Provider-aware connector inventory
Register connectors for Prometheus, Datadog, Azure Monitor, AWS CloudWatch, Grafana, MLflow, Databricks, and custom providers from one workspace.
Feature · Telemetry connectors
Make telemetry connectors a governed control plane, not hidden integration glue
SentinelAI gives operators a first-class telemetry connector workspace for provider onboarding, ingest scheduling, health management, and manual trigger control so live assurance signals enter governance in a deliberate way.
What this area covers
Telemetry connectors are the operational layer behind live monitoring workflows. Instead of treating provider setup as background configuration, SentinelAI exposes connector inventory, status, cadence, and verification controls so governance teams can understand how signals arrive and whether those paths are healthy.
Related product areas
- LLM telemetry and monitoring
Bring live assurance signals, telemetry connector management, trigger rules, and evidence-ready monitoring context into AI governance workflows.
- Governance cases
Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.
- Evaluation suites
Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.
- Release governance
Manage AI-system release records with approval state, rollback references, dependency snapshots, and invalidation handling.
- AI governance intelligence
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
- Reports and certificates
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
Core capabilities
Built to support production governance work
Health and status visibility
Track whether each connector is pending verification, active, paused, or erroring so teams can spot ingest issues before oversight depends on stale data.
Ingest cadence control
Configure schedules and enable or disable ingestion explicitly instead of burying that behavior in background jobs with no governance-facing visibility.
Manual trigger support
Pull telemetry on demand when a review, incident, or case needs current operational context right away.
Connector-level configuration governance
Preserve base URLs, extra configuration, and operational metadata in a dedicated control plane rather than scattering integration details across teams.
Target users
- Platform and governance operators responsible for keeping monitoring feeds healthy
- Compliance and risk teams that need confidence in how live signals enter review workflows
- ML and observability teams connecting existing monitoring systems to governance processes
- Assurance stakeholders investigating whether missing telemetry reflects real stability or connector failure
Governance value
- Elevates telemetry onboarding and health into a reviewable part of the governance operating model
- Makes it easier to distinguish signal issues from connector issues during investigations
- Supports reliable evidence refresh by exposing schedules, manual pulls, and connector posture
- Keeps monitoring integrations aligned to the same tenant-aware workflow as the signals they feed
- Strengthens ongoing oversight without claiming SentinelAI replaces the underlying observability stack
How teams use it
A practical operating flow for this feature family
Step 1
Register and verify providers
Create the connector, define provider settings, and move it from pending verification into active use when the integration is ready.
Step 2
Control cadence and monitor health
Set schedules, pause or resume ingest, and review connector status so live signal delivery stays understandable and intentional.
Step 3
Trigger ingest when governance needs it
Run manual pulls and route healthy connector output into monitoring, case, and evidence workflows whenever reviewers need fresh context.
Continue exploring
Explore how SentinelAI connects adjacent governance workflows
LLM telemetry and monitoring
Bring live assurance signals, telemetry connector management, trigger rules, and evidence-ready monitoring context into AI governance workflows.
Governance cases
Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.
Evaluation suites
Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.
Release governance
Manage AI-system release records with approval state, rollback references, dependency snapshots, and invalidation handling.
AI governance intelligence
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
Reports and certificates
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.