[ASCII-2671] Add check loader name tag on checks.execution_time metric

[pgimalac]

What does this PR do?

Add the check loader name as a tag on the checks.execution_time metrics.

Motivation

In theory each check should be either on the Go loader or the Python loader.
However some python checks are being rewritten in Go, and with custom checks customers could use the same name as a Go check.
Knowing the loader used to run checks would help a lot to know if we risk breaking users with some checks-related changes.

Describe how you validated your changes

Ran the agent locally, with the following configs:

telemetry.enabled: true
telemetry.checks: "*"

Generated a flare, and checked that telemetry.log contained the metric with the tag, with the correct loader name, eg.

checks__execution_time{check_loader="core",check_name="uptime"} 0
checks__execution_time{check_loader="python",check_name="network"} 46

Also updated pkg/collector/check/stats/stats_test.go to have a unit test ensuring the correct check loader name was used.

Possible Drawbacks / Trade-offs

Additional Notes

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 734013ee47af02b9e71bdf20a38931fe76d280dd

Diff per package

package	diff	status	size	ancestor	threshold
datadog-heroku-agent-amd64-deb	0.02MB	⚠️	477.85MB	477.84MB	0.50MB
datadog-iot-agent-arm64-deb	0.01MB	⚠️	89.89MB	89.88MB	0.50MB
datadog-iot-agent-aarch64-rpm	0.01MB	⚠️	89.96MB	89.95MB	0.50MB
datadog-agent-x86_64-rpm	0.01MB	⚠️	922.38MB	922.37MB	0.50MB
datadog-agent-x86_64-suse	0.01MB	⚠️	922.38MB	922.37MB	0.50MB
datadog-agent-amd64-deb	0.01MB	⚠️	912.64MB	912.63MB	0.50MB
datadog-agent-arm64-deb	0.01MB	⚠️	899.85MB	899.84MB	0.50MB
datadog-agent-aarch64-rpm	0.01MB	⚠️	909.57MB	909.56MB	0.50MB
datadog-iot-agent-amd64-deb	0.01MB	⚠️	93.84MB	93.83MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.01MB	⚠️	93.91MB	93.90MB	0.50MB
datadog-iot-agent-x86_64-suse	0.01MB	⚠️	93.90MB	93.90MB	0.50MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	59.01MB	59.01MB	0.50MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	56.50MB	56.50MB	0.50MB
datadog-dogstatsd-x86_64-rpm	-0.00MB	✅	59.09MB	59.09MB	0.50MB
datadog-dogstatsd-x86_64-suse	-0.00MB	✅	59.09MB	59.09MB	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=54456241 --os-family=ubuntu

Note: This applies to commit 76a431a

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: d7c4b5c1-4b58-46b9-a5b5-39e8904d115c

Baseline: 734013e
Comparison: 76a431a
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	+1.49	[+0.60, +2.38]	1	Logs
➖	file_tree	memory utilization	+0.60	[+0.55, +0.66]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.51	[-2.48, +3.51]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.29	[+0.21, +0.36]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.23	[-0.24, +0.70]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.11	[-0.67, +0.89]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.08	[-0.70, +0.87]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	+0.07	[-0.82, +0.96]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.28, +0.30]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.01	[-0.78, +0.79]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.00	[-0.84, +0.85]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.02, +0.03]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.01	[-0.92, +0.91]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.01	[-0.64, +0.63]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.30	[-0.38, -0.22]	1	Logs
➖	quality_gate_idle	memory utilization	-0.34	[-0.38, -0.30]	1	Logs bounds checks dashboard

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	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
✅	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_logs, bounds check lost_bytes: 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_idle, 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_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.

[sgnn7]

@pgimalac Drive-by note: Should we make sure that these are all lowercase to avoid issues with capitalization/filtering on the backend?

[pgimalac]

I lowercased the strings, and added a comment on the Loader method to make it clear the strings were used in tags so had to follow the constraints.

Does that work for you, or were you thinking of converting whatever is returned by Loader instead ? I don't believe we have a conversion function... (so using strings.Lowercase would work for those specific strings but not in general)

[GustavoCaso]

Outside of the capitalization comment from Srdjan. Things look great, maybe moving the loader name to constants.

[ajgajg1134]

Looks good from agent-apm

[iglendd]

LGTM