Serverless FIPS #33799
Serverless FIPS #33799
Conversation
|
|
Static quality checks ✅Please find below the results from static quality gates Successful checksInfo
|
Uncompressed package size comparisonComparison with ancestor Diff per package
Decision✅ Passed |
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: f4b1c7c Optimization Goals: ✅ No significant changes detected
|
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | file_to_blackhole_0ms_latency_http2 | egress throughput | +0.04 | [-0.82, +0.90] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http1 | egress throughput | +0.03 | [-0.83, +0.89] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.03 | [-0.66, +0.71] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.02 | [-0.83, +0.87] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.03, +0.03] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.00 | [-0.28, +0.27] | 1 | Logs |
| ➖ | file_to_blackhole_300ms_latency | egress throughput | -0.01 | [-0.64, +0.62] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.02 | [-0.80, +0.75] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.05 | [-0.83, +0.73] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | -0.10 | [-0.15, -0.05] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.20 | [-0.29, -0.11] | 1 | Logs bounds checks dashboard |
| ➖ | file_tree | memory utilization | -0.21 | [-0.34, -0.09] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | -0.33 | [-0.80, +0.13] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.44 | [-1.28, +0.40] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | -1.26 | [-4.05, +1.53] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.32 | [-1.37, -1.26] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -1.64 | [-1.72, -1.55] | 1 | Logs bounds checks dashboard |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | 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 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_300ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_300ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | |
| ✅ | quality_gate_logs | 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:
-
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".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
a15eadb to
3264cf1
Compare
Test changes on VMUse this command from test-infra-definitions to manually test this PR changes on a VM: dda inv aws.create-vm --pipeline-id=59460770 --os-family=ubuntuNote: This applies to commit 6a791a7 |
cdafae7 to
87e3aca
Compare
87e3aca to
f83a18b
Compare
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 |
f83a18b to
9ba256e
Compare
9ba256e to
24f5b81
Compare
bfffc8a to
6a791a7
Compare
|
/merge |
|
View all feedbacks in Devflow UI.
The expected merge time in
|
In order to support FIPS flavored go agent builds (added in DataDog/datadog-agent#33799 ) we're making the following changes: - refactoring the build pipeline to add fips flavors - rearranging the environment datasource to make it a dictionary instead of a list - replacing our old publish_govcloud.sh script with a new publish_govcloud_layers.sh script which uses the same publish layers script as the commercial gitlab job
What does this PR do?
In conjunction with the datadog-lambda-extension build process intoroduced in DataDog/datadog-lambda-extension#556 we are adding support for FIPS in the agent with goboring.
Describe how you validated your changes
Reviewed tests here. Also deployed a wide array of self-monitoring lambda functions to a govcloud region talking to a datadog org in ddog-gov.
Possible Drawbacks / Trade-offs
We chose to go with the goboring approach rather than the msgo approach because the latter would have required more substantial tooling changes for our build system.