Concurrent improves big data application performance management
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.
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"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:
"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."