[NDMII-3083] add snmp autodiscovery to agent status

[jedupau]

What does this PR do?

This PR adds two expvars in both of the snmp autodiscovery to expose the status of the autodiscovery and show them in the agent status. Each expvars contains two maps counting respectively the number of devices scanned and the number of devices found in the subnet. If the number of devices scanned in the subnet is inferior to the number of ips in the subnet it writes "subnet scanning", else it writes the number of devices found in the subnet

Motivation

We want to gain visibility on the autodiscovery

Describe how to test/QA your changes

Run the agent with the autodiscovery config and check that the status of the autodiscovery is present in the agent status

Possible Drawbacks / Trade-offs

Additional Notes

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 10da522d-e3f3-43fd-a05a-3e55fd01ab98

Baseline: f71aacb3de108cc4131961ff7003357fea74f6d0 Comparison: ee03e2ef88bbb2e13d1f71f7278ca5ad885204f1 Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	pycheck_lots_of_tags	% cpu utilization	+0.75	[-2.62, +4.13]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.68	[-0.04, +1.40]	1	Logs
➖	quality_gate_idle	memory utilization	+0.38	[+0.33, +0.43]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.18	[-0.31, +0.66]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.05	[-0.05, +0.15]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.05	[-0.20, +0.29]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.01	[-0.24, +0.26]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.01	[-0.42, +0.45]	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	[-0.19, +0.19]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.09, +0.08]	1	Logs
➖	file_tree	memory utilization	-0.22	[-0.35, -0.09]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-1.02	[-1.09, -0.95]	1	Logs
➖	basic_py_check	% cpu utilization	-2.49	[-6.28, +1.30]	1	Logs

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	quality_gate_idle	memory_usage	7/10	bounds checks dashboard
❌	file_to_blackhole_0ms_latency	lost_bytes	9/10
❌	file_to_blackhole_100ms_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_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_latency	memory_usage	10/10
✅	file_to_blackhole_500ms_latency	memory_usage	10/10
✅	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".

[pr-commenter[bot]]

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=48543316 --os-family=ubuntu

Note: This applies to commit ee03e2ef

[jedupau]

/merge

[dd-devflow[bot]]

Devflow running: /merge

View all feedbacks in Devflow UI.

---

2024-11-08 12:12:22 UTC :information_source: MergeQueue: pull request added to the queue

The median merge time in main is 24m.