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[Backport 7.73.x] Enable retry on rate limit errors in datadog-api-client calls
#43307
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### What does this PR do? Adds `enable_retry=True` to all `Configuration` instances used with the Datadog API client to enable automatic retry handling for HTTP 429 (rate limit) and 5xx backend errors. ### Motivation The `dynamic_test-evaluate-e2e` job and likely others have been intermittently failing with "Too Many Requests" errors when calling the Datadog CI Visibility API, for instance: - https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/1248067205 - https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/1247686220 The `datadog-api-client` library has built-in retry support that automatically respects the `Retry-After` header on HTTP 429 responses and uses exponential backoff with sensible defaults (`factor=2`, `max_retries=3`) for other failures. ### Describe how you validated your changes - verified that `Configuration(enable_retry=True)` enables automatic retry with `Retry-After` header handling for HTTP 429 responses, - applied consistently across all Datadog API client usage in the codebase. ### Additional Notes Also inlined `Configuration` construction for single-use cases following idiomatic Python style. Co-authored-by: regis.desgroppes <[email protected]> (cherry picked from commit 1eaade1)
Static quality checks✅ Please find below the results from static quality gates Successful checksInfo
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 4229d6d Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ✅ | docker_containers_cpu | % cpu utilization | -38.96 | [-39.98, -37.93] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | quality_gate_logs | % cpu utilization | +4.18 | [+1.32, +7.04] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_metrics_logs | memory utilization | +1.46 | [+1.22, +1.71] | 1 | Logs bounds checks dashboard |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | +0.52 | [+0.47, +0.58] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | +0.19 | [+0.15, +0.23] | 1 | Logs bounds checks dashboard |
| ➖ | docker_containers_memory | memory utilization | +0.13 | [-0.38, +0.64] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | +0.09 | [-0.06, +0.24] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | +0.05 | [-0.01, +0.11] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.05 | [-0.54, +0.65] | 1 | Logs |
| ➖ | otlp_ingest_logs | memory utilization | +0.05 | [-0.04, +0.14] | 1 | Logs |
| ➖ | ddot_metrics | memory utilization | +0.05 | [-0.14, +0.24] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.03 | [-0.58, +0.64] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.02 | [-0.21, +0.25] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | +0.01 | [-0.03, +0.05] | 1 | Logs bounds checks dashboard |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.01, +0.01] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.04 | [-0.65, +0.57] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | -0.07 | [-0.67, +0.54] | 1 | Logs |
| ➖ | ddot_metrics_sum_delta | memory utilization | -0.36 | [-0.53, -0.19] | 1 | Logs |
| ➖ | file_tree | memory utilization | -0.40 | [-0.44, -0.35] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulative | memory utilization | -0.56 | [-0.69, -0.43] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulativetodelta_exporter | memory utilization | -0.57 | [-0.78, -0.36] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.92 | [-2.00, -1.84] | 1 | Logs |
| ✅ | docker_containers_cpu | % cpu utilization | -38.96 | [-39.98, -37.93] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | |
| ✅ | 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_100ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_100ms_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 | bounds checks dashboard |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | memory_usage | 10/10 | bounds checks dashboard |
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:
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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".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, 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_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 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.
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Backport 1eaade1 from #43295.
What does this PR do?
Adds
enable_retry=Trueto allConfigurationinstances used with the Datadog API client to enable automatic retry handling for HTTP 429 (rate limit) and 5xx backend errors.Motivation
The
dynamic_test-evaluate-e2ejob and likely others have been intermittently failing with "Too Many Requests" errors when calling the Datadog CI Visibility API, for instance:The
datadog-api-clientlibrary has built-in retry support that automatically respects theRetry-Afterheader on HTTP 429 responses and uses exponential backoff with sensible defaults (factor=2,max_retries=3) for other failures.Describe how you validated your changes
Configuration(enable_retry=True)enables automatic retry withRetry-Afterheader handling for HTTP 429 responses,Additional Notes
Also inlined
Configurationconstruction for single-use cases following idiomatic Python style.