Using Workspace Dashboard

What Dashboard Is For

Dashboard is your workspace-level control panel for execution quality, stability, and trend monitoring.

Use it to answer practical questions quickly:

• Is quality improving or degrading this week?
• Which pipelines fail the most?
• Which pipelines are unstable (flaky)?
• Are executions getting slower?
• What ran most recently and from which trigger source?

Read Dashboard from Top to Bottom

1. Filter Bar

Start here before reading any chart:

• Time range: 7d / 14d / 30d / 90d or custom date range
• Pipeline: narrow to one or more pipelines
• Tags: narrow to tagged pipeline sets
• Trigger Source: filter by Plan, Gatekeeper, Manual Trigger, Single Run

2. KPI Cards

The first row summarizes the selected scope:

• Total Executions: total number of executions in current filters
• Success Rate: overall pass ratio in current filters
• Avg Duration: average execution duration
• Pending / Running: in-flight executions right now

Use KPI cards to detect anomalies first, then drill into detailed charts below.

3. Workspace Overview Panel

The overview panel gives fast context:

• Assets Composition: counts of pipelines, plans, gatekeepers, and test cases
• TEE Utilization: current TEE Utilization level
• Team & Test Activity: workspace member activity and recent test case execution volume

This helps distinguish quality problems from capacity/load problems.

Understand Core Analysis Sections

Which widgets are affected by filters

Dashboard has two data scopes: filtered analytics scope and workspace overview scope.

Success Rate Trend

Use this trend to see whether quality is consistently improving or dropping over time.

• A short dip may be a one-off incident.
• A sustained downward trend usually needs root-cause analysis.

Pipeline Health Matrix

Pipeline Health Matrix helps compare pipeline stability side by side.

• Rows represent pipelines.
• Cells represent recent execution outcomes.
• Click a cell/execution key to jump into execution investigation.

Top Failed Pipelines

Use this block to prioritize where failure impact is highest.

• Start with top-ranked pipelines.
• Correlate with failure trend and recent executions to identify fresh regressions.
• Ranking compares pipelines inside your current filter scope.
• Pipelines with very few executions are excluded to avoid noisy ranking.

Top Flaky Pipelines

Flaky Pipeline means outcomes are inconsistent across runs.

Use this block to find unstable pipelines that may pass sometimes and fail sometimes.

• Flaky ranking is calculated within your current filter scope.
• It focuses on pass/fail state changes across consecutive runs.

Top Slowest Pipelines

Use this block to find pipelines with high execution cost.

• Prioritize long-running pipelines with frequent usage.
• Check whether slow pipelines also overlap with failed/flaky pipelines.

Top Failed Test Cases

This table helps isolate recurrent failing test cases across pipelines.

• Failed = failed count
• Failure Rate = failed/total in current filters

Use Recent Executions for Fast Drill-Down

The Recent Executions table is your shortcut from trend to evidence.

Use it to quickly confirm:

• current status
• source (Plan, Gatekeeper, Manual Trigger, Single Run)
• duration
• trigger time

Then open execution detail for root-cause analysis.

Recommended Troubleshooting Workflow

1. Narrow time range and source in filters.
2. Check KPI cards for anomaly direction (quality, duration, or queue).
3. Use matrix + top lists to locate candidate pipelines.
4. Open recent execution details and verify failing test cases/logs.
5. Confirm fix by refreshing dashboard and comparing trends.

Related Guides

• How to Read Execution List and Execution Detail
• Manage Test Trigger Methods - Plan Trigger
• Manage Test Trigger Methods - Gatekeeper Trigger
• Manage Test Trigger Methods - Manual Trigger