test/e2e-framework: support kind cluster topology and image customization#48684
Conversation
![chatgpt-codex-connector[bot]](https://avatars.githubusercontent.com/in/1144995?s=60&v=4){kind=small}
There was a problem hiding this comment.
💡 Codex Review
Here are some automated review suggestions for this pull request.
Reviewed commit: 8c28176bd9
ℹ️ About Codex in GitHub
Codex has been enabled to automatically review pull requests in this repo. Reviews are triggered when you
- Open a pull request for review
- Mark a draft as ready
- Comment "@codex review".
If Codex has suggestions, it will comment; otherwise it will react with 👍.
When you sign up for Codex through ChatGPT, Codex can also answer questions or update the PR, like "@codex address that feedback".
| return fmt.Sprintf("kind load docker-image %s --name %s", img, name) | ||
| }).(pulumi.StringOutput), | ||
| }, | ||
| utils.PulumiDependsOn(kindCluster), |
There was a problem hiding this comment.
The image preload commands only use DependsOn(kindCluster) for ordering, but they have no trigger tied to cluster recreation, so Pulumi treats them as unchanged when the Kind cluster is replaced with the same name (for example after topology/version changes or stack updates in dev mode). In that case the new cluster starts without the preloaded images, and agent pods configured with imagePullPolicy: Never can fail to start because the image load step is skipped.
Useful? React with 👍 / 👎.
There was a problem hiding this comment.
Claude suggested to add
// Trigger re-run when the cluster is recreated. KubeConfig changes on
// every new cluster (new TLS certs), so this ensures the image is
// reloaded into the replacement cluster even when the cluster name and
// image haven't changed.
Triggers: pulumi.Array{kindCluster.KubeConfig},which I did.
AlexanderYastrebov
added
qa/done
Files inventory check summaryFile checks results against ancestor bdc7100e: Results for datadog-agent_7.80.0~devel.git.75.6650c0f.pipeline.108726881-1_amd64.deb:No change detected |
4122e59 to
08cd169
Compare
|
This pull request has been automatically marked as stale because it has not had activity in the past 15 days. It will be closed in 30 days if no further activity occurs. If this pull request is still relevant, adding a comment or pushing new commits will keep it open. Also, you can always reopen the pull request if you missed the window. Thank you for your contributions! |
bcdb42c to
4d45763
Compare
…tion Add support for customizing kind cluster topology and pre-loading Docker images into the cluster before the agent is deployed. Co-Authored-By: Claude Sonnet 4.6 <[email protected]>
4d45763 to
6650c0f
Compare
|
/merge |
|
View all feedbacks in Devflow UI.
The expected merge time in
|
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 3fccf8c Optimization Goals: ✅ No significant changes detected
|
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | +0.94 | [-2.04, +3.93] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +2.02 | [+1.83, +2.21] | 1 | Logs |
| ➖ | docker_containers_cpu | % cpu utilization | +0.94 | [-2.04, +3.93] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulative | memory utilization | +0.49 | [+0.33, +0.64] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | +0.47 | [+0.41, +0.54] | 1 | Logs |
| ➖ | ddot_metrics | memory utilization | +0.27 | [+0.10, +0.44] | 1 | Logs |
| ➖ | file_tree | memory utilization | +0.21 | [+0.15, +0.27] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | +0.18 | [+0.11, +0.24] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | +0.07 | [+0.03, +0.11] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | +0.06 | [-0.35, +0.47] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_v3 | ingress throughput | +0.02 | [-0.18, +0.22] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.11, +0.11] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.00 | [-0.20, +0.19] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | -0.07 | [-0.59, +0.46] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.07 | [-0.50, +0.35] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | -0.10 | [-0.21, +0.00] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulativetodelta_exporter | memory utilization | -0.13 | [-0.35, +0.10] | 1 | Logs |
| ➖ | ddot_metrics_sum_delta | memory utilization | -0.13 | [-0.30, +0.05] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | -0.21 | [-0.29, -0.13] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | -0.24 | [-0.40, -0.09] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.45 | [-0.51, -0.40] | 1 | Logs bounds checks dashboard |
| ➖ | otlp_ingest_logs | memory utilization | -0.68 | [-0.77, -0.58] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | -1.46 | [-3.09, +0.18] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_metrics_logs | memory utilization | -1.60 | [-1.83, -1.37] | 1 | Logs bounds checks dashboard |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | observed_value | links |
|---|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | 714 ≥ 26 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | 275.28MiB ≤ 370MiB | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | 659 ≥ 26 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | 0.20GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_0ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | 0.24GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_1000ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | 0.20GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_100ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | 0.22GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_500ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | 4 = 4 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | 176.08MiB ≤ 181MiB | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | 4 = 4 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | 502.44MiB ≤ 550MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | 4 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | 210.75MiB ≤ 220MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | missed_bytes | 10/10 | 0B = 0B | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | 347.73 ≤ 2000 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | 4 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | memory_usage | 10/10 | 421.83MiB ≤ 475MiB | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | missed_bytes | 10/10 | 0B = 0B | 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:
-
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 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 missed_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_logs, 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_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check intake_connections: 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 missed_bytes: 10/10 replicas passed. Gate passed.
2 participants
What does this PR do?
Add support for customizing kind cluster topology and pre-loading Docker images into the cluster before the agent is deployed.
Motivation
Local e2e tests for Spot Scheduling #47429
Describe how you validated your changes
I am testing spot scheduling via #48821 and extracted these changes into a separate PR.
Additional Notes