agentless-scanner on Azure

[diogocp]

trafficstars

What does this PR do?

Initial implementation of Azure disk scanning for the agentless-scanner. Only supports offline mode at the moment, pending scheduler support.

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[bits-bot]

All committers have signed the CLA.

[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=31104165 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 885a3cf7-d97d-40f8-902f-6cd30894e8d1 Baseline: 44fc17f0e6e0fe266994df1ddb55fabb3d969d8d Comparison: 28b63a0b717e2bd9246ea90df168c6c5922de794

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

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

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

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	+1.10	[-4.98, +7.18]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	pycheck_1000_100byte_tags	% cpu utilization	+4.66	[-0.37, +9.68]
➖	file_tree	memory utilization	+3.93	[+3.83, +4.03]
➖	tcp_syslog_to_blackhole	ingress throughput	+1.62	[+1.53, +1.71]
➖	file_to_blackhole	% cpu utilization	+1.10	[-4.98, +7.18]
➖	process_agent_standard_check_with_stats	memory utilization	+0.52	[+0.47, +0.56]
➖	otel_to_otel_logs	ingress throughput	+0.34	[-0.06, +0.75]
➖	idle	memory utilization	+0.24	[+0.21, +0.27]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.19	[-2.69, +3.06]
➖	process_agent_standard_check	memory utilization	+0.10	[+0.04, +0.15]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.03	[-0.00, +0.06]
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.20, +0.20]
➖	trace_agent_msgpack	ingress throughput	-0.00	[-0.02, +0.01]
➖	trace_agent_json	ingress throughput	-0.01	[-0.04, +0.02]
➖	process_agent_real_time_mode	memory utilization	-0.31	[-0.36, -0.27]
➖	basic_py_check	% cpu utilization	-3.36	[-5.82, -0.90]

Explanation

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".