# How Standardizing Product Telemetry Reduced Time to Insight by 97%

[Salesforce](https://yomu.fyi/company/salesforce) · Scott Nyberg · Aug 11, 2026

**Type:** Problem & solution

## Summary

Salesforce faced scaling bottlenecks when individual engineering teams maintained fragmented, custom telemetry pipelines requiring manual data transformations and dashboard creation every release. To resolve these silos, the engineering organization established the Product Data Platform (PDP) using a standardized custom schema built atop Monitoring Cloud infrastructure. This framework mandates core telemetry fields for consistent metric generation while offering governed optional attributes for product-specific flexibility. An AI-driven Model Context Protocol tool assists developers by recommending compliant instrumentation patterns directly within their workflows. Today, the unified platform processes 45 billion rows of data daily across 19,000 distinct events and 2,000 product features, reducing dashboard refresh latency by 97 percent from one month to daily updates.

## Context

Individual Salesforce product teams historically built customized, fragmented telemetry pipelines that required engineers to manually transform events into adoption dashboards every release. This duplicate effort created data silos, lacked a centralized adoption view across products like Agentforce and Data 360, and forced teams to wait roughly a month for metrics.

## Approach / What changed

Salesforce created the Product Data Platform (PDP), introducing a standardized telemetry framework and schema on Monitoring Cloud infrastructure featuring both mandatory fields and governed optional attributes. Automated pipelines process raw event streams into uniform adoption metrics. Additionally, the team introduced an AI-driven Model Context Protocol (MCP) tool to automatically recommend compliant instrumentation configurations to engineers.

## Takeaways

- The Product Data Platform replaced custom, per-team pipelines by standardizing core telemetry schemas on Monitoring Cloud while supporting governed optional attributes for flexibility.
- Automating metric pipelines reduced time to insight by 97%, moving dashboard refresh cycles from approximately one month down to a single day.
- Standardized telemetry now processes 45 billion rows across 19,000 events and 2,000 product features daily, powering downstream Model Context Protocol plugins for AI queries.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Data Pipelines](https://yomu.fyi/topic/data-pipelines), [Developer Experience](https://yomu.fyi/topic/developer-experience), [Observability](https://yomu.fyi/topic/observability), [Scalability](https://yomu.fyi/topic/scalability)

[Read original post](https://engineering.salesforce.com/how-standardizing-product-telemetry-reduced-time-to-insight-by-97)