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Pepperdata Capacity Optimizer Next Gen: How Pepperdata Can Save 30% Off Your Cloud Bill

Pepperdata Capacity Optimizer Next Gen is the only cost optimization solution for both Apache Spark and microservices that can save you between 30–47% on your cloud bill. No matter if you try to manually tune your applications on your own, an estimated one-third of what is spent every day on cloud computing resources is wasted. While you might have cost-optimized your infrastructure with things like savings plans, spot and reserved instances, that doesn’t address the waste inherent in your applications.

Optimization Without Recommendations: Automating Your Cost Optimization on Amazon EKS

Learn how Pepperdata uses machine learning to provide Continuous Intelligent Tuning automatically to your Amazon EKS applications, helping your platform team recover wasted capacity and ultimately reduce your spend for cloud resources.

How Pepperdata Capacity Optimizer Next Gen Can Save 30% Off Your Cloud Bill

Pepperdata Capacity Optimizer Next Gen is the only cost optimization solution for both Apache Spark and microservices that can save you between 30–47% on your cloud bill. No matter if you try to manually tune your applications on your own, an estimated one-third of what is spent every day on cloud computing resources is wasted. While you might have cost-optimized your infrastructure with things like savings plans, spot and reserved instances, that doesn’t address the waste inherent in your applications. Pepperdata is the only cost optimization solution that.

Pepperdata with Ash Munshi and Kirk Lewis: AWS Startup Showcase, Season 3, Episode 2

Hosted by SiliconAngle and theCUBE, Pepperdata CEO Ash Munshi walks through the history of Pepperdata as well as the importance of cloud cost optimization in the world of cloud computing. Also, Senior Solution Architect Kirk Lewis gives a demo of our two solutions: Capacity Optimizer Classic—which is designed for DevOps—and Capacity Optimizer Next Gen, which focuses on the financial side of optimizing the cloud.

The Cloud Cost Optimization Company | Pepperdata CEO Ash Munshi interview with theCUBE

Pepperdata CEO Ash Munshi discusses Pepperdata's origin from stabilizing big data workloads to optimizing cloud costs in real time. With cost control becoming an imperative for companies with an uncertain economic outlook—as well as a difficulty in managing how they spend in the cloud—Munshi walks through how Pepperdata reduces cloud costs for companies in the Fortune 5 through autonomous and continuous resource utilization.

Real-Time, Automated Cost Optimization for Amazon EMR

Running your infrastructure in the cloud can lead to wasted resources and ultimately overspending. Pepperdata Capacity Optimizer for Amazon EMR operates dynamically in real time to optimize performance without the need to model your workloads ahead of time, change application code, or platform settings. It provides autonomous optimization continuously, improving resource utilization at both the instance level and with the EMR autoscaler. Watch the full video for a deep-dive on how Pepperdata solves the problem of cloud overspending and resource waste without manual intervention.

Pepperdata Capacity Optimizer for Amazon EMR

Running your infrastructure in the cloud can lead to wasted resources and ultimately overspending. Pepperdata Capacity Optimizer for Amazon EMR operates dynamically in real time to optimize performance without the need to model your workloads ahead of time, change application code, or platform settings. It provides autonomous optimization continuously, improving resource utilization at both the instance level and with the EMR autoscaler. Watch the full video for a deep-dive on how Pepperdata solves the problem of cloud overspending and resource waste without manual intervention.

2021 Kubernetes on Big Data Report: Data Management | Pepperdata

Get the Pepperdata 2021 Kubernetes on Big Data report and start your journey of better understanding how your competitors are managing their data with Kubernetes. Cloud vendors have proliferated and promised users optimal performance and tight spend. Still, many of these vendors don't provide visibility into Kubernetes big data, resulting in performance issues, poor resource allocation, overspending, and ineffective tuning. To fully optimize your Kubernetes big data, maximize performance, and reduce spend, you need to step beyond the basic K8s measurements and look at app performance.