Amazon Managed Grafana is a fully managed service for the open-source Grafana visualization platform. It provides enterprise-ready Grafana workspaces with built-in authentication (AWS IAM Identity Center, SAML), automatic scaling, and native integration with AWS data sources. For AI projects, Managed Grafana serves as the operational dashboard layer for monitoring model performance, data pipeline health, and infrastructure metrics.

Official documentation: https://docs.aws.amazon.com/grafana/ Pricing: https://aws.amazon.com/grafana/pricing/ Service quotas: https://docs.aws.amazon.com/grafana/latest/userguide/AMG-limits.html

Core Concepts

Workspace - An isolated Grafana instance with its own URL, user management, and configuration. Each workspace runs the latest compatible Grafana version and scales automatically based on usage. Workspaces support Grafana plugins, alerting, and all standard Grafana features.

Data Sources - Connections to backend data stores. Managed Grafana has native support for CloudWatch, Timestream, OpenSearch, Prometheus, X-Ray, and many third-party sources. Data source credentials are managed through IAM roles, eliminating the need to store database passwords in Grafana configuration.

Dashboards - Collections of panels (charts, tables, gauges, maps) that visualize data from one or more data sources. Dashboards support variables, templating, and time range controls for interactive exploration.

Authentication and Access Control

Managed Grafana integrates with AWS IAM Identity Center (formerly SSO) or any SAML 2.0 identity provider. Users are assigned roles: Viewer (read-only dashboard access), Editor (create and modify dashboards), or Admin (workspace configuration). This maps well to enterprise teams where data scientists need Editor access and business stakeholders need Viewer access.

Service-managed permissions allow the workspace to automatically discover and connect to AWS data sources in your account without manual credential configuration.

AI/ML Monitoring Dashboards

The primary value of Managed Grafana for AI projects is operational monitoring. Common dashboard patterns include:

Model performance tracking - Visualize prediction accuracy, latency percentiles, and throughput over time. Connect to CloudWatch metrics emitted by SageMaker endpoints or custom metrics from your inference pipeline. Set alerts when accuracy drops below a threshold or latency exceeds SLA targets.

Data pipeline health - Monitor Glue job success rates, Step Functions execution status, and data freshness. A single dashboard showing pipeline status across all stages (extraction, transformation, model training, deployment) provides situational awareness that prevents issues from cascading.

Cost monitoring - Track AWS spend across AI services using CloudWatch billing metrics. Visualize SageMaker training costs, Bedrock API call volumes, and infrastructure costs on a single dashboard. This visibility is critical for projects where inference costs can grow unpredictably.

Drift detection - Plot feature distributions and prediction distributions over time. Statistical shifts become visible as distribution charts change shape, enabling early detection of model drift before performance degradation becomes significant.

Alerting

Managed Grafana supports Grafana Alerting with notification channels including SNS, Slack, PagerDuty, and email. Alerts can be configured with multiple conditions, evaluation intervals, and notification policies that route alerts to different channels based on severity.

For AI operations, configure alerts for: model endpoint errors exceeding a threshold, training job failures, data pipeline delays beyond acceptable windows, and cost anomalies.

Prometheus Integration

For teams running containerized ML workloads on EKS, Managed Grafana pairs with Amazon Managed Prometheus for a complete monitoring stack. Prometheus scrapes metrics from ML containers (GPU utilization, batch processing rates, queue depths), and Grafana visualizes them. This combination provides Kubernetes-native monitoring without managing Prometheus or Grafana infrastructure.

Pricing

Managed Grafana charges per active user per month, with pricing varying by license tier (Editor or Viewer). There is no charge for the workspace itself or for data source queries. This per-user pricing model means costs scale with team size rather than data volume, making it predictable for budgeting.