Managing Costs for Spark on Amazon EMR
Are you looking to optimize costs and resource usage for your Spark jobs on Amazon EMR? Then this is the webinar for you. Overallocating resources, such as memory, is a common fault when setting up Spark jobs. And for Spark jobs running on EMR, adding resources is a click away - but it’s an expensive click, so cost management is critical.
Unravel Data is our AI-enabled observability platform for Spark jobs on Amazon EMR and other Big Data technologies. Unravel helps you right-size memory allocations, choose the right number of workers, and map your cluster needs to available instance types.
Unravel’s troubleshooting capabilities mean you can fix problems the right way. You may never have to over allocate memory and other resources again!Join Mike Wong, Solutions Engineer at Unravel Data, as he offers tricks and tips to help you get the most from your EMR environment, while taking advantage of auto-scaling, different instance types, while reducing cost.
- How Unravel cuts costs by an average of 30-40%.
- How Unravel cuts time to solve problems (MTTR) by an average of 50%.
- How to auto-tune and fix jobs to speed them up, eliminate errors, and meet SLAs.
- How to screen jobs with Unravel before they go into production, ensuring a smooth launch and happy users.
- How Unravel’s AI-powered recommendations, AutoActions, and TopX reports save you time, money, and stress.
Learn More About Unravel DataWebsite: https://www.unraveldata.com/
Try Unravel for free: https://www.unraveldata.com/saas-free-trial/