AWS Elastic MapReduce (EMR)
Benefits and Use Cases
• Integrate cloud-based EMR processing with on-premises and multi-cloud systems for unified orchestration.
• Trigger Amazon EMR jobs to run Spark, Hadoop, or Presto based processing as part of scheduled workflows.
• Monitor EMR job progress and completion status in real time through Automic.
• Cancel or restart EMR steps and clusters directly from Automic in response to job dependencies or failures.
Example Use Case: Scheduled Data Transformation Pipeline
Schedule recurring batch processing jobs that transform large datasets for analytics and reporting. Seamlessly ingest raw S3 data into clean datasets, maximize resource efficiency through programmatic job termination, and automatically trigger downstream reporting based on real-time execution status.
Automic Features
✓ Add steps to a cluster
✓ Schedule Notebook process
✓ Monitor Notebook jobs to completion
✓ View execution log for problem diagnosis
✓ Alert on failure of Amazon EMR jobs
✓ Incorporate Amazon EMR jobs into enterprise automation workflows including dependency enforcement