Workflow Overview Tab

The Overview tab of the Workflow Detail page shows four charts that give a quick health pulse for a specific GitHub Actions workflow, plus an Optimization Tips banner.

Overview Charts

Chart	What it shows	How to read it
Rolling Success Rate	Moving average of CI pass rate over every 7 consecutive runs.	A dip below the red 80% reference line that persists across multiple windows indicates a systemic problem, not just a fluke failure.
Action Duration Trend	Two independent (non-stacked) area series: purple = execution time only (run_started → completed), amber = queue wait only (triggered → run_started). Total elapsed = purple + amber.	Rising purple = workflow getting slower (test suite growth, cache misses). Rising amber = runner capacity bottleneck. The two series share the Y-axis but are NOT added together.
Outcome Breakdown	Donut chart of run conclusions over the last 60 runs: success, failure, cancelled, skipped, timed_out.	A large failure or timed_out slice needs immediate attention. Cancelled runs often indicate force-pushes interrupting in-flight runs.
Run Frequency	Bar chart of runs triggered per calendar day over the last 14 days.	Gaps are expected on holidays. Unusual spikes may indicate retry storms, misconfigured cron schedules, or a flood of PRs.

Optimization Tips

GitDash automatically analyses workflow patterns and surfaces actionable suggestions in a dismissible banner at the top of the Overview tab. Tips are generated from the last 60 runs.

Tip type	Trigger condition	Suggested action
Weekend runs	>50% of runs triggered on Sat/Sun	Move scheduled/cron workflows to weekday-only schedules to save CI minutes.
High cancel rate	>20% of runs cancelled	Consider using concurrency groups to cancel superseded runs instead of letting them start.
Long queue wait	Queue wait P95 > 5 minutes	Add more runners or switch to larger GitHub-hosted runner tiers.
High re-run rate	>10% of runs re-triggered manually	Investigate flaky tests or infrastructure instability.
Duration regression	P95 duration grown >25% in last 14 days vs prior 14 days	Profile slow jobs — look for cache misses, dependency bloat, or uncapped test parallelism.

Workflow Overview Tab

The Overview tab of the Workflow Detail page shows four charts that give a quick health pulse for a specific GitHub Actions workflow, plus an Optimization Tips banner.

Overview Charts

Chart	What it shows	How to read it
Rolling Success Rate	Moving average of CI pass rate over every 7 consecutive runs.	A dip below the red 80% reference line that persists across multiple windows indicates a systemic problem, not just a fluke failure.
Action Duration Trend	Two independent (non-stacked) area series: purple = execution time only (run_started → completed), amber = queue wait only (triggered → run_started). Total elapsed = purple + amber.	Rising purple = workflow getting slower (test suite growth, cache misses). Rising amber = runner capacity bottleneck. The two series share the Y-axis but are NOT added together.
Outcome Breakdown	Donut chart of run conclusions over the last 60 runs: success, failure, cancelled, skipped, timed_out.	A large failure or timed_out slice needs immediate attention. Cancelled runs often indicate force-pushes interrupting in-flight runs.
Run Frequency	Bar chart of runs triggered per calendar day over the last 14 days.	Gaps are expected on holidays. Unusual spikes may indicate retry storms, misconfigured cron schedules, or a flood of PRs.

Optimization Tips

GitDash automatically analyses workflow patterns and surfaces actionable suggestions in a dismissible banner at the top of the Overview tab. Tips are generated from the last 60 runs.

Tip type	Trigger condition	Suggested action
Weekend runs	>50% of runs triggered on Sat/Sun	Move scheduled/cron workflows to weekday-only schedules to save CI minutes.
High cancel rate	>20% of runs cancelled	Consider using concurrency groups to cancel superseded runs instead of letting them start.
Long queue wait	Queue wait P95 > 5 minutes	Add more runners or switch to larger GitHub-hosted runner tiers.
High re-run rate	>10% of runs re-triggered manually	Investigate flaky tests or infrastructure instability.
Duration regression	P95 duration grown >25% in last 14 days vs prior 14 days	Profile slow jobs — look for cache misses, dependency bloat, or uncapped test parallelism.