Improving Autoscaling Just Got Easier

Autoscaling from cloud service providers offers valuable elasticity for big data deployments. But, based on workload peak needs, it also leads to wasted resources and inflated costs. You need a way to optimize your resource utilization and reduce costs without requiring a complicated application implementation.

The latest benchmark results using TPC-DS workloads with Pepperdata Capacity Optimizer on Amazon EMR show that you can dramatically lower your costs and improve performance. Capacity Optimizer can be seamlessly added to Amazon EMR Auto Scaling deployments. The solution makes thousands of decisions per second, analyzing the resource usage of each node to optimize CPU, memory, and I/O resources. The net result is optimized horizontal scaling and reduced waste.

Read The Benchmark Report To See How We Can Optimize Your Big Data Analytics Stack

✔ Ensure optimal performance for all of your workloads.

✔ Reduce infrastructure costs and recapture wasted capacity.

✔ Improve cluster throughput, real-time visibility, and more.

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