datadog-agent
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[ASCII-1022] Use status component for security agent
What does this PR do?
Migrate security agent to use the status component to render the status response and build the flare information.
To use the status component with the current code of the security agent we had to extend the status component interface. We added:
- LoadProvider
- LoadHeaderProvider
Those two functions allow us to pass providers after the status component has been initialized. (In the future when the compliance and runtime agent we can use the normal FX value group logic to inject the status providers)
I added test to make sure the logic of reorganizing providers is correct.
With those changes we were able to simplify the security agent server and flare generation 😄
The templates added to the new status providers are a copy from the ones in pkg/status/render/templates/*. I'm not deleting those templates until the migration for the status component is fully done. That way if at any time I have to revert we can easily go back to use the pkg/status package.
Motivation
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
- Validate that the security agent status output is correct. Both text
security-agent statusand JOSNsecurity-agent status -p - Generating a security agent flare remains to work as expected.
security-agent flare
Go Package Import Differences
Baseline: 2c3ae7299428a34eb4e4de3ab15f5c4f34d76177 Comparison: 0850d2496b54669647de0d7e74dd3d06fe383522
| binary | os | arch | change |
|---|---|---|---|
| security-agent | linux | amd64 | +15, -0
+github.com/DataDog/datadog-agent/comp/core/status/statusimpl
+github.com/DataDog/datadog-agent/comp/metadata/host
+github.com/DataDog/datadog-agent/comp/metadata/host/hostimpl
+github.com/DataDog/datadog-agent/comp/metadata/resources
+github.com/DataDog/datadog-agent/comp/metadata/runner
+github.com/DataDog/datadog-agent/comp/metadata/runner/runnerimpl
+github.com/DataDog/datadog-agent/pkg/gohai
+github.com/DataDog/datadog-agent/pkg/gohai/cpu
+github.com/DataDog/datadog-agent/pkg/gohai/filesystem
+github.com/DataDog/datadog-agent/pkg/gohai/memory
+github.com/DataDog/datadog-agent/pkg/gohai/network
+github.com/DataDog/datadog-agent/pkg/gohai/platform
+github.com/DataDog/datadog-agent/pkg/gohai/processes
+github.com/DataDog/datadog-agent/pkg/gohai/processes/gops
+github.com/DataDog/datadog-agent/pkg/gohai/utils
|
| security-agent | linux | arm64 | +15, -0
+github.com/DataDog/datadog-agent/comp/core/status/statusimpl
+github.com/DataDog/datadog-agent/comp/metadata/host
+github.com/DataDog/datadog-agent/comp/metadata/host/hostimpl
+github.com/DataDog/datadog-agent/comp/metadata/resources
+github.com/DataDog/datadog-agent/comp/metadata/runner
+github.com/DataDog/datadog-agent/comp/metadata/runner/runnerimpl
+github.com/DataDog/datadog-agent/pkg/gohai
+github.com/DataDog/datadog-agent/pkg/gohai/cpu
+github.com/DataDog/datadog-agent/pkg/gohai/filesystem
+github.com/DataDog/datadog-agent/pkg/gohai/memory
+github.com/DataDog/datadog-agent/pkg/gohai/network
+github.com/DataDog/datadog-agent/pkg/gohai/platform
+github.com/DataDog/datadog-agent/pkg/gohai/processes
+github.com/DataDog/datadog-agent/pkg/gohai/processes/gops
+github.com/DataDog/datadog-agent/pkg/gohai/utils
|
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: febd021f-73fd-4e85-b2d7-2ac2d6755f98 Baseline: 2c3ae7299428a34eb4e4de3ab15f5c4f34d76177 Comparison: 0850d2496b54669647de0d7e74dd3d06fe383522
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
Experiments with missing or malformed data
- basic_py_check
Usually, this warning means that there is no usable optimization goal data for that experiment, which could be a result of misconfiguration.
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 | +1.04 | [-5.53, +7.61] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | process_agent_standard_check_with_stats | memory utilization | +1.47 | [+1.43, +1.50] |
| ➖ | file_to_blackhole | % cpu utilization | +1.04 | [-5.53, +7.61] |
| ➖ | process_agent_real_time_mode | memory utilization | +0.83 | [+0.80, +0.86] |
| ➖ | idle | memory utilization | +0.59 | [+0.55, +0.62] |
| ➖ | file_tree | memory utilization | +0.47 | [+0.41, +0.53] |
| ➖ | process_agent_standard_check | memory utilization | +0.31 | [+0.28, +0.35] |
| ➖ | trace_agent_msgpack | ingress throughput | +0.01 | [-0.01, +0.03] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.00, +0.00] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.00, +0.00] |
| ➖ | trace_agent_json | ingress throughput | -0.03 | [-0.07, +0.00] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.05 | [-1.49, +1.39] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.05 | [-0.11, +0.01] |
| ➖ | otel_to_otel_logs | ingress throughput | -1.11 | [-1.75, -0.47] |
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:
-
Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
-
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.
-
Its configuration does not mark it "erratic".
/merge
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