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[usm] add module name to debugger #31003

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@guyarb guyarb commented Nov 12, 2024

What does this PR do?

Adds module name to the debugger utilities of USM to allow filtering and distinguishing between usm entries to other modules.

Motivation

Allow other modules to easily implement their own debugging endpoints.

Filter out irrelevant entries in the blocked and traced programs output.

Describe how to test/QA your changes

UTs + manual query the debugging endpoints.

Possible Drawbacks / Trade-offs

Additional Notes

@github-actions github-actions bot added component/system-probe long review PR is complex, plan time to review it labels Nov 12, 2024
@guyarb guyarb added changelog/no-changelog team/usm The USM team qa/done Skip QA week as QA was done before merge and regressions are covered by tests labels Nov 12, 2024
The module name will allow us to distinguish between different modules using
attachers, and will allow us to provide only relevant information for the usm
debugging endpoints
@guyarb guyarb force-pushed the guy.arbitman/add-module-name-to-debugger branch from 93570a4 to 7f67340 Compare November 12, 2024 17:24
@guyarb guyarb marked this pull request as ready for review November 12, 2024 17:24
@guyarb guyarb requested review from a team as code owners November 12, 2024 17:24
@guyarb guyarb changed the title Guy.arbitman/add module name to debugger [usm] add module name to debugger Nov 12, 2024
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agent-platform-auto-pr bot commented Nov 12, 2024

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=48885538 --os-family=ubuntu

Note: This applies to commit 264a038

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cit-pr-commenter bot commented Nov 12, 2024

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: f6a0f9e8-2ad2-46ff-95fb-f2fec0105434

Baseline: 0b38b96
Comparison: 264a038
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 +2.97 [-0.52, +6.46] 1 Logs
basic_py_check % cpu utilization +2.20 [-1.70, +6.09] 1 Logs
otel_to_otel_logs ingress throughput +0.85 [+0.19, +1.51] 1 Logs
tcp_syslog_to_blackhole ingress throughput +0.36 [+0.30, +0.41] 1 Logs
file_to_blackhole_500ms_latency egress throughput +0.14 [-0.10, +0.38] 1 Logs
file_to_blackhole_300ms_latency egress throughput +0.11 [-0.09, +0.30] 1 Logs
quality_gate_idle memory utilization +0.07 [+0.03, +0.12] 1 Logs bounds checks dashboard
quality_gate_idle_all_features memory utilization +0.06 [-0.03, +0.16] 1 Logs bounds checks dashboard
file_to_blackhole_100ms_latency egress throughput +0.03 [-0.30, +0.36] 1 Logs
file_to_blackhole_0ms_latency egress throughput +0.01 [-0.43, +0.46] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput -0.00 [-0.01, +0.01] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.01 [-0.10, +0.08] 1 Logs
file_to_blackhole_1000ms_latency egress throughput -0.16 [-0.64, +0.32] 1 Logs
file_to_blackhole_1000ms_latency_linear_load egress throughput -0.44 [-0.93, +0.04] 1 Logs
file_tree memory utilization -0.61 [-0.74, -0.48] 1 Logs
uds_dogstatsd_to_api_cpu % cpu utilization -1.63 [-2.36, -0.90] 1 Logs

Bounds Checks: ❌ Failed

perf experiment bounds_check_name replicates_passed links
file_to_blackhole_100ms_latency lost_bytes 6/10
quality_gate_idle memory_usage 6/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 9/10 bounds checks dashboard
file_to_blackhole_0ms_latency lost_bytes 10/10
file_to_blackhole_0ms_latency 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 memory_usage 10/10
file_to_blackhole_300ms_latency memory_usage 10/10
file_to_blackhole_500ms_latency 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".

registries []*FileRegistry
attachers map[string]Attacher
registries map[string][]*FileRegistry
attachers map[string]map[string]Attacher
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What do you think about flattening the nested map? I feel that the current attachers struct is quite complex. Maybe we should consider adding a struct to improve the current map structure?

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added a syntactic sugar and documentation to make it easier

}

func (d *tlsDebugger) GetTracedPrograms() []TracedProgram {
func (d *tlsDebugger) GetTracedPrograms(moduleName string) []TracedProgram {
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Can you please add documentation to this function?

@@ -78,24 +79,24 @@ func WaitForProgramsToBeTraced(t *testing.T, programType string, pid int, traceM
t.Logf("process %v is not traced by %v, trying to attach manually", pid, programType)

// Get attacher for the program type
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update the documentation to contain your change

if !ok {
d.mux.Unlock()
w.WriteHeader(http.StatusBadRequest)
fmt.Fprintf(w, "module %q is unrecognized", moduleName)
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Maybe we can add unit tests to validate this flow, just to ensure that when we use a module that doesn't exist, everything behaves as expected.

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LGTM for ebpf-platform files other than a minor comment. Thanks for this!

pkg/gpu/probe.go Outdated
@@ -139,7 +139,7 @@ func NewProbe(cfg *config.Config, deps ProbeDependencies) (*Probe, error) {
}
}

p.attacher, err = uprobes.NewUprobeAttacher(gpuAttacherName, attachCfg, p.m, nil, &uprobes.NativeBinaryInspector{}, deps.ProcessMonitor)
p.attacher, err = uprobes.NewUprobeAttacher("gpu", gpuAttacherName, attachCfg, p.m, nil, &uprobes.NativeBinaryInspector{}, deps.ProcessMonitor)
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Can we have a constant gpuAttacherModuleName similar to gpuAttacherName?

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Go Package Import Differences

Baseline: 0b38b96
Comparison: 264a038

binaryosarchchange
system-probelinuxamd64
+1, -0
+github.com/DataDog/datadog-agent/pkg/network/usm/consts
system-probelinuxarm64
+1, -0
+github.com/DataDog/datadog-agent/pkg/network/usm/consts

@@ -32,6 +32,7 @@ import (

const (
gpuAttacherName = "gpu"
gpuModuleName = gpuAttacherName
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i think it would be better to use config.GPUMonitoringModule

(actually i can change all "magic string" references in probe.go in a separate PR)

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unfortunately, no, as it will cause cyclic import
we need to move config.GPUMonitoringModule to be in pkg/

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