Operations | Monitoring | ITSM | DevOps | Cloud

Without Pepperdata, the Kubernetes system scheduler only sees resource allocations—causing low utilization and inflated spend. Watch the video to learn how Pepperdata optimizes workloads running on Kubernetes. Visit pepperdata.com to learn more.

#shorts #cloudcomputing #aws #costoptimization #kubernetes

#shorts #cloudcomputing #aws #costoptimization #kubernetes

#shorts #cloudcomputing #aws #costoptimization #kubernetes

Struggling with underutilized Kubernetes resources or rising cloud costs? Learn how Pepperdata Capacity Optimizer delivers real-time, automated resource optimization for Kubernetes and Amazon EMR workloads—helping teams reduce costs and boost performance without manual tuning. In this video, discover how Pepperdata helps DevOps, platform engineers, and FinOps teams.

Struggling with underutilized Kubernetes resources or rising cloud costs? Learn how Pepperdata Capacity Optimizer delivers real-time, automated resource optimization for Kubernetes and Amazon EMR workloads—helping teams reduce costs and boost performance without manual tuning. In this video, discover how Pepperdata helps DevOps, platform engineers, and FinOps teams.

In this AWS Startup Partner Spotlight, discover how Pepperdata empowers cloud-native startups to optimize their Kubernetes and Amazon EMR workloads in real time. With automated resource optimization, companies can reduce costs by an average of 30% while increasing utilization by up to 80%—without any manual tuning. Whether you're scaling rapidly or managing unpredictable workloads, Pepperdata ensures your infrastructure runs efficiently and cost-effectively from day one.

Watch this interview between Pepperdata CEO Ash Munshi and theCUBE for insights into how Pepperdata helps customers control costs for their workloads in the cloud with real-time, automated resource optimization.

Spark Dynamic Allocation is a useful feature that was developed through the Spark community’s focus on continuous innovation and improvement. While Apache Spark users may believe Spark Dynamic Allocation is helping them eliminate resource waste, it doesn’t eliminate waste within applications themselves. Watch this video to understand SDA's benefits, where it falls short, and the solution gaps that remain with this component of Apache Spark.

Manual tuning can remediate some waste, but it doesn’t scale or address in-application waste. Watch this conversation to learn why manually tuning your Apache Spark applications is not the best approach to achieving optimization with price and performance in mind. Visit Pepperdata's page for information on real time, autonomous optimization for Apache Spark applications on Amazon EMR and EKS.