datadog-agent
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processes: autodetect service name from node package.json
What does this PR do?
Improve the service name extraction algorithm by adding an heuristic on nodejs processes. It finds the nearest package js starting from the directory where the js entrypoint script resides walking up till the root until a package.js is found.
Then it takes the value of the name field.
This algorithm is the standard one implemented in the js tracer. Here we're aligning to it.
Please note that this extraction is opt in (system_probe_config.process_service_inference.use_improved_algorithm has to be explicitly set to true)
Motivation
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: 10a23048-c18e-4924-ae68-d3ad41caf647 Baseline: ccfc50490988fee22cafc0a11ec127aa2ca6327a Comparison: a320911035cb71231599da01fbd618a680505320
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 | +0.25 | [-6.30, +6.79] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_tree | memory utilization | +1.17 | [+1.05, +1.29] |
| ➖ | otel_to_otel_logs | ingress throughput | +1.06 | [+0.41, +1.71] |
| ➖ | idle | memory utilization | +0.92 | [+0.88, +0.97] |
| ➖ | process_agent_standard_check | memory utilization | +0.43 | [+0.39, +0.48] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | +0.41 | [+0.35, +0.46] |
| ➖ | file_to_blackhole | % cpu utilization | +0.25 | [-6.30, +6.79] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +0.13 | [-1.33, +1.58] |
| ➖ | trace_agent_json | ingress throughput | +0.03 | [+0.01, +0.06] |
| ➖ | trace_agent_msgpack | ingress throughput | +0.03 | [+0.01, +0.04] |
| ➖ | 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] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.28 | [-0.33, -0.24] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.37 | [-1.43, -1.30] |
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".
Go Package Import Differences
Baseline: 06321a2ec53270337eb29a9fbe60ac68e923ba53 Comparison: 7a63b7b9f557ab74d1278c0eb2b0671d43264b95
| binary | os | arch | change |
|---|---|---|---|
| process-agent | linux | amd64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
| process-agent | linux | arm64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
| process-agent | windows | amd64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
| process-agent | darwin | amd64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
| process-agent | darwin | arm64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
| heroku-process-agent | linux | amd64 | +1, -0
+github.com/DataDog/datadog-agent/pkg/process/metadata/parser/nodejs
|
@amarziali why is the PR based on the java spring parsing? I think you should base the logic on top of main and make it to the mainline
/merge
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We have an E2E test for nodejs here, does it need to be updated?
It's a good call. I preferred to keep as it for non regressions since the new logic is behind a feature flag so by default it should not change
Also, what's the reason for adding this behind a config flag? Do we plan to make this algorithm the default for nodejs eventually?
The reason I know is that this algorithm is also linked to the way automatic injection is inferring the service name and we want to put it behind a feature flag in order to control how this can be rolled out not to impact existing customer on metrics / monitors that can then break
/merge
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