What is Scalability in Cloud Computing?

What is Scalability in Cloud Computing?

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Automatically Optimize Your Big Data Workloads and Amazon EMR Infrastructure

Big data in the cloud has a lot of moving parts, overlap, and sprawling interdependencies that make understanding cloud resource usage a challenge. Pepperdata helps you leverage cloud visibility deployments, accelerate your cloud adoption, streamline IT operations, and deliver great customer experiences.

Pepperdata for Amazon EMR provide full-stack observability, automated tuning, and real-time insights across all of your EMR instances—all in one place. Automatically optimize your big data and improve cloud price/performance by up to 3X.

  • Get full-stack observability, automated tuning, and job-specific recommendations for Spark and MapReduce.
  • Automatically optimize node performance and prevent waste by applications.
  • Customize alerts to quickly understand and troubleshoot application and infrastructure issues.
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Reduce Amazon EMR Costs

Cloud providers provision infrastructure based on the peak needs of workloads. This guarantees the maximums are met, but can create a lot of waste. Pepperdata Capacity Optimizer uses machine learning to make thousands of decisions per second, analyzing and optimizing the resource usage of each node in real time to optimize the utilization of CPU, memory, and I/O resources on big data clusters. The net effect is that horizontal scaling is optimized and waste is eliminated. With automated tuning you can:

  • Run the same number of workloads on fewer instances.
  • Optimize each node’s ability to run an optimal number of containers.
  • Decrease the persistence of backlogs as applications wait for resources.

Pepperdata for Amazon EMR

Pepperdata for Amazon EMR includes:

Capacity Optimizer

Automatically tune applications and infrastructure and recapture cloud resources. Optimize your cluster resources and run more applications.