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Performance Tab

The Performance tab of the Workflow Detail page breaks down where time is spent across jobs and individual steps, helping you identify the highest-impact optimization targets.

Job Duration

A horizontal bar chart showing each job's average duration (purple) vs its p95 duration (blue), displayed in minutes. The gap between average and p95 is the “tail latency” — a large gap means some runs of that job are dramatically slower than usual.

Column / SeriesDefinition
AvgMean duration of that job across all loaded runs.
p9595th-percentile duration — 95% of runs of that job finish within this time. A rising p95 is a stronger signal of regression than a rising average.
Gap (avg → p95)Large gaps indicate non-deterministic jobs: slow on some runs, fast on others. Common causes: cache misses, test flakiness, or shared infrastructure contention.

Job Composition per Run

A stacked bar chart showing the last 20 runs on the X-axis and total run duration on the Y-axis. Each bar is segmented by job, colour-coded consistently. This reveals which job dominates total run time and whether that share is growing.

Hover any segment to see the exact job name and its duration for that run. A sudden change in a job's share often corresponds to a code change in that job's steps.

Slowest Steps

A ranked table of the top 10 individual step names by average runtime, aggregated across all jobs and loaded runs. Each row shows: step name, job context, run count, average, p95, max durations, and success %.

ColumnWhat it means
RUNSNumber of runs in which this step executed (denominator for averages).
AVGMean step duration in seconds across all runs.
P9595th-percentile step duration. Use this to size timeouts and SLOs.
MAXWorst observed duration for this step — a ceiling for worst-case pipeline time.
SUCCESS %Percentage of step executions that completed successfully. Low values indicate a flaky step.
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GitDash v4.7.1 — GitHub Actions Dashboard

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