CUPERTINO, CA--(Marketwired - Sep 13, 2016) - Pepperdata recently surveyed over 100 production Hadoop users, and fast and effective troubleshooting was reported as a top operations challenge, second only to a lack of expertise or skills. Based on this customer need for improved troubleshooting tools, the company is announcing the Pepperdata Insights Service, a 30-day license for the most comprehensive Hadoop troubleshooting technology available today, along with performance troubleshooting expertise. Pepperdata's granular cluster diagnostics help operations teams reduce troubleshooting by up to 90 percent and solve their most challenging performance problems.
Even the most advanced Hadoop users encounter blind spots in the daily operations of their Hadoop clusters and frequently find themselves experiencing slowdowns or failures without being able to identify the root cause. The new service provides an opportunity to use Pepperdata software for one month and experience firsthand how fine-grained cluster metrics can help solve troubleshooting issues faster than ever before. Customers that purchase Pepperdata Insights Service receive:
- A 30-day license to the software, with full product support and no limitations on cluster size
- Two hours of performance troubleshooting support, to diagnose performance problems.
- An easy-to-use dashboard that provides visibility into usage of CPU, memory, disk, and network by group, user, and job.
Once the 30-day subscription has ended, organizations receive a full diagnostic report of their cluster activity, accompanied by expert recommendations from Pepperdata on how to improve performance moving forward.
"Hadoop operations team are struggling to troubleshoot with existing Hadoop tools that only provide node level visibility," said Ed Colonna, VP marketing and business development, Pepperdata. "Pepperdata is the only solution that provides deep, granular visibility into hardware usage at the user, job and task level across the entire cluster to solve performance problems with minimal effort."
To learn more and sign up for Pepperdata Insights Service, visit pepperdata.com/insight30.
Pepperdata develops software that governs and guarantees consistent, peak performance of Hadoop clusters from hundreds to thousands of nodes. Enterprises, from Fortune 500 companies to SMBs, trust Pepperdata to deliver transparency and control over distributed systems, and eliminate blind spots in Hadoop environments. Pepperdata provides the only solution that can anticipate and avert cluster performance issues at both the user and job level to create order out of the chaos inherent in distributed computing. Its Adaptive Performance Core™ has predictive learning capabilities that can anticipate a cluster's performance by looking 30 seconds into the future to anticipate changing conditions. Pepperdata then uses this information to reshape application usage of CPU, RAM, network and disk without user intervention, so that jobs can complete on time. Pepperdata software dynamically prevents bottlenecks in multi-tenant, multi-workload clusters so that numerous users and jobs can run reliably on a single cluster at maximum utilization, increasing throughput by 30 to 50 percent. Job performance is enforced on the fly based on priority and current cluster conditions, eliminating fatal contention for hardware resources and the need for workload isolation. The software also precisely pinpoints where problems are occurring so that IT teams can quickly identify and fix troublesome jobs. By capturing global knowledge of each cluster and controlling processes second by second to deliver Quality of Service, the software reclaims control over unpredictable cluster environments so that enterprises can realize untapped value from existing distributed infrastructures. The distributed systems supervisor installs in under an hour runs on existing clusters, and is compatible with all major Hadoop distributions. With Pepperdata, organizations can put their big data to use in production to meet business objectives today and satisfy future use cases.