Free Assessment Tool
Is your data ready for AI-driven operations?
Most observability stacks have data gaps that make AI unreliable and most teams don't know where they are. This checklist finds them first, so you can fix them on your terms.
- 22 data coverage checkpoints
- 7 hidden gap categories
- <10 minutes to complete
Complete this assessment and you'll walk away with:
- A scored readiness rating out of 22
A clear, objective baseline of where your data coverage stands today - A list of your blind spots
Specific data gaps, along with the operation risk they create - A roadmap you can act on immediately
Know exactly which data gap to close first to make your AI reliable
Why This Matters
The 7 hidden data gaps that break AI operations
AI is only as smart as the data it sees. These are the coverage areas most teams think they have but don't.
Application Telemetry
Metrics, distributed traces, and logs that reveal true user experience and root cause — not just uptime.
Infrastructure Telemetry
VM metrics, storage I/O, and OS logs that expose resource constraints before they become outages.
Kubernetes & Platform
Pod, node, cluster metrics plus control plane logs that diagnose orchestration blind spots.
Network & Transport
Flow records, latency, TCP retransmissions, and dependency maps that reveal network-layer issues.
Security & Access
Auth logs, firewall events, and IDS/IPS data that provide threat and policy enforcement context.
Cloud & SaaS Telemetry
Provider metrics, SaaS API health, and regional dependency data for third-party visibility.
Business & Service Context
CMDB ownership, app-to-business mapping, and SLA/SLO definitions connecting tech issues to business impact.
Understanding Your Score
What your readiness score means
The checklist scores your organization out of 22. Here's how to interpret where you land.
15–22
Strong Foundation
You have the visibility needed for trusted AI-assisted operations. Continue optimizing correlation and context.
8–14
Risk of Blind Spots
Gaps in your data will limit AI accuracy and slow incident resolution. Prioritize the missing data types.
0–7
High Risk
Too many blind spots. AI-driven operations are not advisable until observability coverage improves.