Key Metrics and KPIs to Track in the AAP 2.6 Automation Dashboard
By Luca Berton · Published 2024-01-01 · Category: troubleshooting
Which metrics and KPIs to monitor in the AAP 2.6 automation dashboard to demonstrate value, optimize resources, and drive automation adoption.

Introduction
The automation dashboard in AAP 2.6 can track numerous metrics, but which ones actually matter? This guide helps you identify the key performance indicators (KPIs) that demonstrate automation value and drive informed decisions.
See also: How to Use the AAP 2.6 Automation Dashboard to Measure ROI
Essential KPIs
1. Job Success Rate
The most fundamental metric — what percentage of automation jobs succeed?
Success Rate = (Successful Jobs / Total Jobs) × 100
Target: > 95% for production automation
Warning: < 90% indicates systemic issues
Why it matters: Low success rates indicate unreliable automation that may be worse than manual processes. Track this over time to show improvement.
2. Time Savings
Quantify the time your automation saves:
Time Saved = (Manual Duration - Automated Duration) × Executions
Example:
Manual server provisioning: 4 hours
Automated provisioning: 15 minutes
Monthly executions: 50
Monthly time saved: 50 × 3.75 hours = 187.5 hours
3. Automation Coverage
What percentage of repeatable tasks are automated?
Coverage = (Automated Tasks / Total Repeatable Tasks) × 100
Track growth over quarters to show progress
4. Mean Time to Resolution (MTTR)
For event-driven automation, how quickly are incidents resolved?
MTTR = Total Resolution Time / Number of Incidents
Compare before and after EDA implementation
5. Node Utilization
Are you using your automation resources efficiently?
Utilization = (Active Node Hours / Total Available Node Hours) × 100
Target: 40-70% (leaves headroom for spikes)
Warning: > 90% indicates capacity planning needed
Warning: < 20% indicates over-provisioning
Business-Oriented Metrics
Cost Avoidance
Calculate the cost of manual processes you've eliminated:
Cost Avoidance = Time Saved × Average Hourly Rate × Benefit Multiplier
Example: 187.5 hours × $75/hr × 1.3 = $18,281/month
Error Reduction
Track manual errors before and after automation:
Error Rate Improvement = 1 - (Post-Automation Errors / Pre-Automation Errors)
Deployment Frequency
How often can you deploy with confidence?
Track: Deployments per week/month
Goal: Increase frequency while maintaining success rate
Dashboard Report Templates
Executive Summary (Monthly)
• Total automation runs • Success rate trend • Time saved this month • Top 5 most-used automations • Cost avoidance estimateTechnical Deep-Dive (Weekly)
• Job failure analysis • Execution time trends • Node utilization • EDA event processing rates • Collection usage statisticsCapacity Planning (Quarterly)
• Node utilization trends • Growth projections • License usage vs entitlement • Resource optimization recommendationsBest Practices
Set baselines before claiming improvements Automate report generation — Schedule regular exports Compare periods — Show week-over-week and month-over-month trends Segment by team — Different teams have different KPIs Celebrate wins — Share positive metrics to drive adoptionSee also: What's New in Ansible Automation Platform 2.6 — Complete Overview
Conclusion
The right metrics tell a compelling story about your automation program's value. Use the AAP 2.6 dashboard to track these KPIs consistently and share them with stakeholders to drive continued investment in automation.
For more Ansible tutorials and guides, explore the complete article collection on Ansible Pilot.
Related Articles
• Ansible template guideCategory: troubleshooting