Pepperdata introduces optimization for Spark on Kubernetes

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Pepperdata announced that its product portfolio now provides autonomous optimization and observability for Spark applications running on Kubernetes. Kubernetes is a key part of the modern hybrid, multi-cloud architecture in today’s enterprises, notes Pepperdata. As big-data applications move from Spark on legacy systems to Spark on Kubernetes, the performance of these applications can change dramatically. Pepperdata promises full-stack observability for Spark on Kubernetes, allowing developers to manually tune their applications while autonomously optimizing resources at run time. The combination of manual and autonomous tuning is necessary to deliver the best price and performance for these applications. Pepperdata uses machine learning across clusters, containers, pods, nodes, users and workflows to give you a complete understanding of your environment.

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