[FA][HA Agent][NDMII-3267] Add config_id metadata

[AlexandreYang]

What does this PR do?

[FA]HA Agent Add config_id, ha_agent_enabled, ha_agent_state metadata

Motivation

Motivation: New fields needed for Fleet Automation and HA Agent feature

• config_id: Need for Fleet Automation
• ha_agent_enabled: this is needed to know when to show or not some HA related elements in UI
• ha_agent_state: this is needed to show the Agent State

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Additional Notes

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 0b1e55627c4476098c3015c8afef5ee0598b3dad

Diff per package

package	diff	status	size	ancestor	threshold
datadog-dogstatsd-arm64-deb	0.00MB	✅	56.50MB	56.50MB	0.50MB
datadog-iot-agent-arm64-deb	0.00MB	✅	89.87MB	89.87MB	0.50MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	89.94MB	89.94MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	93.87MB	93.87MB	0.50MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	93.87MB	93.87MB	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
datadog-agent-amd64-deb	0.00MB	✅	911.86MB	911.86MB	0.50MB
datadog-agent-x86_64-rpm	0.00MB	✅	921.60MB	921.60MB	0.50MB
datadog-agent-x86_64-suse	0.00MB	✅	921.60MB	921.60MB	0.50MB
datadog-agent-arm64-deb	0.00MB	✅	899.25MB	899.25MB	0.50MB
datadog-agent-aarch64-rpm	0.00MB	✅	908.97MB	908.97MB	0.50MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	59.01MB	59.01MB	0.50MB
datadog-heroku-agent-amd64-deb	0.00MB	✅	477.81MB	477.81MB	0.50MB
datadog-iot-agent-amd64-deb	0.00MB	✅	93.80MB	93.80MB	0.50MB

Decision

✅ Passed

[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=54326045 --os-family=ubuntu

Note: This applies to commit 359607d

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 28a4a94d-42a2-4395-af45-8173182a8ffa

Baseline: 0b1e556
Comparison: 359607d
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	+3.13	[+2.20, +4.05]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+2.11	[+2.05, +2.18]	1	Logs
➖	quality_gate_idle	memory utilization	+0.51	[+0.47, +0.55]	1	Logs bounds checks dashboard
➖	file_tree	memory utilization	+0.39	[+0.33, +0.45]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.05	[-0.76, +0.87]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.04	[-0.88, +0.96]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	+0.03	[-0.91, +0.96]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	+0.02	[-0.61, +0.66]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.02, +0.02]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.01	[-0.30, +0.27]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.03	[-0.94, +0.88]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.04	[-0.09, +0.01]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	-0.12	[-0.92, +0.67]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.35	[-1.12, +0.43]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	-0.42	[-0.88, +0.04]	1	Logs
➖	quality_gate_logs	% cpu utilization	-3.47	[-6.46, -0.48]	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	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_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_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.

[hush-hush]

Will this state change often ? We want very static data in REDAPL (storage used for this payload).
Also, should we trigger a new payload each time ha state changes or is it OK to wait for the next payload interval ?

[AlexandreYang]

@hush-hush

Will this state change often ? We want very static data in REDAPL (storage used for this payload).

The state field can indeed change, but it changes very rarely. Example: in HA setup, we have agent1 (state:active) and agent2 (state:standby), agent2 might change its state to active, but only when agent1 is down/crashes.

Also, customer that will use the HA Agent feature will be very limited (likely only large customers that are willing to run 2 agents in active/standby to get fault tolerance).

I think it shouldn't create additional actual writes to REDAPL, since the change frequency is very low, and only few customers will use HA.

Also, should we trigger a new payload each time ha state changes or is it OK to wait for the next payload interval ?

If should be OK for this case, we can wait for next payload interval. The REDAPL backend guarantee is 5min anyway :)

[hush-hush]

We resend payload to REDAPL every 10min if we don't get any updates. And this interval might be expanded at some point to lower the load on our backend services.

[hush-hush]

Added one last comment about the README. Feel free to merge after that 👍

[AlexandreYang]

/merge

[dd-devflow]

Devflow running: /merge

View all feedbacks in Devflow UI.

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2025-01-30 10:22:31 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 26m.

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2025-01-30 10:48:52 UTC ℹ️ MergeQueue: This merge request was merged