Simplifying Prometheus metrics collection across your AWS infrastructure (7 minute read)
AWS now offers fully managed Prometheus metric collectors that eliminate the need to run your own Prometheus servers across EC2, ECS, and MSK environments.
What: AWS managed collectors are a feature of Amazon Managed Service for Prometheus that automatically scrape metrics from AWS resources like EC2 instances, ECS containers, and MSK clusters, storing them in a centralized workspace without requiring self-managed Prometheus infrastructure.
Why it matters: Running separate Prometheus servers for each environment creates significant operational burden around high availability, scaling, security group management, and configuration drift, all of which this managed service eliminates while enabling unified cross-service querying and alerting.
Takeaway: If you're currently self-hosting Prometheus on AWS, evaluate migrating to AWS managed collectors by following the step-by-step examples for EC2, ECS, or MSK workloads provided in the AWS documentation.
Deep dive
- AWS managed collectors run as fully managed scrapers deployed in your VPC that collect Prometheus metrics and write them to Amazon Managed Service for Prometheus workspaces without requiring you to operate any Prometheus servers
- Configuration uses familiar Prometheus syntax with base64-encoded YAML files defining scrape intervals, target endpoints, and relabeling rules, then deployed via AWS CLI commands
- EC2 monitoring uses static target configurations pointing to Node Exporter (port 9100) for system metrics and application endpoints (like port 8080) with custom relabeling for consistent tagging across environments
- ECS workloads benefit from DNS-based service discovery using AWS Cloud Map, which automatically tracks ephemeral task IP addresses as containers are replaced or scaled, querying DNS every 30 seconds for updates
- Amazon MSK clusters expose two Prometheus exporters when OpenMonitoring is enabled: JMX Exporter on port 11001 for Kafka-specific metrics (topics, partitions, consumer lag) and Node Exporter on port 11002 for broker system metrics
- The scraper configuration for MSK uses cluster-level DNS names that resolve to all broker IPs, making monitoring resilient to broker replacements and cluster scaling events
- Unified querying across all three platforms becomes possible through a single Amazon Managed Service for Prometheus workspace, enabling PromQL queries that aggregate metrics from EC2, ECS, and MSK simultaneously
- Cross-service alerting can correlate metrics across platforms, such as triggering when Kafka consumer lag exceeds thresholds AND the consuming service's error rate increases, helping identify root causes faster
- Security follows the shared responsibility model where AWS manages scraper infrastructure while you configure IAM least-privilege policies, security group ingress rules limited to scraper groups, private subnet deployment, and VPC endpoints
- AWS automatically creates a service-linked role (AWSServiceRoleForAmazonPrometheusScraperInternal) when creating scrapers, granting necessary VPC access and workspace write permissions
- Production best practices include migrating EC2 workloads to DNS-based service discovery via Cloud Map, deploying multiple scrapers for different lifecycles or security zones, and tuning scrape intervals (30s for apps, 60s for infrastructure, 90s+ for non-prod)
- Cost optimization comes from dropping noisy debug metrics using metric_relabel_configs with regex patterns, since halving scrape intervals doubles ingestion costs
- All data is encrypted in transit via TLS to the workspace and at rest by default, with optional customer-managed keys available for additional control
Decoder
- Prometheus: Open-source monitoring system that collects time-series metrics from applications and infrastructure by scraping HTTP endpoints
- Scraper: A component that periodically pulls (scrapes) metrics from target endpoints, in this context running as a managed AWS service rather than self-hosted
- Node Exporter: Prometheus exporter that exposes hardware and OS-level metrics like CPU, memory, and disk usage from Linux systems
- JMX Exporter: Java Management Extensions exporter that exposes JVM and application-specific metrics, used here for Kafka broker internals
- AWS Cloud Map: Service discovery system that maintains DNS records for dynamically changing resources like ECS tasks
- PromQL: Prometheus Query Language used to select and aggregate time-series metric data
- Amazon MSK: Amazon Managed Streaming for Apache Kafka, AWS's managed Kafka service
- Service discovery: Automated mechanism for finding and tracking network endpoints as they change, crucial for ephemeral containerized workloads
- Relabeling: Prometheus feature for adding, modifying, or dropping metric labels during or after collection to normalize data across sources
Original article
AWS managed collectors for Amazon Managed Service for Prometheus replace multiple self-managed Prometheus servers by centrally scraping metrics from EC2, ECS, and MSK via VPC, reducing operational overhead while enabling unified monitoring, scaling, and security. Configuration uses exporters, DNS-based service discovery, and IAM-secured scrapers to collect and query metrics across environments, supporting resilient observability, cross-service alerting, and cost-optimized monitoring with best practice controls.