.67	[-0.89, -0.46]	1	Logs bounds checks dashboard
➖	tcp_syslog_to_blackhole	ingress throughput	-0.80	[-0.88, -0.72]	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_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_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.
• 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_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 memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.