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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.

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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

Provider-aware connector inventory

Register connectors for Prometheus, Datadog, Azure Monitor, AWS CloudWatch, Grafana, MLflow, Databricks, and custom providers from one workspace.

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.