AWS Innovator Benjamin Black Joins Pivotal To Lead Internet of Things Lab

Benjamin Black, one of the key resources behind the concept and implementation of Amazon Web Services, joined Pivotal Cloud Foundry as Senior Director of Technology in late February. Black collaborated with Chris Pinkham to write the proposal to build Amazon’s Elastic Cloud Compute (EC2) platform that was subsequently approved by Amazon CEO Jeff Bezos. In his new role at Pivotal Cloud Foundry, Black will lead an Internet of Things lab in Seattle that represents the cusp of Pivotal’s thought leadership about IoT data aggregation and analytics. After leading an engineering team at Amazon Web Services, Black worked at Microsoft before becoming CEO and Founder of Boundary. Black’s addition to the Pivotal Cloud Foundry team constitutes the latest of high profile hires including Joshua McKenty, former CEO of Piston Cloud Computing and OpenStack co-founder and Andrew Clay Shafer, co-founder of Puppet Labs. The announcement of Black’s hire comes head on the heels of Pivotal’s decision to open source its Big Data Suite and enter into a strategic partnership with Hortonworks. Pivotal is a spinoff of EMC and VMware that aims to drive a transformation of contemporary IT by bringing the power of cloud computing, Big Data, agile application development and real-time analytics to the modern enterprise.

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Glassbeam Integrates With Apache Spark And Enhances Its Analytics And Machine Learning Functionality

Santa Clara-based machine data analytics vendor Glassbeam recently revealed details of a new version of Glassbeam SCALAR marked by deep integration with Apache Spark. Apache Spark is a parallel data processing framework that facilitates real-time analytics, machine learning and real-time analytics by storing the results of data operators in memory and performing low latency, iterative calculations on in memory computational results. Known for its ability to automate the parallelization of tasks and jobs, Spark boasts operational efficiencies over MapReduce by a factor of 100 with respect to the execution of calculations on large datasets. Glassbeam SCALAR’s integration with Apache Spark enhances its computational capabilities as well as the platform’s machine learning functionality and capacity to perform real-time analytics on streaming datasets by means of the Spark Streaming and MLLib components of the Spark stack. Built on Cassandra, Spark’s addition to the Glassbeam’s cloud analytics platform gives it the benefits of Cassandra’s distributed data management architecture in addition to Spark’s computational, analytic and machine learning functionality. As such, today’s announcement strengthens Glassbeam’s position in the nascent but exploding internet of things analytics space by augmenting its ability to ingest, process and analyze massive amounts of data as well as enhancing Glassbeam SCALAR’s advanced analytics, machine learning and predictive analytics capabilities.