Data Warehouse & Analytics
Foglight for Amazon EMR
Big-data clusters, jobs, and nodes under one roof
Description
Amazon EMR is a managed big-data platform that simplifies running Apache Spark, Hadoop, Hive, Presto, and other frameworks on EC2 clusters. Teams rely on EMR for large-scale ETL, log processing, and machine-learning feature pipelines that would be costly to operate by hand.
Foglight for Amazon EMR brings EMR cluster and node telemetry into Foglight so platform teams can watch cluster lifecycle, resource utilization, and job outcomes from the same monitoring estate as their databases and warehouses.
Business Challenge
EMR clusters are ephemeral and heterogeneous - nodes join and leave, jobs succeed and fail, and YARN queues can back up without a single pane that ties cluster state to downstream SLA risk. CloudWatch metrics exist, but correlating them with cluster inventory and job history takes custom tooling most teams never build.
Foglight for Amazon EMR assembles CloudWatch series and EMR management API facts into a cluster-centric view with proactive alerting on failed steps, unhealthy nodes, and resource pressure.
Key Features
Foglight for Amazon EMR monitors cluster state, core/task node health, HDFS and YARN utilization, and step/job outcomes via CloudWatch and the EMR management API. As with all Foglight solutions, it runs on the Foglight Agent Manager (FglAM) independent of the monitored clusters and uses the Foglight Rules Engine to alert on conditions that threaten batch windows and data pipeline reliability.
Ready to see Amazon EMR in action?
Request a free trial or talk to our engineers about your environment.