Stories tagged telemetry

Agentforce Health Monitoring addresses the gap where traditional dashboards show healthy status while users actually receive no end-to-end response. The system tracks over sixteen built-in metrics including error rates, escalation rates, engagement, and latency, with plans to add cost, time-to-first-token, and RAG quality signals. Its primary goal is proactive visibility that connects alerts directly to the relevant session context.

The engineering team solved a major fragmentation problem by consolidating signals scattered across five or six separate systems. By converting data ingestion to streaming and simplifying query complexity, they accelerated metric evaluation. This optimization reduced the time from a threshold breach to administrator notification from approximately twenty minutes to several minutes, targeting an investigation start time under two minutes.

Operational workflows now emphasize actionable debugging rather than simple detection. Administrators can drill down from an alert to examine specific reasoning steps, tool calls, or flow configurations that caused a failure, and they can define custom thresholds like token usage limits. Looking ahead, the roadmap includes runtime insight agents to suggest fixes and fully automated remediation pipelines that apply approved solutions without manual intervention.

Salesforce Engineering addressed the challenge of monitoring enterprise org health at scale by moving beyond static reports to an in-app experience called Salesforce Health Insights. The team needed to correlate point-in-time configuration metadata with continuously changing runtime telemetry across systems that lack shared identity models.

To solve this, they built a harmonization layer that reconciles fragmented datasets and maps runtime activity to individual metadata components while accounting for traffic volume and seasonality. This architecture maintains clear boundaries between deterministic findings and external operational context, preserving data origin and freshness information.

The initiative expanded from roughly one hundred initial security signals to over four hundred covering process automation, customization, and agentic readiness. Each signal follows standardized metadata rules and remediation guidance derived from the Salesforce Well-Architected Framework and known system hotspots.

Findings are prioritized using operational context such as application CPU usage and peak business hour traffic to determine criticality and required effort. The system uses a headless schema that emits raw JSON for any user interface or agent, supports an MCP interface, and can deliver summaries directly to Slack channels.