New Spyglass Initiative includes customizable, extensible, and sharable system for operational insights
MapR Technologies announced at the Hadoop Summit the Spyglass Initiative — a comprehensive, open, and extensible approach for increasing user and administrator productivity. The first in a series of releases as part of the Spyglass Initiative, MapR introduces new functionality to provide deep visibility with customizable dashboards that simplifies the management of big data deployments, enabling unprecedented views into converged data across containers, processes, components, and more.
The Spyglass Initiative was formed to simplify the management and extend the value of growing big data deployments. Organizations can be more effective in decision-making based on centralized information with a broad view of operational data that can easily be shared within and across organizations. The centralized monitoring opens the doors for big data analysis for all data-driven organizations. New features in the MapR Converged Data Platform include deep search across cluster-wide metrics and logs, shareable, powerful, customizable, mobile-ready, multi-tenant dashboards and extensible APIs for third-party tool integration.
Also new in the MapR Platform are performance and JSON enhancements to MapR-DB. Advanced multi-master JSON replication provides mission-critical disaster recovery for JSON documents as well as a global view of enterprise-wide data in local deployments. The next phase of optimizations on solid state drives (SSDs) delivers faster parallel processing of data through MapR-DB. The new features in the MapR Platform will be available in Q3 as per the release.
Anil Gadre, Senior Vice President, Product Management, MapR Technologies said, “We’ve always focused on making big data easier for our customers and we’ve learned a lot from our customer successes, and have applied that learning to new capabilities that will help new customers with their big data journey. With this new release, we can help our customers in two distinct ways: customers now have a better view of cluster operations in MapR and they also have a better view of project interoperability.”
