Advertisement

Pepperdata Helps HPE Improve Performance and Streamline Its Big Data Systems

By on

by Angela Guess

A new press release states, “Pepperdata, the DevOps for Big Data company, today announced that Hewlett Packard Enterprise (HPE) has selected the Pepperdata product suite to automatically optimize its Hadoop clusters and improve monitoring, tuning, and troubleshooting. The Pepperdata product suite helps HPE to better manage its big data environment, providing several measurable benefits. With the industry’s most comprehensive portfolio, spanning the cloud to the data center to the intelligent edge, HPE’s technology and services help customers around the world make IT more efficient, more productive, and more secure.”

Ash Munshi, CEO of Pepperdata, commented, “As modern distributed systems and applications scale in size and complexity, achieving optimal performance remains one of the most significant challenges of Big Data… Pepperdata is excited to partner with HPE to better understand its unique big data challenges, and provide the team with a practical, innovative solution. The Pepperdata product suite gives HPE deep granularity into its clusters, enabling the company to streamline workflow efficiency, improve performance, and stay ahead of issues that could impact long-term cluster health.”

The release continues, “The Pepperdata product suite enables enterprises to automatically optimize big data clusters and provides solutions for monitoring, tuning, and troubleshooting. Pepperdata allows enterprises to: Reduce time-to-problem resolution using comprehensive and detailed performance data, allowing operators to troubleshoot performance problems 10x faster. Increase capacity utilization by 30 percent to 50 percent without adding hardware, automatically increasing job productivity and deployment. Provide developers with tools that help them understand performance impacts and make recommendations on how to better optimize their jobs.”

Read more at Marketwired.

Photo credit: Pepperdata

Leave a Reply