Concurrent Adds Spark Support to Big Data App Management Solution
Concurrent Inc. has added support for Apache Spark technology to its Big Data application performance management solution, becoming the latest in a long line of vendors embracing the ever-popular open source analytics project.
"Driven 2.0 represents an industry milestone by enabling application performance monitoring and management across heterogeneous Hadoop and Spark environments within a single, comprehensive solution," the company said in a statement Tuesday.
Concurrent, which describes itself as a "data application infrastructure" company, specializes in monitoring and managing enterprise Big Data applications, which the company said are becoming more complicated and diverse with a steady stream of new development frameworks, tools, technologies and compute engines. In an age of DevOps, Concurrent said it aims to provide visibility, measurement and control of large-scale data processing application performance.
Driven helps companies monitor the current and historical performance of Big Data applications, track key performance indicators, visually fine-tune application performance, analyze failures, monitor service-level agreements, track compliance efforts and more, Concurrent said.
With the update to version 2.0, Concurrent is adding support -- in beta right now -- for Apache Spark, an open source cluster computing framework that acts as a general engine for Big Data processing. The project is among the most popular open source initiatives under development today, providing speed and performance benefits over MapReduce, an original technology component of the Hadoop ecosystem. The performance and flexibility of Spark have created industry buzz about it rivaling Hadoop itself in the Big Data realm.
"Enterprises can now seamlessly and transparently collect all the operational intelligence for Apache Spark applications in Driven," Concurrent said. Currently in beta, new Spark support provides the comprehensive performance management required to deliver and maintain production Spark data processes."
Along with Spark, Driven works with applications written in Cacscading, Hadoop MapReduce and Apache Hive.
Other highlights of the Driven 2.0 update, Concurrent said, include redesigned application analytics and custom views and deeper search capabilities.
"Driven delivers new capabilities to segment operational metadata and create customized views and dashboards for more concise information delivery to the enterprise user," Concurrent said. "Because data processes can be unwieldy and complex, comprised of hundreds of steps, pinpointing where something was executed or went wrong in an application can be time consuming and expensive. Whether fulfilling an audit request, debugging an application, looking for a slow down or searching for dependencies, the new search capabilities in Driven enable enterprise users to quickly find specific units of work and progress to satisfy their needs."
David Ramel is an editor and writer for Converge360.