Amazon Managed Service for Prometheus Cheat Sheet

• A managed monitoring service for container environments.
• You can monitor and alert on the performance of containerized workloads using the open-source PromQL without having to scale or manage the underlying infrastructure.
• Automatically scale the ingestion, storage, alerting, and querying of operational metrics as workload increases.

• Integrated with Amazon EKS, Amazon ECS, and AWS Distro for OpenTelemetry.

Amazon Managed Service for Prometheus Features

• With Prometheus query language (PromQL), you can easily obtain performance visibility using a filter, aggregate, and alarm on metrics.
• Supports multi-AZ replication within an AWS Region.
• Collect and query metrics from container clusters on AWS and on-premises.
• Support for PagerDuty integration for automated incident response workflows.
• Added resource-based policy support with DeleteResourcePolicy, DescribeResourcePolicy, and PutResourcePolicy API actions.
• Support for editing rules definition files and Alert manager configuration files from the console.
• Simpler AWS managed collector setup with Amazon EKS access entries, including updated managed policy for deleting unused access entries.
• Support for customer-managed keys for workspace encryption.
• AWS managed collectors can now be used as an ingestion method.
• Integration with Amazon Managed Grafana alerts.
• Custom storage retention per workspace for metrics.
• Support for Alert Manager and Ruler logs in Amazon CloudWatch Logs.
• Integration into Amazon EKS cost monitoring.
• Added Amazon EKS observability solution using AWS Observability Accelerator.

Amazon Managed Service for Prometheus Concepts

• Workspace
  • A logical space dedicated to storage and querying of metrics.
  • Supports one or more workspaces in each Region.
  • Metrics ingested into a workspace can only be stored for 150 days.
  • Supports multiple rule files.
• Rules
  • To use rules in Prometheus, you’ll need to create YAML rule files.
  • Each rules file is contained under its own namespace.
  • Rules are organized into rules groups within a rules file and are evaluated in order from top to bottom.
• Recording rules
  • You can precompute frequently used or computationally expensive expressions and save the results as a new collection of time series.
  • Querying precomputed result is much faster than running the original expression.
• Alerting rules
  • Create alert conditions based on PromQL and a threshold.
  • A notification is sent to the alert manager when a rule triggers the threshold and forwards it to Amazon SNS.
• Alert manager
  • Supports deduplication, grouping, and routing of alerts to downstream receivers.
  • You can also silence and inhibit alerts.
  • Configuration file
    • Grouping – collects similar alerts into a single notification.
    • Inhibition – suppresses notifications if certain alerts are already firing.
    • Silences – mute alerts for a specified time.
• Templating is stored in the same alert manager configuration file as your alert manager configuration.
• Supports tagging for workspaces and rule groups namespaces.
• Workspaces now support tags and improved management via policies and permissions.
• Alert Manager configuration can be edited in-console, including grouping, inhibition, silences, and templating.
• Rule editing supports multiple rule definition files per workspace.

Amazon Managed Service for Prometheus Pricing

• You are charged based on metrics ingested, queried, and stored.
• Metrics ingested and stored are only charged when you send metrics to Prometheus.
• PromQL Query Samples Processed (QSP) is charged on a per-billion basis.
• Storage fees are calculated depending on the compressed size of metric samples and metadata.
• There are no charges for data transfer in.

References:
https://aws.amazon.com/prometheus/
https://docs.aws.amazon.com/prometheus/latest/userguide/what-is-Amazon-Managed-Service-Prometheus.html