UPDATED 08:00 EDT / SEPTEMBER 27 2016

NEWS

MapR ramps up DevOps appeal with event-driven microservices support

In an effort to boost its appeal to among developers, MapR Technologies Inc. is adding support for event-driven microservices to its flagship MapR Converged Data Platform.

The move brings new capabilities ranging from microservices application monitoring and management, to integrated support for agile microservices app development, to the Hadoop-based platform.

MapR’s initiative comes at a time when microservices are rapidly gaining in popularity among enterprises and developers alike. Defined as “an approach to application development in which a large application is built as a suite of modular services,” the term microservices refers to a suite of independently deployed modular services in which each one runs a unique process and communicates through a well-defined, lightweight mechanism. That’s in contrast to the “monolithic” application development approach, in which all functionality is part of a single program.

Microservices are growing in popularity as organizations strive to reduce costs while also speeding up innovation said Jack Norris, senior vice president of data and applications at MapR. “One way to do both is to have a more efficient and productive development environment that helps them roll out new use cases much faster,” Norris said.

MapR is doing that by adding new capabilities to its platform that enable developers to better focus on creating microservices-based applications. In a statement, MapR said that its support for event-driven microservices relies on a number of new underlying capabilities, including:

  • Comprehensive monitoring of cluster-wide operations and resource usage in a single-pane-of-glass view;
  • Microservices-specific volumes for application versioning, simplifying the development lifecycle and production deployment; and
  • Microservices for A-B and multivariate testing, enabling rapid machine learning model development and optimization.

Those capabilities, MapR said, will ensure that developers have greater freedom to combine analytics and machine learning functions directly on top of their data. In addition, MapR’s Converged Data Platform is now able to orchestrate microservices with an underlying publish-and-subscribe framework that integrates data-in-motion and data-at-rest, thereby supporting continuous and low-latency processing in microservices-based applications.

“If you look at the microservices that are being deployed today, they are generally lightweight and stateless,” MapR’s Norris explained. “Apps that drive innovation today incorporate data and analytics as part of the business operations. And if you look at the intersection of microservices that can take advantage of stateful data and also use machine learning, that’s transformational.”

Together with the new capabilities, MapR also made available a Converged Application Blueprint that enterprises can follow to speed up the development of applications. It enables developers to view how microservices-based applications work and put them into production, Norris said. In addition, the blueprint comes with source code that demonstrates how microservices can be combined to create “converged applications” that are able to capture high-speed streaming data, perform real-time analytics and persist that data for historical analysis.

MapR said that microservices support would be made available immediately in the MapR Converged Community and Enterprise Editions of its platform.


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