[Versa] Improvements from Customer Feedback

[ken-schneider]

What does this PR do?

A few improvements/additional options for the Versa integration based on customer feedback.

1. Separate out lookback times for endpoints where data is not available within the default time window.
2. Expose option to use a different endpoint for Appliances (less rich data, but better performance in larger environments)
3. Expose timeout option
4. Expose flag to change query params for different Versa versions

Motivation

Based on customer feedback, a few improvements were made/additional configuration flags exposed.

Describe how you validated your changes

Tested against our internal environment and with some early customers.

Additional Notes

[agent-platform-auto-pr]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 3b8a0ac

Successful checks

Info

	Quality gate	Delta	On disk size (MiB)	Delta	On wire size (MiB)
✅	agent_deb_amd64	DataNotFound	$${706.31}$$ < $${717.44}$$	DataNotFound	$${172.66}$$ < $${177.37}$$
✅	agent_deb_amd64_fips	DataNotFound	$${700.59}$$ < $${711.66}$$	DataNotFound	$${171.43}$$ < $${174.84}$$
✅	agent_heroku_amd64	DataNotFound	$${328.88}$$ < $${337.57}$$	DataNotFound	$${87.52}$$ < $${90.78}$$
✅	agent_msi	DataNotFound	$${1000.63}$$ < $${1015.38}$$	DataNotFound	$${144.44}$$ < $${149.42}$$
✅	agent_rpm_amd64	DataNotFound	$${706.3}$$ < $${717.41}$$	DataNotFound	$${175.75}$$ < $${178.01}$$
✅	agent_rpm_amd64_fips	DataNotFound	$${700.58}$$ < $${711.64}$$	DataNotFound	$${173.51}$$ < $${177.26}$$
✅	agent_rpm_arm64	DataNotFound	$${691.59}$$ < $${702.19}$$	DataNotFound	$${159.68}$$ < $${163.22}$$
✅	agent_rpm_arm64_fips	DataNotFound	$${687.01}$$ < $${697.6}$$	DataNotFound	$${158.96}$$ < $${162.68}$$
✅	agent_suse_amd64	DataNotFound	$${706.3}$$ < $${717.41}$$	DataNotFound	$${175.75}$$ < $${178.01}$$
✅	agent_suse_amd64_fips	DataNotFound	$${700.58}$$ < $${711.64}$$	DataNotFound	$${173.51}$$ < $${177.26}$$
✅	agent_suse_arm64	DataNotFound	$${691.59}$$ < $${702.19}$$	DataNotFound	$${159.68}$$ < $${163.22}$$
✅	agent_suse_arm64_fips	DataNotFound	$${687.01}$$ < $${697.6}$$	DataNotFound	$${158.96}$$ < $${162.68}$$
✅	docker_agent_amd64	DataNotFound	$${768.7}$$ < $${769.92}$$	DataNotFound	$${260.5}$$ < $${261.52}$$
✅	docker_agent_arm64	DataNotFound	$${778.33}$$ < $${779.46}$$	DataNotFound	$${250.77}$$ < $${251.72}$$
✅	docker_agent_jmx_amd64	DataNotFound	$${959.57}$$ < $${960.8}$$	DataNotFound	$${329.15}$$ < $${330.15}$$
✅	docker_agent_jmx_arm64	DataNotFound	$${957.8}$$ < $${958.93}$$	DataNotFound	$${315.38}$$ < $${316.35}$$
✅	docker_cluster_agent_amd64	DataNotFound	$${179.2}$$ < $${207.49}$$	DataNotFound	$${63.22}$$ < $${70.2}$$
✅	docker_cluster_agent_arm64	DataNotFound	$${196.69}$$ < $${223.38}$$	DataNotFound	$${59.95}$$ < $${66.42}$$
✅	docker_cws_instrumentation_amd64	DataNotFound	$${7.07}$$ < $${7.12}$$	DataNotFound	$${2.95}$$ < $${3.29}$$
✅	docker_cws_instrumentation_arm64	DataNotFound	$${6.69}$$ < $${6.92}$$	DataNotFound	$${2.7}$$ < $${3.07}$$
✅	docker_dogstatsd_amd64	DataNotFound	$${38.54}$$ < $${39.3}$$	DataNotFound	$${14.9}$$ < $${15.76}$$
✅	docker_dogstatsd_arm64	DataNotFound	$${37.18}$$ < $${37.94}$$	DataNotFound	$${14.34}$$ < $${14.83}$$
✅	dogstatsd_deb_amd64	DataNotFound	$${29.76}$$ < $${30.53}$$	DataNotFound	$${7.85}$$ < $${8.75}$$
✅	dogstatsd_deb_arm64	DataNotFound	$${28.28}$$ < $${29.11}$$	DataNotFound	$${6.79}$$ < $${7.71}$$
✅	dogstatsd_rpm_amd64	DataNotFound	$${29.76}$$ < $${30.53}$$	DataNotFound	$${7.86}$$ < $${8.76}$$
✅	dogstatsd_suse_amd64	DataNotFound	$${29.76}$$ < $${30.53}$$	DataNotFound	$${7.86}$$ < $${8.76}$$
✅	iot_agent_deb_amd64	DataNotFound	$${42.48}$$ < $${43.19}$$	DataNotFound	$${11.09}$$ < $${11.98}$$
✅	iot_agent_deb_arm64	DataNotFound	$${40.21}$$ < $${40.92}$$	DataNotFound	$${9.55}$$ < $${10.45}$$
✅	iot_agent_deb_armhf	DataNotFound	$${40.14}$$ < $${40.86}$$	DataNotFound	$${9.66}$$ < $${10.56}$$
✅	iot_agent_rpm_amd64	DataNotFound	$${42.48}$$ < $${43.19}$$	DataNotFound	$${11.11}$$ < $${12.0}$$
✅	iot_agent_suse_amd64	DataNotFound	$${42.48}$$ < $${43.19}$$	DataNotFound	$${11.11}$$ < $${12.0}$$

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 75fdbab7-fddb-412b-9d70-b2e1a380bff0

Baseline: 4e29f89
Comparison: 65b83db
Diff

Optimization Goals: ✅ No significant changes detected

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	-1.15	[-4.09, +1.79]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	ddot_metrics_sum_cumulative	memory utilization	+0.83	[+0.68, +0.97]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	+0.24	[+0.01, +0.48]	1	Logs
➖	docker_containers_memory	memory utilization	+0.24	[+0.15, +0.33]	1	Logs
➖	ddot_metrics_sum_delta	memory utilization	+0.16	[-0.03, +0.35]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	+0.15	[+0.10, +0.20]	1	Logs
➖	quality_gate_idle	memory utilization	+0.08	[+0.03, +0.13]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.02	[-0.36, +0.39]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.12, +0.13]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	-0.00	[-0.14, +0.13]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.08, +0.07]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.01	[-0.42, +0.40]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.04	[-0.08, +0.01]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.05	[-0.46, +0.35]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.09	[-0.14, -0.04]	1	Logs bounds checks dashboard
➖	otlp_ingest_metrics	memory utilization	-0.23	[-0.37, -0.09]	1	Logs
➖	ddot_logs	memory utilization	-0.23	[-0.29, -0.18]	1	Logs
➖	file_tree	memory utilization	-0.34	[-0.39, -0.29]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.41	[-0.48, -0.33]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	-0.62	[-0.83, -0.41]	1	Logs bounds checks dashboard
➖	ddot_metrics	memory utilization	-0.63	[-0.85, -0.42]	1	Logs
➖	quality_gate_logs	% cpu utilization	-0.88	[-2.36, +0.60]	1	Logs bounds checks dashboard
➖	otlp_ingest_logs	memory utilization	-1.09	[-1.18, -0.99]	1	Logs
➖	docker_containers_cpu	% cpu utilization	-1.15	[-4.09, +1.79]	1	Logs

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	links
✅	docker_containers_cpu	simple_check_run	10/10
✅	docker_containers_memory	memory_usage	10/10
✅	docker_containers_memory	simple_check_run	10/10
✅	file_to_blackhole_0ms_latency	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency	lost_bytes	10/10
✅	file_to_blackhole_1000ms_latency	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_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	bounds checks dashboard
✅	quality_gate_logs	lost_bytes	10/10	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	bounds checks dashboard
✅	quality_gate_metrics_logs	lost_bytes	10/10	bounds checks dashboard
✅	quality_gate_metrics_logs	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_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check memory_usage: 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.
• 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_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.

[Sophie-Ruetschi]

What is the advantage of holding onto a string and a float representation of the same metric in this case?

[ken-schneider]

The string comes to us from the API, we have to convert it to a float to send it as a metric. We have a separate parsing function which should act as a point of failure in the case that a bad value gets sent back to us so we fail in the parser rather than the piece of code that sends the metrics.