[ha-agent] Add agent_group tag to datadog.agent.running metric

[AlexandreYang]

What does this PR do?

[ha-agent] Add agent_group tag to datadog.agent.running metric.

This PR changes a lot of files, but the actual change is only few lines located in pkg/aggregator/aggregator.go:
https://github.com/DataDog/datadog-agent/pull/31156/files#diff-0940f1dc68973941178797f388ffb31d3318abeefa87b7f0b66d575915a0e575R867-R869

the rest of the changes are only about injecting correctly the component.

Motivation

Add agent_group tag to datadog.agent.running metric is needed for HA Agent feature.

HA Agent will fetch datadog.agent.running metric by grouping by host,agent_group in backend with:

• that will help know which agent is in which agent group (agent_group tag)
• know which agent is active (datadog.agent.running)

Describe how to test/QA your changes

When HA Agent is enabled, verify that the datadog.agent.running metric has the tag agent_group.

1/ Enabled ha_agent feature in datadog.yaml

ha_agent:
  enabled: true
  group: my-group01

2/ start the agent and verify datadog.agent.running metric has the tag agent_group.

Possible Drawbacks / Trade-offs

Additional Notes

[cit-pr-commenter]

Go Package Import Differences

Baseline: 30d51b5
Comparison: b06fc67

binary	os	arch	change
cluster-agent	linux	amd64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
cluster-agent	linux	arm64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
cluster-agent-cloudfoundry	linux	amd64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
cluster-agent-cloudfoundry	linux	arm64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
dogstatsd	linux	amd64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
dogstatsd	linux	arm64	+3, -0 +github.com/DataDog/datadog-agent/comp/haagent/def +github.com/DataDog/datadog-agent/comp/haagent/fx +github.com/DataDog/datadog-agent/comp/haagent/impl
security-agent	linux	amd64	+1, -0 +github.com/DataDog/datadog-agent/comp/haagent/def
security-agent	linux	arm64	+1, -0 +github.com/DataDog/datadog-agent/comp/haagent/def
security-agent	windows	amd64	+1, -0 +github.com/DataDog/datadog-agent/comp/haagent/def
serverless	linux	amd64	+1, -0 +github.com/DataDog/datadog-agent/comp/haagent/def
serverless	linux	arm64	+1, -0 +github.com/DataDog/datadog-agent/comp/haagent/def

[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 create-vm --pipeline-id=49912338 --os-family=ubuntu

Note: This applies to commit b06fc67

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: f7c82893-910f-47de-ab72-1581a916dd57

Baseline: 30d51b5
Comparison: b06fc67
Diff

Optimization Goals: ❌ Significant changes detected

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
✅	pycheck_lots_of_tags	% cpu utilization	-6.28	[-9.72, -2.84]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	basic_py_check	% cpu utilization	+3.75	[-0.11, +7.61]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+1.55	[+1.49, +1.62]	1	Logs
➖	otel_to_otel_logs	ingress throughput	+0.63	[-0.05, +1.30]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.34	[-0.46, +1.14]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.24	[-0.22, +0.70]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.06	[-0.80, +0.92]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.11, +0.12]	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	[-0.63, +0.63]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.04	[-0.71, +0.63]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.09	[-0.86, +0.67]	1	Logs
➖	quality_gate_idle	memory utilization	-0.31	[-0.36, -0.27]	1	Logs bounds checks dashboard
➖	file_tree	memory utilization	-0.77	[-0.91, -0.63]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.87	[-1.60, -0.14]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-2.92	[-3.02, -2.81]	1	Logs bounds checks dashboard
✅	pycheck_lots_of_tags	% cpu utilization	-6.28	[-9.72, -2.84]	1	Logs

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	file_to_blackhole_0ms_latency	lost_bytes	9/10
✅	file_to_blackhole_0ms_latency	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

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_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.

[github-actions]

📥 📢 Info, this pull request increases the binary size of serverless extension by 0 bytes. Each MB of binary size increase means about 10ms of additional cold start time, so this pull request would increase cold start time by 0ms.

Debug info

If you have questions, we are happy to help, come visit us in the #serverless slack channel and provide a link to this comment.

We suggest you consider adding the !serverless build tag to remove any new dependencies not needed in the serverless extension.

[github-actions]

Serverless Benchmark Results

BenchmarkStartEndInvocation comparison between 1b7481c and b71df99.

tl;dr

Use these benchmarks as an insight tool during development.

1. Skim down the vs base column in each chart. If there is a ~, then there was no statistically significant change to the benchmark. Otherwise, ensure the estimated percent change is either negative or very small.

2. The last row of each chart is the geomean. Ensure this percentage is either negative or very small.

What is this benchmarking?

The BenchmarkStartEndInvocation compares the amount of time it takes to call the start-invocation and end-invocation endpoints. For universal instrumentation languages (Dotnet, Golang, Java, Ruby), this represents the majority of the duration overhead added by our tracing layer.

The benchmark is run using a large variety of lambda request payloads. In the charts below, there is one row for each event payload type.

How do I interpret these charts?

The charts below comes from benchstat. They represent the statistical change in duration (sec/op), memory overhead (B/op), and allocations (allocs/op).

The benchstat docs explain how to interpret these charts.

Before the comparison table, we see common file-level configuration. If there are benchmarks with different configuration (for example, from different packages), benchstat will print separate tables for each configuration.

The table then compares the two input files for each benchmark. It shows the median and 95% confidence interval summaries for each benchmark before and after the change, and an A/B comparison under "vs base". ... The p-value measures how likely it is that any differences were due to random chance (i.e., noise). The "~" means benchstat did not detect a statistically significant difference between the two inputs. ...

Note that "statistically significant" is not the same as "large": with enough low-noise data, even very small changes can be distinguished from noise and considered statistically significant. It is, of course, generally easier to distinguish large changes from noise.

Finally, the last row of the table shows the geometric mean of each column, giving an overall picture of how the benchmarks changed. Proportional changes in the geomean reflect proportional changes in the benchmarks. For example, given n benchmarks, if sec/op for one of them increases by a factor of 2, then the sec/op geomean will increase by a factor of ⁿ√2.

I need more help

First off, do not worry if the benchmarks are failing. They are not tests. The intention is for them to be a tool for you to use during development.

If you would like a hand interpreting the results come chat with us in #serverless-agent in the internal DataDog slack or in #serverless in the public DataDog slack. We're happy to help!

Benchmark stats

goos: linux
goarch: amd64
pkg: github.com/DataDog/datadog-agent/pkg/serverless/daemon
cpu: AMD EPYC 7763 64-Core Processor                
                                      │ baseline/benchmark.log │       current/benchmark.log        │
                                      │         sec/op         │   sec/op     vs base               │
api-gateway-appsec.json                            85.75µ ± 6%   88.31µ ± 4%       ~ (p=0.353 n=10)
api-gateway-kong-appsec.json                       65.64µ ± 2%   65.35µ ± 4%       ~ (p=0.123 n=10)
api-gateway-kong.json                              63.56µ ± 3%   62.89µ ± 1%       ~ (p=0.165 n=10)
api-gateway-non-proxy-async.json                  100.03µ ± 1%   98.75µ ± 2%       ~ (p=0.063 n=10)
api-gateway-non-proxy.json                         97.83µ ± 0%   98.00µ ± 1%       ~ (p=0.781 n=10)
api-gateway-websocket-connect.json                 65.37µ ± 2%   65.16µ ± 1%       ~ (p=0.684 n=10)
api-gateway-websocket-default.json                 57.82µ ± 1%   57.94µ ± 2%       ~ (p=0.436 n=10)
api-gateway-websocket-disconnect.json              57.47µ ± 1%   57.97µ ± 3%  +0.87% (p=0.011 n=10)
api-gateway.json                                   106.2µ ± 1%   106.4µ ± 0%       ~ (p=0.529 n=10)
application-load-balancer.json                     57.31µ ± 1%   57.54µ ± 1%       ~ (p=0.529 n=10)
cloudfront.json                                    44.37µ ± 2%   43.72µ ± 1%  -1.47% (p=0.011 n=10)
cloudwatch-events.json                             36.72µ ± 1%   36.22µ ± 2%       ~ (p=0.353 n=10)
cloudwatch-logs.json                               59.81µ ± 2%   57.41µ ± 2%  -4.01% (p=0.000 n=10)
custom.json                                        29.84µ ± 1%   29.32µ ± 2%  -1.74% (p=0.007 n=10)
dynamodb.json                                      88.45µ ± 2%   86.38µ ± 1%  -2.34% (p=0.001 n=10)
empty.json                                         27.87µ ± 3%   27.62µ ± 2%       ~ (p=0.315 n=10)
eventbridge-custom.json                            44.82µ ± 1%   45.11µ ± 1%       ~ (p=0.739 n=10)
eventbridge-no-bus.json                            43.50µ ± 2%   43.55µ ± 1%       ~ (p=0.529 n=10)
eventbridge-no-timestamp.json                      44.39µ ± 2%   43.49µ ± 2%  -2.02% (p=0.009 n=10)
eventbridgesns.json                                59.08µ ± 1%   58.38µ ± 2%  -1.18% (p=0.035 n=10)
eventbridgesqs.json                                66.22µ ± 2%   65.63µ ± 1%  -0.89% (p=0.011 n=10)
http-api.json                                      67.04µ ± 1%   65.99µ ± 1%  -1.57% (p=0.000 n=10)
kinesis-batch.json                                 65.47µ ± 2%   65.00µ ± 1%  -0.72% (p=0.035 n=10)
kinesis.json                                       51.18µ ± 2%   50.75µ ± 2%       ~ (p=0.089 n=10)
s3.json                                            55.46µ ± 1%   55.23µ ± 1%       ~ (p=0.404 n=10)
sns-batch.json                                     84.89µ ± 1%   84.01µ ± 1%       ~ (p=0.089 n=10)
sns.json                                           62.67µ ± 1%   62.45µ ± 2%       ~ (p=0.579 n=10)
snssqs.json                                        107.4µ ± 1%   107.0µ ± 1%       ~ (p=0.247 n=10)
snssqs_no_dd_context.json                          96.41µ ± 4%   96.79µ ± 2%       ~ (p=1.000 n=10)
sqs-aws-header.json                                55.10µ ± 2%   54.24µ ± 2%  -1.56% (p=0.011 n=10)
sqs-batch.json                                     87.44µ ± 1%   86.84µ ± 1%  -0.69% (p=0.043 n=10)
sqs.json                                           66.78µ ± 2%   66.00µ ± 1%       ~ (p=0.143 n=10)
sqs_no_dd_context.json                             62.10µ ± 1%   61.10µ ± 2%  -1.61% (p=0.019 n=10)
stepfunction.json                                  40.73µ ± 5%   42.00µ ± 3%       ~ (p=0.143 n=10)
geomean                                            61.40µ        61.03µ       -0.60%

                                      │ baseline/benchmark.log │        current/benchmark.log        │
                                      │          B/op          │     B/op      vs base               │
api-gateway-appsec.json                           37.26Ki ± 0%   37.26Ki ± 0%       ~ (p=0.177 n=10)
api-gateway-kong-appsec.json                      26.90Ki ± 0%   26.90Ki ± 0%       ~ (p=0.866 n=10)
api-gateway-kong.json                             24.37Ki ± 0%   24.36Ki ± 0%       ~ (p=0.643 n=10)
api-gateway-non-proxy-async.json                  47.94Ki ± 0%   47.94Ki ± 0%       ~ (p=0.541 n=10)
api-gateway-non-proxy.json                        47.11Ki ± 0%   47.11Ki ± 0%       ~ (p=0.839 n=10)
api-gateway-websocket-connect.json                25.34Ki ± 0%   25.34Ki ± 0%       ~ (p=0.180 n=10)
api-gateway-websocket-default.json                21.23Ki ± 0%   21.22Ki ± 0%       ~ (p=0.103 n=10)
api-gateway-websocket-disconnect.json             20.99Ki ± 0%   20.99Ki ± 0%       ~ (p=0.550 n=10)
api-gateway.json                                  49.26Ki ± 0%   49.26Ki ± 0%       ~ (p=0.590 n=10)
application-load-balancer.json                    22.12Ki ± 0%   22.12Ki ± 0%       ~ (p=0.133 n=10)
cloudfront.json                                   17.43Ki ± 0%   17.43Ki ± 0%       ~ (p=0.387 n=10)
cloudwatch-events.json                            11.49Ki ± 0%   11.49Ki ± 0%       ~ (p=1.000 n=10)
cloudwatch-logs.json                              53.05Ki ± 0%   53.05Ki ± 0%       ~ (p=0.208 n=10)
custom.json                                       9.527Ki ± 0%   9.527Ki ± 0%       ~ (p=0.180 n=10)
dynamodb.json                                     40.30Ki ± 0%   40.29Ki ± 0%       ~ (p=0.138 n=10)
empty.json                                        9.065Ki ± 0%   9.065Ki ± 0%       ~ (p=0.721 n=10)
eventbridge-custom.json                           14.67Ki ± 0%   14.67Ki ± 0%       ~ (p=0.621 n=10)
eventbridge-no-bus.json                           13.63Ki ± 0%   13.63Ki ± 0%       ~ (p=1.000 n=10)
eventbridge-no-timestamp.json                     13.63Ki ± 0%   13.63Ki ± 0%       ~ (p=0.596 n=10)
eventbridgesns.json                               20.43Ki ± 0%   20.43Ki ± 0%       ~ (p=0.254 n=10)
eventbridgesqs.json                               24.56Ki ± 0%   24.56Ki ± 0%       ~ (p=0.596 n=10)
http-api.json                                     23.25Ki ± 0%   23.25Ki ± 0%       ~ (p=0.990 n=10)
kinesis-batch.json                                26.49Ki ± 0%   26.50Ki ± 0%       ~ (p=0.932 n=10)
kinesis.json                                      17.37Ki ± 0%   17.37Ki ± 0%       ~ (p=0.205 n=10)
s3.json                                           19.87Ki ± 0%   19.87Ki ± 0%       ~ (p=0.374 n=10)
sns-batch.json                                    39.07Ki ± 0%   39.07Ki ± 0%       ~ (p=0.323 n=10)
sns.json                                          24.49Ki ± 0%   24.49Ki ± 0%       ~ (p=0.814 n=10)
snssqs.json                                       52.68Ki ± 0%   52.68Ki ± 0%       ~ (p=0.064 n=10)
snssqs_no_dd_context.json                         46.44Ki ± 0%   46.44Ki ± 0%       ~ (p=0.924 n=10)
sqs-aws-header.json                               18.77Ki ± 0%   18.78Ki ± 0%  +0.04% (p=0.037 n=10)
sqs-batch.json                                    41.26Ki ± 0%   41.26Ki ± 0%       ~ (p=0.356 n=10)
sqs.json                                          25.39Ki ± 0%   25.39Ki ± 0%       ~ (p=0.473 n=10)
sqs_no_dd_context.json                            21.01Ki ± 0%   21.01Ki ± 0%       ~ (p=0.426 n=10)
stepfunction.json                                 13.51Ki ± 0%   13.51Ki ± 0%  +0.00% (p=0.033 n=10)
geomean                                           24.08Ki        24.08Ki       +0.00%

                                      │ baseline/benchmark.log │        current/benchmark.log        │
                                      │       allocs/op        │ allocs/op   vs base                 │
api-gateway-appsec.json                             630.0 ± 0%   630.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-kong-appsec.json                        488.0 ± 0%   488.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-kong.json                               466.0 ± 0%   466.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-non-proxy-async.json                    723.0 ± 0%   723.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-non-proxy.json                          713.0 ± 0%   713.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-websocket-connect.json                  451.0 ± 0%   451.0 ± 0%       ~ (p=1.000 n=10)
api-gateway-websocket-default.json                  376.0 ± 0%   376.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway-websocket-disconnect.json               366.0 ± 0%   366.0 ± 0%       ~ (p=1.000 n=10) ¹
api-gateway.json                                    785.0 ± 0%   785.0 ± 0%       ~ (p=1.000 n=10) ¹
application-load-balancer.json                      348.0 ± 0%   348.0 ± 0%       ~ (p=1.000 n=10) ¹
cloudfront.json                                     281.0 ± 0%   281.0 ± 0%       ~ (p=1.000 n=10) ¹
cloudwatch-events.json                              218.0 ± 0%   218.0 ± 0%       ~ (p=1.000 n=10) ¹
cloudwatch-logs.json                                211.0 ± 0%   211.0 ± 0%       ~ (p=1.000 n=10) ¹
custom.json                                         166.0 ± 0%   166.0 ± 0%       ~ (p=1.000 n=10) ¹
dynamodb.json                                       582.0 ± 0%   582.0 ± 0%       ~ (p=1.000 n=10) ¹
empty.json                                          157.0 ± 0%   157.0 ± 0%       ~ (p=1.000 n=10) ¹
eventbridge-custom.json                             261.0 ± 0%   261.0 ± 0%       ~ (p=1.000 n=10) ¹
eventbridge-no-bus.json                             252.0 ± 0%   252.0 ± 0%       ~ (p=1.000 n=10) ¹
eventbridge-no-timestamp.json                       252.0 ± 0%   252.0 ± 0%       ~ (p=1.000 n=10) ¹
eventbridgesns.json                                 318.0 ± 0%   318.0 ± 0%       ~ (p=1.000 n=10) ¹
eventbridgesqs.json                                 358.0 ± 0%   358.0 ± 0%       ~ (p=1.000 n=10) ¹
http-api.json                                       424.0 ± 0%   424.0 ± 0%       ~ (p=1.000 n=10) ¹
kinesis-batch.json                                  383.0 ± 0%   383.0 ± 0%       ~ (p=1.000 n=10) ¹
kinesis.json                                        279.0 ± 0%   279.0 ± 0%       ~ (p=1.000 n=10) ¹
s3.json                                             351.0 ± 0%   351.0 ± 0%       ~ (p=1.000 n=10) ¹
sns-batch.json                                      465.0 ± 0%   465.0 ± 0%       ~ (p=1.000 n=10) ¹
sns.json                                            336.0 ± 0%   336.0 ± 0%       ~ (p=1.000 n=10) ¹
snssqs.json                                         460.0 ± 0%   460.0 ± 0%       ~ (p=1.000 n=10) ¹
snssqs_no_dd_context.json                           420.0 ± 0%   420.0 ± 0%       ~ (p=1.000 n=10) ¹
sqs-aws-header.json                                 276.0 ± 0%   276.0 ± 0%       ~ (p=1.000 n=10) ¹
sqs-batch.json                                      500.0 ± 0%   500.0 ± 0%       ~ (p=1.000 n=10) ¹
sqs.json                                            351.0 ± 0%   351.0 ± 0%       ~ (p=1.000 n=10) ¹
sqs_no_dd_context.json                              337.0 ± 0%   337.0 ± 0%       ~ (p=1.000 n=10) ¹
stepfunction.json                                   226.0 ± 0%   226.0 ± 0%       ~ (p=1.000 n=10) ¹
geomean                                             360.0        360.0       +0.00%
¹ all samples are equal

[L3n41c]

👍🏻 LGTM for file owned by @DataDog/container-integrations.

[davidor]

👍 for the file owned by container-platform

[AlexandreYang]

@DataDog/agent-metrics-logs Can I have a review? :)

[AlexandreYang]

/merge

[dd-devflow]

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View all feedbacks in Devflow UI.

---

2024-11-26 10:10:58 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 23m.