source-performance-observatory

Data source performance monitoring tracks key indicators and explicitly surfaces degradation and staleness for operator action. It implements minimum viable contracts to validate data feeds against performance benchmarks before full system integration.

A QA gate workflow manages a structured quality assurance and release gate process for data sources. It ensures new data feeds meet organizational compliance requirements and performance benchmarks before approval and full integration.

Implementing minimum viable contracts starts with database, API, and UI components in sequence. This approach adheres to SDD governance and org-safe contracts while favoring read-time aggregation before introducing new persistence layers.

Reversible rollouts are supported during source performance monitoring by implementing minimum viable contracts. This ensures data governance changes can be safely reversed while tracking degradation and staleness explicitly for operator action.

Read-time aggregation is needed before introducing new persistence layers for source performance observability. This approach minimizes infrastructure overhead while still tracking key performance indicators and surfacing data staleness for operators.

Source performance monitoring reuses shared cloud checks for v1.2 compatibility. It surfaces degradation and staleness explicitly while adhering to SDD governance and org-safe contracts within the observatory framework.