Docs · Telemetry connectors
Telemetry connector workflows
See how SentinelAI manages telemetry providers, ingest schedules, health status, and manual pulls for governed monitoring workflows.
Overview
Telemetry connectors make live monitoring feeds visible as part of the governance operating model. They give teams a dedicated control plane for provider setup, ingest cadence, health status, and manual signal pulls before those signals flow into cases, evidence, or broader monitoring reviews.
This page is part of the public SentinelAI documentation layer. It is meant to accelerate orientation and evaluation while staying aligned with the product’s governance-focused positioning and messaging guardrails.
Provider onboarding
Connector workflows help teams configure providers such as Prometheus, Datadog, Azure Monitor, AWS CloudWatch, Grafana, MLflow, Databricks, or custom sources from a shared tenant-aware workspace.
Cadence and health
Monitoring workflows are easier to trust when teams can see connector status, ingest schedules, and error posture instead of assuming signals are arriving correctly in the background.
Routing live signals into governance
Connector workflows matter most when current telemetry needs to support investigation, evidence refresh, or post-release oversight. The goal is to make that live context reviewable without presenting SentinelAI as a replacement for the underlying observability stack.