Improve Leader Election metrics

[keisku]

What does this PR do?

When the pod is leader, is_leader is true, and its value becomes 1. Otherwise, is_leader is false, and the value is 0.

Motivation

DataDog/integrations-core#19308 (comment)

Describe how you validated your changes

kubectl exec -it datadog-cluster-agent-5877c6744d-8f52h -c cluster-agent -- curl http://localhost:5000/metrics | grep is_leader
# HELP leader_election_is_leader When the pod is leader, is_leader is true, and its value becomes 1. Otherwise, is_leader is false, and the value is 0.
# TYPE leader_election_is_leader gauge
leader_election_is_leader{is_leader="false",join_leader="true"} 0

kubectl exec -it datadog-cluster-agent-5877c6744d-z2wbp -c cluster-agent -- curl http://localhost:5000/metrics | grep is_leader
# HELP leader_election_is_leader When the pod is leader, is_leader is true, and its value becomes 1. Otherwise, is_leader is false, and the value is 0.
# TYPE leader_election_is_leader gauge
leader_election_is_leader{is_leader="true",join_leader="true"} 1

Possible Drawbacks / Trade-offs

Additional Notes

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 701ea4a893ea0f2fd137f9ac0efad01ce158f55f

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-x86_64-rpm	0.11MB	⚠️	1200.18MB	1200.07MB	140.00MB
datadog-agent-x86_64-suse	0.11MB	⚠️	1200.18MB	1200.07MB	140.00MB
datadog-agent-amd64-deb	0.09MB	⚠️	1190.86MB	1190.77MB	140.00MB
datadog-agent-aarch64-rpm	0.08MB	⚠️	944.45MB	944.37MB	140.00MB
datadog-heroku-agent-amd64-deb	0.07MB	⚠️	505.27MB	505.21MB	70.00MB
datadog-agent-arm64-deb	0.06MB	⚠️	935.16MB	935.10MB	140.00MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	78.57MB	78.57MB	10.00MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	78.65MB	78.65MB	10.00MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	78.65MB	78.65MB	10.00MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	55.77MB	55.77MB	10.00MB
datadog-iot-agent-amd64-deb	0.00MB	✅	113.35MB	113.35MB	10.00MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	113.42MB	113.42MB	10.00MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	113.42MB	113.42MB	10.00MB
datadog-iot-agent-arm64-deb	0.00MB	✅	108.81MB	108.81MB	10.00MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	108.88MB	108.88MB	10.00MB

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=51834083 --os-family=ubuntu

Note: This applies to commit 7794eac

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: fcddc4d6-94ad-4b52-9ef9-c4c597d69689

Baseline: 701ea4a
Comparison: 7794eac
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+2.73	[-0.61, +6.06]	1	Logs
➖	file_tree	memory utilization	+0.65	[+0.53, +0.78]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.26	[+0.20, +0.32]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.13	[-0.33, +0.59]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.06	[-0.74, +0.86]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.04	[-0.73, +0.82]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	+0.02	[-0.62, +0.67]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	+0.02	[-0.85, +0.89]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.01, +0.01]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.11, +0.11]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.02	[-0.74, +0.69]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.03	[-0.88, +0.83]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.04	[-0.96, +0.88]	1	Logs
➖	quality_gate_idle	memory utilization	-0.44	[-0.47, -0.40]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	-0.51	[-0.59, -0.43]	1	Logs bounds checks dashboard
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.56	[-1.24, +0.11]	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, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, 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_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.