How Metadata and Runtime Telemetry Reveal Which Enterprise System Problems to Fix First

Summary

Salesforce Health Insights addresses enterprise org health monitoring by combining configuration metadata with runtime telemetry to identify and prioritize remediation. The team evolved a static report into an in-app experience with durable finding dispositions, approximately 400+ signals across domains, and standards informed by Well-Architected principles and implementation anti-patterns. A shared harmonization layer reconciles fragmented datasets, connector patterns link runtime activity to metadata components, and the system preserves data origin, freshness, and access requirements while keeping deterministic findings distinct from externally supplied context. Prioritization combines findings with request volume, application and database CPU, call behavior, and peak-business-hour traffic to rank next best actions by criticality and effort. A headless JSON schema supports interfaces including an MCP connection, while the deterministic core is intended to produce dependable recommendations and extend access beyond the primary interface.

Takeaways

1. 1

   A shared harmonization layer connects fragmented metadata and runtime telemetry while preserving each dataset’s origin, freshness, and access requirements.

2. 2

   Prioritization uses request volume, application CPU, database CPU, call behavior, and peak-business-hour traffic alongside metadata findings.

3. 3

   The headless architecture emits raw JSON for UIs and agents, and an MCP interface can provide guidance on security, implementation patterns, and anti-patterns.