Update serverless-init Cloud Run service to support cloud run functions vs Cloud Functions#29307
Update serverless-init Cloud Run service to support cloud run functions vs Cloud Functions#29307nina9753 wants to merge 16 commits into
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…ns via cloud functions
Test changes on VMUse this command from test-infra-definitions to manually test this PR changes on a VM: inv create-vm --pipeline-id=44405040 --os-family=ubuntuNote: This applies to commit b63215b |
Regression DetectorRegression Detector ResultsRun ID: 9fd97ba8-2a83-438d-8e5c-60e26c2e9df6 Metrics dashboard Target profiles Baseline: edc716f Performance changes are noted in the perf column of each table:
No significant changes in experiment optimization goalsConfidence level: 90.00% There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +0.42 | [+0.37, +0.46] | 1 | Logs |
| ➖ | file_tree | memory utilization | +0.40 | [+0.29, +0.50] | 1 | Logs |
| ➖ | idle | memory utilization | +0.20 | [+0.16, +0.25] | 1 | Logs |
| ➖ | otel_to_otel_logs | ingress throughput | +0.07 | [-0.75, +0.89] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.00, +0.00] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.20 | [-0.96, +0.55] | 1 | Logs |
| ➖ | basic_py_check | % cpu utilization | -1.33 | [-4.11, +1.45] | 1 | Logs |
| ➖ | pycheck_lots_of_tags | % cpu utilization | -1.46 | [-4.09, +1.18] | 1 | Logs |
Bounds Checks
| perf | experiment | bounds_check_name | replicates_passed |
|---|---|---|---|
| ✅ | idle | memory_usage | 10/10 |
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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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Its configuration does not mark it "erratic".
…less-init-support
…less-init-support
Serverless Benchmark Results
tl;drUse these benchmarks as an insight tool during development.
What is this benchmarking?The The benchmark is run using a large variety of lambda request payloads. In the charts below, there is one row for each event payload type. How do I interpret these charts?The charts below comes from The benchstat docs explain how to interpret these charts.
I need more helpFirst off, do not worry if the benchmarks are failing. They are not tests. The intention is for them to be a tool for you to use during development. If you would like a hand interpreting the results come chat with us in Benchmark stats |
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What does this PR do?
Update serverless-init Cloud Run service to support Cloud Run functions
This adds the other environmental variables returned by cloud run and cloud run functions into the tag array.
K_CONFIGURATION,FUNCTION_SIGNATURE_TYPE,FUNCTION_TARGETThis also updates the metric prefix to be
gcp.cloudfunctionand the origin iscloudfunctionMotivation
Google Cloud Run Function now supports sidecars under cloud run
Additional Notes
Currently blocks PR #29057 which will update the origin to
cloudrunfunctionwhen we make this product GAPossible Drawbacks / Trade-offs
Currently, this approach will work for all runtimes except Go. Which does not have any out of the box environmental variables we could use to mark a service as a cloud function source deploy. We will need to force the customer to add
FUNCTION_TARGETto the variables during setup so that in datadog everything is tagged correctlyDescribe how to test/QA your changes
added a new test case
TestGetCloudRunFunctionTagsWithEnvironmentVariablesyou can also run all test locally by runninggo test -tags "test" -v ./cmd/serverless-init/...