How to Audit Your PI System: A Technical Checklist for PI Admins

Auditing your PI System isn't optional - it's essential. Over time, stale tags, misconfigured compression, abandoned displays, and underperforming calculations silently erode the reliability of your historian. Left unchecked, these issues can slow down PI and AF, drive up costs, and reduce trust in the data your business depends on.

In this post, we'll walk through a PI System Audit Checklist every admin should know. Then, we'll show how tools like Osprey make the process faster, continuous, and less error-prone.

PI System Audit Checklist

1. Audit Interface Health

• Verify all interfaces and connectors are up and reporting.
• Identify "zombie" interfaces that haven't been active but still consume configuration and resources.
• Monitor for latency and data gaps - a single misconfigured interface can cause downstream blind spots.

2. Identify Dead or Abandoned Tags

• Flatlined or stale tags: Sensors that haven't updated in days, weeks, or months.
• Unused tags: Points created but never referenced in AF or displays.
• Ghost tags: Tags that no longer map to live assets but still occupy license slots.
• Business impact: Each unused tag consumes resources and licensing - removing them reduces load and cost.

3. Check Compression and Exception Settings

• Review tags with overly aggressive compression → critical data may be silently dropped.
• Review tags with minimal compression → unnecessary load on PI Data Archive, leading to slowdowns.
• Look for AF calculation bottlenecks caused by excessive inputs or poor configuration.

4. Audit Asset Framework (AF)

• Confirm templates and elements align with naming conventions and governance standards.
• Detect broken or circular calculations that increase CPU load.
• Identify attributes connected to stale or missing tags.
• Trace dependencies: which AF analyses depend on mission-critical tags?

5. Audit AF Calculation Health

• Broken calculations: Identify AF analyses that are failing, erroring out, or producing invalid results.
• Performance bottlenecks: Find calculations consuming excessive CPU or memory resources.
• Orphaned calculations: Analyses that reference deleted or moved tags but continue running.
• Circular dependencies: Calculations that reference each other, creating infinite loops.
• Business impact: Broken calculations can cascade failures and mislead operators with incorrect KPIs.

6. Audit Archive and Disk Space

• Archive growth trends: Monitor historical growth rates and project future storage needs.
• Disk space utilization: Check available space on PI Data Archive servers and backup locations.
• Archive fragmentation: Identify archives that need defragmentation for optimal performance.
• Backup validation: Ensure backups are completing successfully and can be restored.
• Archive shifting: Review archive boundaries and shifting policies for optimal performance.

7. Audit Calculation Documentation

• Missing documentation: Identify AF analyses without proper descriptions or comments.
• Business logic clarity: Ensure calculations include clear explanations of what they compute and why.
• Input/output documentation: Document expected inputs, outputs, and units for each calculation.
• Knowledge transfer readiness: Assess if junior engineers can understand and maintain existing calculations.
• Change history: Track who modified calculations and when, with reasoning for changes.

8. Audit PI Vision Displays

• Detect displays containing bad, missing, or dead tags.
• Flag dashboards that reference ghost or deprecated assets.
• Understand which operators or engineers are relying on data that may be untrustworthy.

9. Audit Security & Access

• Review PI System security mappings to ensure the right users have access.
• Identify orphaned users and permissions no longer needed.
• Confirm compliance with IT/OT security policies.

10. Trace Tag Usage Across the System

For any given tag, identify:

• Which assets reference it.
• Which AF calculations depend on it.
• Which displays surface it.
• Which users access it.

This dependency mapping is critical to prevent hidden ripple effects when retiring or reconfiguring a tag.

Why Manual Audits Aren't Enough

Running through this checklist manually takes days or weeks. Even then, it's easy to miss hidden issues: a calculation buried in AF, a tag referenced in dozens of dashboards, or a compression setting that's slowly eroding resolution on critical equipment.

That's why forward-looking PI Admins are adopting automated, continuous auditing with tools built for data quality, governance, and reliability.

Automate Your PI System Audit with Osprey

With Osprey, you don't just run a one-time audit - you get ongoing visibility across your entire PI System:

• Interface health monitoring → catch data gaps and latency before they spread.
• Dead tag detection → automatically surface stale, flatlined, or unused points.
• Compression insights → flag tags where settings are too aggressive or too loose.
• AF + PI Vision scanning → map every asset, analysis, and display that depends on a tag.
• Governance & lineage tracking → understand how data flows across archives, AF, and displays.
• Calculation health monitoring → detect broken, failing, or poorly performing AF analyses.
• Storage monitoring → track archive growth and disk space utilization trends.
• Documentation assessment → identify undocumented or poorly documented calculations.

Instead of firefighting problems when users complain about missing or unreliable data, you'll have a trust layer that continuously audits your PI System in the background.

Conclusion

Auditing your PI System is about more than compliance - it's about keeping your historian reliable, your calculations performant, and your operators confident in the data they use to run the business.

Following the checklist above is a strong start. But if you want a faster, more complete way to audit your PI System, explore how Osprey can help.

Don't wait for bad data to cause downtime. Start auditing your PI System today.