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ci: dynamic pipeline#1642

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hoolioh wants to merge 28 commits intomainfrom
julio/rd-week-dynamic-pipeline
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ci: dynamic pipeline#1642
hoolioh wants to merge 28 commits intomainfrom
julio/rd-week-dynamic-pipeline

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@hoolioh
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@hoolioh hoolioh commented Mar 3, 2026 •
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What does this PR do?

Makes all CI workflows dynamic — they detect which crates were changed/affected by a PR and only run jobs for those crates, skipping everything on pushes to main where nothing changed.

Key changes

New crates-reporter composite action (replaces changed-crates)

  • The old action was a bash-heavy composite action doing crate detection in shell script
  • The new one is a compiled Rust binary that uses cargo-metadata to detect changed crates and compute transitive dependants (affected crates), giving a richer output: crates, affected_crates, crates_count, affected_crates_count, status
  • A new ci-shared library crate provides shared logic (git, workspace, crate_detection, github_output) reused across multiple action binaries
  • A shared Cargo.toml/Cargo.lock workspace at .github/actions/ replaces per-action workspaces

test.yml — unit tests now only run on affected packages (direct + transitive dependants), not the full workspace. The cross-centos7 job was made dynamic: it builds the nextest command conditionally based on $PACKAGES/$CRASHTRACKER_FEATURE from the setup stage

test-ffi.yml (new, split from test.yml) — FFI jobs extracted into their own workflow, also driven by the setup stage; only runs when -ffi crates are affected

lint.yml — rustfmt now runs only on directly changed crates; clippy runs on affected crates (since a change can introduce warnings in dependants)

miri.yml — Miri now runs only on affected crates on PRs; still runs --workspace on pushes to main

fuzz.yml — fuzz jobs now filter to only the fuzz-capable crates that were affected

Motivation

Previously, every PR triggered CI jobs against the entire workspace regardless of what changed. With the current approach:

  • Reduces CI runtime and cost by skipping unaffected crates
  • Uses transitive dependency analysis (not just direct changes) so a change in a shared crate still triggers tests for its dependants
  • Replaces a fragile bash-based crate detector with a reliable, tested Rust implementation using cargo-metadata
  • Splits FFI testing into its own workflow for cleaner separation of concerns and run both test jobs (nextests and ffi) in parallel.

Results

The new pipeline has been tested with two crates. libdd-common which is a foundational crate and has a lot of transitive dependencies (almost all workspace) and libdd-data-pipeline-ffi which only has one transitive dependency.

Workflow libddcommon libdd-data-pipeline-ffi
Fuzz ~22m (95%) ~13m (92%)
Miri ~1m (4%) ~23m (92%)
Test ~1m (4%) ~12m (43%)
Lint -1m (-14%, setup overhead) ~6m (50%)
Total wall-clock ~0m (0%) 11m 6s (39%)

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codecov-commenter commented Mar 3, 2026 •
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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.46%. Comparing base (0e8c2c6) to head (f131d99).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1642      +/-   ##
==========================================
+ Coverage   71.35%   71.46%   +0.11%     
==========================================
  Files         429      430       +1     
  Lines       63779    63954     +175     
==========================================
+ Hits        45509    45707     +198     
+ Misses      18270    18247      -23
Components Coverage Δ
libdd-crashtracker 63.90% <ø> (+1.44%) ⬆️
libdd-crashtracker-ffi 17.72% <ø> (+0.08%) ⬆️
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 88.32% <ø> (ø)
libdd-data-pipeline-ffi 76.94% <ø> (ø)
libdd-common 79.73% <ø> (ø)
libdd-common-ffi 73.40% <ø> (ø)
libdd-telemetry 62.48% <ø> (ø)
libdd-telemetry-ffi 16.75% <ø> (ø)
libdd-dogstatsd-client 82.64% <ø> (ø)
datadog-ipc 80.35% <ø> (ø)
libdd-profiling 81.60% <ø> (+0.03%) ⬆️
libdd-profiling-ffi 63.65% <ø> (ø)
datadog-sidecar 32.59% <ø> (-0.06%) ⬇️
datdog-sidecar-ffi 8.50% <ø> (ø)
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 91.80% <ø> (ø)
libdd-trace-protobuf 68.25% <ø> (ø)
libdd-trace-utils 89.08% <ø> (ø)
datadog-tracer-flare 88.95% <ø> (ø)
libdd-log 74.69% <ø> (ø)
🚀 New features to boost your workflow:
  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
  • 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

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github-actions bot commented Mar 3, 2026 •
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Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

  • Base Branch: origin/main
  • PR Branch: origin/julio/rd-week-dynamic-pipeline

Summary by Rule

Rule Base Branch PR Branch Change
unwrap_used 5 5 No change (0%)
Total 5 5 No change (0%)

Annotation Counts by File

File Base Branch PR Branch Change
.github/actions/clippy-annotation-reporter/src/analyzer/annotation.rs 5 5 No change (0%)

Annotation Stats by Crate

Crate Base Branch PR Branch Change
clippy-annotation-reporter 5 5 No change (0%)
datadog-ffe-ffi 1 1 No change (0%)
datadog-ipc 28 28 No change (0%)
datadog-live-debugger 6 6 No change (0%)
datadog-live-debugger-ffi 10 10 No change (0%)
datadog-profiling-replayer 4 4 No change (0%)
datadog-remote-config 3 3 No change (0%)
datadog-sidecar 59 59 No change (0%)
libdd-common 10 10 No change (0%)
libdd-common-ffi 12 12 No change (0%)
libdd-data-pipeline 5 5 No change (0%)
libdd-ddsketch 2 2 No change (0%)
libdd-dogstatsd-client 1 1 No change (0%)
libdd-profiling 13 13 No change (0%)
libdd-telemetry 19 19 No change (0%)
libdd-tinybytes 4 4 No change (0%)
libdd-trace-normalization 2 2 No change (0%)
libdd-trace-obfuscation 9 9 No change (0%)
libdd-trace-utils 15 15 No change (0%)
Total 208 208 No change (0%)

About This Report

This report tracks Clippy allow annotations for specific rules, showing how they've changed in this PR. Decreasing the number of these annotations generally improves code quality.

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pr-commenter bot commented Mar 3, 2026 •
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Benchmarks

Comparison

Benchmark execution time: 2026-03-13 17:05:31

Comparing candidate commit f131d99 in PR branch julio/rd-week-dynamic-pipeline with baseline commit 892b7bf in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 58 metrics, 2 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

  • 🟩 = significantly better candidate vs. baseline
  • 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

Candidate

Candidate benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sql/obfuscate_sql_string execution_time 88.892µs 89.266µs ± 0.288µs 89.234µs ± 0.061µs 89.301µs 89.497µs 89.650µs 92.931µs 4.14% 10.426 130.013 0.32% 0.020µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [89.226µs; 89.306µs] or [-0.045%; +0.045%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
single_flag_killswitch/rules-based execution_time 190.586ns 192.779ns ± 1.875ns 192.606ns ± 1.283ns 193.616ns 196.139ns 198.984ns 201.277ns 4.50% 1.286 2.418 0.97% 0.133ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
single_flag_killswitch/rules-based execution_time [192.519ns; 193.039ns] or [-0.135%; +0.135%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample2_frames_x1000 execution_time 729.259µs 732.854µs ± 1.394µs 732.957µs ± 0.971µs 733.792µs 735.042µs 735.949µs 736.101µs 0.43% -0.020 -0.410 0.19% 0.099µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample2_frames_x1000 execution_time [732.661µs; 733.047µs] or [-0.026%; +0.026%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sdk_test_data/rules-based execution_time 144.524µs 146.537µs ± 1.712µs 146.286µs ± 0.557µs 146.860µs 148.084µs 154.128µs 162.397µs 11.01% 5.538 42.100 1.17% 0.121µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sdk_test_data/rules-based execution_time [146.300µs; 146.774µs] or [-0.162%; +0.162%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
credit_card/is_card_number/ execution_time 3.896µs 3.916µs ± 0.005µs 3.916µs ± 0.002µs 3.917µs 3.920µs 3.925µs 3.966µs 1.28% 6.132 54.146 0.14% 0.000µs 1 200
credit_card/is_card_number/ throughput 252152797.687op/s 255345881.600op/s ± 345965.333op/s 255381349.834op/s ± 103180.582op/s 255480149.202op/s 255591297.225op/s 255677307.107op/s 256675419.416op/s 0.51% -6.056 53.428 0.14% 24463.443op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.599µs 80.014µs ± 0.080µs 80.014µs ± 0.043µs 80.049µs 80.131µs 80.191µs 80.421µs 0.51% 0.162 6.078 0.10% 0.006µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12434537.136op/s 12497817.222op/s ± 12434.468op/s 12497737.285op/s ± 6649.254op/s 12504961.656op/s 12515299.704op/s 12521677.466op/s 12562985.786op/s 0.52% -0.138 6.085 0.10% 879.250op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 67.832µs 67.940µs ± 0.069µs 67.936µs ± 0.038µs 67.974µs 68.026µs 68.077µs 68.557µs 0.91% 3.736 30.956 0.10% 0.005µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 14586406.868op/s 14718952.847op/s ± 14816.484op/s 14719826.258op/s ± 8200.086op/s 14728009.856op/s 14736931.313op/s 14741000.384op/s 14742244.309op/s 0.15% -3.679 30.288 0.10% 1047.684op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.896µs 3.915µs ± 0.003µs 3.915µs ± 0.001µs 3.917µs 3.920µs 3.923µs 3.938µs 0.58% 0.978 17.873 0.08% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 253958489.674op/s 255405186.608op/s ± 206251.686op/s 255434486.259op/s ± 91380.506op/s 255515405.885op/s 255599189.075op/s 255638797.874op/s 256682827.396op/s 0.49% -0.932 17.801 0.08% 14584.197op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 64.592µs 64.694µs ± 0.049µs 64.687µs ± 0.034µs 64.726µs 64.780µs 64.829µs 64.864µs 0.27% 0.692 0.414 0.08% 0.003µs 1 200
credit_card/is_card_number/378282246310005 throughput 15416930.495op/s 15457395.439op/s ± 11696.030op/s 15458978.827op/s ± 8150.430op/s 15465470.630op/s 15473923.190op/s 15476171.390op/s 15481717.640op/s 0.15% -0.687 0.404 0.08% 827.034op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 45.470µs 45.736µs ± 0.106µs 45.740µs ± 0.067µs 45.803µs 45.911µs 45.957µs 45.977µs 0.52% -0.209 -0.092 0.23% 0.007µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 21749977.356op/s 21864601.877op/s ± 50486.559op/s 21862503.635op/s ± 32154.069op/s 21895096.046op/s 21959422.197op/s 21986050.402op/s 21992606.467op/s 0.60% 0.222 -0.087 0.23% 3569.939op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.592µs 6.632µs ± 0.011µs 6.635µs ± 0.004µs 6.639µs 6.645µs 6.648µs 6.650µs 0.23% -1.302 1.469 0.17% 0.001µs 1 200
credit_card/is_card_number/x371413321323331 throughput 150371189.637op/s 150792202.166op/s ± 252838.597op/s 150710993.347op/s ± 99865.490op/s 150879231.478op/s 151293511.403op/s 151600398.411op/s 151688644.431op/s 0.65% 1.310 1.498 0.17% 17878.389op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.900µs 3.915µs ± 0.002µs 3.915µs ± 0.001µs 3.916µs 3.919µs 3.921µs 3.922µs 0.17% -0.710 7.149 0.06% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 255001025.396op/s 255431217.919op/s ± 158838.387op/s 255443323.189op/s ± 89349.374op/s 255527942.841op/s 255636662.040op/s 255689830.362op/s 256433812.917op/s 0.39% 0.726 7.246 0.06% 11231.570op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 65.609µs 65.725µs ± 0.048µs 65.729µs ± 0.033µs 65.757µs 65.798µs 65.833µs 65.856µs 0.19% -0.044 -0.307 0.07% 0.003µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15184580.485op/s 15214940.460op/s ± 11007.941op/s 15213986.208op/s ± 7644.435op/s 15223379.589op/s 15232547.841op/s 15238800.723op/s 15241730.863op/s 0.18% 0.048 -0.308 0.07% 778.379op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 53.366µs 53.431µs ± 0.033µs 53.426µs ± 0.019µs 53.446µs 53.489µs 53.537µs 53.548µs 0.23% 0.936 1.349 0.06% 0.002µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 18674720.637op/s 18715775.514op/s ± 11554.818op/s 18717322.778op/s ± 6512.963op/s 18723425.869op/s 18731697.861op/s 18734459.199op/s 18738673.942op/s 0.11% -0.931 1.336 0.06% 817.049op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.895µs 3.915µs ± 0.003µs 3.915µs ± 0.001µs 3.916µs 3.919µs 3.921µs 3.924µs 0.23% -1.503 14.376 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 254845836.223op/s 255417776.874op/s ± 175660.129op/s 255428390.651op/s ± 83078.840op/s 255507888.808op/s 255633747.578op/s 255734065.462op/s 256724859.979op/s 0.51% 1.532 14.602 0.07% 12421.047op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 50.162µs 50.215µs ± 0.027µs 50.213µs ± 0.016µs 50.231µs 50.257µs 50.293µs 50.341µs 0.25% 0.883 2.100 0.05% 0.002µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 19864512.109op/s 19914217.037op/s ± 10573.077op/s 19915142.574op/s ± 6301.158op/s 19920881.232op/s 19929168.447op/s 19932882.140op/s 19935276.139op/s 0.10% -0.878 2.079 0.05% 747.629op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 45.491µs 45.743µs ± 0.104µs 45.744µs ± 0.072µs 45.816µs 45.899µs 45.972µs 46.009µs 0.58% -0.067 -0.297 0.23% 0.007µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 21735028.957op/s 21861563.312op/s ± 49724.612op/s 21860833.053op/s ± 34312.035op/s 21893451.123op/s 21948263.490op/s 21968877.039op/s 21982284.086op/s 0.56% 0.079 -0.299 0.23% 3516.061op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.595µs 6.632µs ± 0.010µs 6.635µs ± 0.004µs 6.638µs 6.644µs 6.646µs 6.651µs 0.25% -1.162 1.141 0.15% 0.001µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 150346499.363op/s 150791235.433op/s ± 227205.477op/s 150718783.272op/s ± 88449.053op/s 150870697.367op/s 151238316.393op/s 151373574.107op/s 151639820.356op/s 0.61% 1.170 1.166 0.15% 16065.853op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
credit_card/is_card_number/ execution_time [3.916µs; 3.917µs] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/ throughput [255297934.132op/s; 255393829.068op/s] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [80.003µs; 80.025µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12496093.924op/s; 12499540.520op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [67.930µs; 67.949µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ 378282246310005 throughput [14716899.425op/s; 14721006.269op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/37828224631 execution_time [3.915µs; 3.916µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number/37828224631 throughput [255376602.108op/s; 255433771.108op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number/378282246310005 execution_time [64.687µs; 64.701µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/378282246310005 throughput [15455774.481op/s; 15459016.396op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [45.722µs; 45.751µs] or [-0.032%; +0.032%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [21857604.925op/s; 21871598.829op/s] or [-0.032%; +0.032%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.630µs; 6.633µs] or [-0.023%; +0.023%] None None None
credit_card/is_card_number/x371413321323331 throughput [150757161.168op/s; 150827243.163op/s] or [-0.023%; +0.023%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.915µs; 3.915µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ throughput [255409204.446op/s; 255453231.392op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [65.718µs; 65.731µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15213414.866op/s; 15216466.055op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [53.426µs; 53.435µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [18714174.127op/s; 18717376.900op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.915µs; 3.916µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255393432.070op/s; 255442121.678op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [50.212µs; 50.219µs] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [19912751.710op/s; 19915682.364op/s] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [45.728µs; 45.757µs] or [-0.032%; +0.032%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [21854671.959op/s; 21868454.665op/s] or [-0.032%; +0.032%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.630µs; 6.633µs] or [-0.021%; +0.021%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [150759746.939op/s; 150822723.927op/s] or [-0.021%; +0.021%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
concentrator/add_spans_to_concentrator execution_time 13.003ms 13.038ms ± 0.020ms 13.035ms ± 0.008ms 13.047ms 13.061ms 13.077ms 13.241ms 1.57% 5.451 50.515 0.15% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
concentrator/add_spans_to_concentrator execution_time [13.036ms; 13.041ms] or [-0.021%; +0.021%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
redis/obfuscate_redis_string execution_time 32.374µs 33.191µs ± 1.156µs 32.452µs ± 0.049µs 34.783µs 35.183µs 35.248µs 36.005µs 10.95% 0.922 -1.067 3.47% 0.082µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.030µs; 33.351µs] or [-0.483%; +0.483%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching serializing traces from their internal representation to msgpack execution_time 14.673ms 14.725ms ± 0.030ms 14.722ms ± 0.014ms 14.735ms 14.790ms 14.828ms 14.923ms 1.36% 2.365 10.475 0.20% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching serializing traces from their internal representation to msgpack execution_time [14.721ms; 14.729ms] or [-0.028%; +0.028%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
ip_address/quantize_peer_ip_address_benchmark execution_time 4.949µs 5.033µs ± 0.045µs 5.023µs ± 0.028µs 5.051µs 5.105µs 5.110µs 5.111µs 1.76% 0.372 -0.963 0.89% 0.003µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
ip_address/quantize_peer_ip_address_benchmark execution_time [5.027µs; 5.039µs] or [-0.124%; +0.124%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
write only interface execution_time 1.167µs 3.157µs ± 1.430µs 2.987µs ± 0.023µs 3.008µs 3.325µs 13.794µs 15.129µs 406.42% 7.521 57.123 45.16% 0.101µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [2.959µs; 3.356µs] or [-6.275%; +6.275%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time 205.053µs 205.845µs ± 0.582µs 205.677µs ± 0.342µs 206.208µs 207.009µs 207.582µs 208.053µs 1.16% 1.204 1.384 0.28% 0.041µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 4806468.832op/s 4858059.073op/s ± 13688.966op/s 4861984.045op/s ± 8088.027op/s 4867598.685op/s 4873633.533op/s 4875562.734op/s 4876782.810op/s 0.30% -1.188 1.325 0.28% 967.956op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 18.553µs 18.670µs ± 0.098µs 18.640µs ± 0.024µs 18.669µs 18.897µs 19.030µs 19.173µs 2.86% 2.439 6.293 0.52% 0.007µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 52156793.931op/s 53562078.904op/s ± 277483.847op/s 53647263.790op/s ± 69738.016op/s 53702765.904op/s 53790955.177op/s 53836278.511op/s 53898777.183op/s 0.47% -2.402 6.068 0.52% 19621.071op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.674µs 10.806µs ± 0.047µs 10.807µs ± 0.034µs 10.838µs 10.884µs 10.929µs 10.941µs 1.24% 0.031 -0.079 0.44% 0.003µs 1 200
normalization/normalize_name/normalize_name/good throughput 91400535.286op/s 92542647.260op/s ± 404836.464op/s 92533337.065op/s ± 288631.493op/s 92884679.069op/s 93150229.927op/s 93399996.153op/s 93687266.184op/s 1.25% -0.006 -0.090 0.44% 28626.261op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time [205.764µs; 205.926µs] or [-0.039%; +0.039%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [4856161.914op/s; 4859956.232op/s] or [-0.039%; +0.039%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [18.657µs; 18.684µs] or [-0.073%; +0.073%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [53523622.312op/s; 53600535.497op/s] or [-0.072%; +0.072%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.799µs; 10.813µs] or [-0.061%; +0.061%] None None None
normalization/normalize_name/normalize_name/good throughput [92486540.820op/s; 92598753.701op/s] or [-0.061%; +0.061%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
receiver_entry_point/report/2598 execution_time 3.423ms 3.462ms ± 0.042ms 3.447ms ± 0.010ms 3.461ms 3.570ms 3.612ms 3.634ms 5.43% 2.209 4.262 1.22% 0.003ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
receiver_entry_point/report/2598 execution_time [3.456ms; 3.467ms] or [-0.169%; +0.169%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching deserializing traces from msgpack to their internal representation execution_time 49.334ms 49.606ms ± 0.622ms 49.509ms ± 0.050ms 49.568ms 49.683ms 52.935ms 55.673ms 12.45% 7.521 60.686 1.25% 0.044ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching deserializing traces from msgpack to their internal representation execution_time [49.520ms; 49.692ms] or [-0.174%; +0.174%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time 493.379µs 494.244µs ± 0.751µs 494.191µs ± 0.234µs 494.406µs 494.837µs 495.182µs 503.396µs 1.86% 9.145 108.432 0.15% 0.053µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1986506.763op/s 2023297.693op/s ± 3034.568op/s 2023509.129op/s ± 958.930op/s 2024567.167op/s 2025779.827op/s 2026444.327op/s 2026839.407op/s 0.16% -9.023 106.447 0.15% 214.576op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 370.587µs 371.199µs ± 0.282µs 371.174µs ± 0.174µs 371.356µs 371.748µs 371.976µs 372.077µs 0.24% 0.565 0.339 0.08% 0.020µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2687615.421op/s 2693974.003op/s ± 2045.057op/s 2694157.380op/s ± 1259.820op/s 2695396.389op/s 2697091.295op/s 2697716.787op/s 2698423.909op/s 0.16% -0.561 0.332 0.08% 144.607op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 167.313µs 167.660µs ± 0.316µs 167.612µs ± 0.079µs 167.694µs 167.918µs 169.799µs 170.104µs 1.49% 5.616 37.069 0.19% 0.022µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5878750.096op/s 5964483.951op/s ± 11139.715op/s 5966173.600op/s ± 2802.429op/s 5968515.111op/s 5972331.300op/s 5975920.779op/s 5976816.069op/s 0.18% -5.573 36.646 0.19% 787.697op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 37.125µs 37.293µs ± 0.055µs 37.299µs ± 0.038µs 37.333µs 37.371µs 37.395µs 37.441µs 0.38% -0.397 -0.028 0.15% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26708969.485op/s 26814641.121op/s ± 39221.582op/s 26810632.408op/s ± 27645.576op/s 26839819.287op/s 26883582.393op/s 26902049.245op/s 26936342.767op/s 0.47% 0.405 -0.022 0.15% 2773.385op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.400µs 45.627µs ± 0.129µs 45.619µs ± 0.109µs 45.732µs 45.824µs 45.874µs 45.893µs 0.60% 0.071 -1.065 0.28% 0.009µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21789968.431op/s 21917138.075op/s ± 62012.889op/s 21920589.512op/s ± 52200.524op/s 21967805.209op/s 22010929.798op/s 22024127.379op/s 22026604.222op/s 0.48% -0.064 -1.067 0.28% 4384.973op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time [494.140µs; 494.348µs] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [2022877.131op/s; 2023718.255op/s] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [371.160µs; 371.238µs] or [-0.011%; +0.011%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2693690.578op/s; 2694257.428op/s] or [-0.011%; +0.011%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [167.616µs; 167.704µs] or [-0.026%; +0.026%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5962940.093op/s; 5966027.808op/s] or [-0.026%; +0.026%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.286µs; 37.301µs] or [-0.020%; +0.020%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26809205.387op/s; 26820076.855op/s] or [-0.020%; +0.020%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [45.609µs; 45.645µs] or [-0.039%; +0.039%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21908543.685op/s; 21925732.465op/s] or [-0.039%; +0.039%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching string interning on wordpress profile execution_time 161.064µs 161.712µs ± 0.285µs 161.656µs ± 0.131µs 161.818µs 162.143µs 162.878µs 163.213µs 0.96% 2.118 7.482 0.18% 0.020µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching string interning on wordpress profile execution_time [161.672µs; 161.751µs] or [-0.024%; +0.024%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample_frames_x1000 execution_time 4.129ms 4.133ms ± 0.007ms 4.132ms ± 0.001ms 4.134ms 4.137ms 4.142ms 4.220ms 2.12% 11.727 152.006 0.16% 0.000ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample_frames_x1000 execution_time [4.132ms; 4.134ms] or [-0.022%; +0.022%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
two way interface execution_time 18.060µs 25.764µs ± 9.380µs 18.599µs ± 0.428µs 33.972µs 43.235µs 43.742µs 65.890µs 254.26% 0.889 0.148 36.32% 0.663µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [24.464µs; 27.064µs] or [-5.046%; +5.046%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
tags/replace_trace_tags execution_time 2.305µs 2.388µs ± 0.023µs 2.387µs ± 0.004µs 2.396µs 2.422µs 2.451µs 2.456µs 2.87% -0.973 4.116 0.95% 0.002µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
tags/replace_trace_tags execution_time [2.385µs; 2.391µs] or [-0.132%; +0.132%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz f131d99 1773416604 julio/rd-week-dynamic-pipeline
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_trace/test_trace execution_time 245.720ns 254.030ns ± 10.589ns 249.810ns ± 2.887ns 255.708ns 284.288ns 286.101ns 286.875ns 14.84% 1.970 2.838 4.16% 0.749ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_trace/test_trace execution_time [252.562ns; 255.497ns] or [-0.578%; +0.578%] None None None

Baseline

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dd-octo-sts bot commented Mar 3, 2026 •
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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 100.37 MB 100.37 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.70 MB 8.70 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 117.05 MB 117.05 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.22 MB 11.22 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.18 MB 27.18 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 76.61 KB 76.61 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 186.17 MB 186.16 MB -0% (-8.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 917.36 MB 917.36 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.94 MB 9.94 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 76.61 KB 76.61 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 24.78 MB 24.78 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.46 MB 51.46 MB 0% (0 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 22.98 MB 22.98 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 77.80 KB 77.80 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.34 MB 190.31 MB --.01% (-32.00 KB) 💪
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 901.01 MB 901.01 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 7.54 MB 7.54 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 77.80 KB 77.80 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 26.53 MB 26.53 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 47.08 MB 47.08 MB 0% (0 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 87.58 MB 87.58 MB 0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 10.22 MB 10.22 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 109.91 MB 109.91 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.96 MB 11.96 MB 0% (0 B) 👌

@hoolioh
ci: create workspace for actions
089947d 
Create actions workspace to share and build code for repo actions:
* Move code from clippy-annotation-reporter to ci-shared crate.
* Port code from changed-crates bash script to changed-crates binary
  inside ci-crates.
* Create affected-crates binary to compute dependency graph and get
  affected crates by the PR.
* Modify lint workflow to manage affected crates.
@hoolioh hoolioh force-pushed the julio/rd-week-dynamic-pipeline branch from d33ce6c to 089947d Compare March 4, 2026 16:19
@datadog-datadog-prod-us1

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iunanua
iunanua reviewed Mar 5, 2026
View reviewed changes
@hoolioh hoolioh changed the title ci: create workspace for actions ci: dynamic pipeline Mar 5, 2026
@hoolioh hoolioh force-pushed the julio/rd-week-dynamic-pipeline branch from 7e53a10 to 34635e3 Compare March 5, 2026 13:52
hoolioh and others added 17 commits March 5, 2026 15:11
@hoolioh
Fix call to action
c9785c8
@hoolioh
compile action
8fd143e
@hoolioh
Restore workflows.
344aa18
@hoolioh
Modify fuzz to just run the tests if the crates just changed
32182b8
@hoolioh
Modify lint workflow
a20def1
@hoolioh
restore id
76262ad
@iunanua
remove if
b0ec864
@iunanua
triggers and log
847325b
@iunanua
call fetch_base
150a5bf
@iunanua
Change workflow triggers
b0048f8
@hoolioh
Fix base reference name
e784a9b
@hoolioh
split test and make ffi dynamic
97e6af2
@hoolioh
make unit test workflow dynamic
8610e98
@iunanua
chore(ci): setup miri crates before running (#1679)
026698c 
# What does this PR do?

A brief description of the change being made with this pull request.

# Motivation

What inspired you to submit this pull request?

# Additional Notes

Anything else we should know when reviewing?

# How to test the change?

Describe here in detail how the change can be validated.
@hoolioh
Merge branch 'julio/rd-week-unit-test-workflow' into julio/rd-week-dy…
16dfffc 
…namic-pipeline
@hoolioh
fix spellcheck
c8cd45f
@hoolioh
make clippy and rustfmt dynamic
63c0349
hoolioh and others added 5 commits March 7, 2026 08:40
@hoolioh
fix shellcheck
36fe200
@hoolioh
fix: search crates by exact name rather than substring
ada2860
@hoolioh
fix: only run tests on crates containing tracing integration tests
9c957d3
@iunanua
ci: changed-crates refactor (#1691)
cb5bf5f 
# What does this PR do?

Remove the `github.event_name == 'pull_request'` checks 
 
# Motivation

What inspired you to submit this pull request?

# Additional Notes

Anything else we should know when reviewing?

# How to test the change?

Describe here in detail how the change can be validated.
@hoolioh
Merge branch 'main' into julio/rd-week-dynamic-pipeline
2b97a89
@hoolioh hoolioh force-pushed the julio/rd-week-dynamic-pipeline branch from 56bf633 to 91b03cc Compare March 13, 2026 13:08
@hoolioh hoolioh force-pushed the julio/rd-week-dynamic-pipeline branch from 91b03cc to a434e47 Compare March 13, 2026 13:11
@hoolioh hoolioh force-pushed the julio/rd-week-dynamic-pipeline branch from 8265042 to 0e12df0 Compare March 13, 2026 15:02
@hoolioh hoolioh marked this pull request as ready for review March 13, 2026 16:38
@hoolioh hoolioh requested review from a team as code owners March 13, 2026 16:38
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