Data application infrastructure specialist Concurrent today released the latest version of Driven, its big data application performance management solution. Concurrent is also the primary sponsor of the open source Cascading application development framework for big data.
Driven is purpose-built to address the pain points of enterprise application development and application performance management on Apache Hadoop, particularly organizations that have adopted data lakes and now have a multitude of departments accessing a single, shared resource.
"The [Hadoop] distributions have done a good job of the systems management stuff," says Gary Nakamura, CEO of Concurrent. "We're not really focused on deployment of Hadoop nodes and the health of those nodes. What we're really focused on is what's on top — visibility from the application layer through to the business level."
But, of course, Hadoop isn't the be-all-and-end-all of the big data ecosystem, so part of the Driven 2.0 release is supporting heterogeneity.
"The reality of what's happening in the enterprise right now is that they use whatever tool is available to them that will solve their problem — Cascading for ETL, Spark for machine learning, Hive for ad hoc queries and so on," Nakamura says. "What we see is a heterogeneous environment. Driven needs to be able to support these different frameworks."
Key new features of Driven 2.0 include the following:
- Support for Apache Spark. Enterprises can now seamlessly and transparently collect all the operational intelligence for Apache Spark applications in Driven. Currently in beta.
- Redesigned application analytics and custom views. The release delivers new capabilities to segment operational metadata and create customized views and dashboards for more concise information delivery to the enterprise user. Driven 2.0 also features new and more comprehensive visualization and navigation of applications with the aim of providing a more intuitive view of applications and transaction history. Users can now drill down in real time or to specific time periods to view the health of an application or clusters or the processes associated with a specific organization.
- Deeper search capabilities. Data processes can be unwieldy and complex, which makes pinpointing where something was executed or went wrong in an application time consuming and expensive. The new search capabilities allow enterprise users to quickly find specific units of work, whether they're fulfilling an audit request, debugging an application, looking for a slow down or searching for dependencies.
"Enterprise needs have not changed," Nakamura says. "They want a comprehensive solution to monitor and manage their data processes. They want technical, operational, organizational and business-level context on every process. They want to measure how these processes are performing, how they are consuming resources and whether they are delivering or not — and if they aren't, where is the issue? Driven equips enterprises with this and more, and is playing a critical role in the success of big data initiatives in the enterprise."
This story, "Concurrent improves big data application performance management" was originally published by CIO.