Managed Prometheus
Definition
Fully managed Prometheus-compatible metrics collection and alerting that stores and queries infrastructure metrics without running Prometheus yourself.
Use Cases
- AWS: Operate a scalable, highly available Prometheus-compatible metrics backend for container and infrastructure monitoring. — AWS provides Amazon Managed Service for Prometheus as a managed, PromQL-compatible metrics store that integrates with Amazon EKS and the AWS Distro for OpenTelemetry (ADOT) Collector for remote_write ingestion, and commonly pairs with Amazon Managed Grafana for dashboards. (Teams can centralize metrics across many clusters/accounts and reduce operational work for scaling, storage management, and high availability compared with self-managed Prometheus.)
- Google Cloud: Kubernetes and application monitoring using Prometheus metrics at scale without running Prometheus long-term storage. — Google Cloud Managed Service for Prometheus ingests Prometheus-format metrics (including from GKE) and stores them in Cloud Monitoring’s managed backend, enabling PromQL querying and integration with Cloud Monitoring alerting and dashboards. (Improved reliability and scalability for metrics retention and querying, with less time spent maintaining Prometheus storage and HA configurations.)
- Microsoft Azure: Standardize Prometheus metrics collection for AKS clusters and integrate with Azure-native alerting and visualization. — Azure Monitor managed service for Prometheus collects Prometheus metrics (commonly from AKS) and stores them in Azure Monitor, enabling PromQL-based querying and integration with Azure Monitor alerts and workbooks/dashboards. (Faster onboarding for cluster monitoring and reduced operational overhead versus running and scaling Prometheus and long-term storage internally.)
Provider Equivalents
- AWS: Amazon Managed Service for Prometheus (AMP)
- Azure: Azure Monitor managed service for Prometheus
- GCP: Google Cloud Managed Service for Prometheus
- OCI: OCI Observability & Management Platform (Monitoring) with Prometheus-format metrics ingestion (no dedicated 'Managed Prometheus' service name)
Frequently Asked Questions
- What's the difference between Managed Prometheus and self-managed Prometheus?
- Self-managed Prometheus means you run and maintain the Prometheus servers yourself (scaling, upgrades, storage, backups, and high availability). Managed Prometheus provides a Prometheus-compatible service where the cloud provider operates the storage and query layer for you. You typically still run lightweight collectors/agents (like Prometheus scrapers or OpenTelemetry collectors) to send metrics to the managed backend.
- When should I use Managed Prometheus?
- Use Managed Prometheus when you need Prometheus/PromQL compatibility but don’t want to manage long-term storage, scaling, or HA Prometheus clusters—especially for many Kubernetes clusters, multiple environments, or high-cardinality metrics. It’s also a good fit when you want tighter integration with cloud-native IAM, managed dashboards, and managed alerting.
- How much does Managed Prometheus cost?
- Pricing is usually based on metrics ingested (samples/time series), data stored/retained, and queries or API usage, plus any costs for agents/collectors and network egress. Costs rise with high-cardinality labels, long retention periods, and heavy query/alert workloads. Check your provider’s pricing page and estimate using expected ingestion rate, retention, and query volume.
Category: monitoring
Difficulty: advanced
Related Terms
See Also