leo

About Leo Schoukroun

Leo is a Big Data & Hadoop solution architect with 2 years of experience on Hadoop and Distributed Systems. He has designed, developed and operated data ingestion workflows and real-time services while accompanying his clients in defining their needs and implementing them. It is versatile on Big Data platforms, from planning, design and architecture of cluster deployment, administration, maintenance and prototyping and application industrialization in collaboration with business users, analysts , Data Scientists, Engineers and Operations Teams.

Hadoop cluster takeover with Apache Ambari

We recently migrated a large production Hadoop cluster from a “manual” automated install to Apache Ambari, we called this the Ambari Takeover. This is a risky process and we will detail why this operation was required and how we did it. […]

By |2018-11-20T13:54:41+00:00November 15th, 2018|Categories: Adalas Summit 2018, Big Data|Tags: , , , |0 Comments

Present and future of Hadoop workflow scheduling: Oozie 5.x

During the DataWorks Summit Europe 2018 in Berlin, I had the opportunity to attend a breakout session on Apache Oozie. It covers the new features released in Oozie 5.0, including future features of Oozie 5.X, which is the main subject of this article. They spent some time discussing the Apache Ambari’s Workflow Scheduler and its way [...]

By |2018-06-05T22:36:37+00:00May 23rd, 2018|Categories: Big Data, DataWorks Summit 2018|Tags: , |2 Comments

Apache Thrift VS REST

Adaltas recently attended the Open Source Summit Europe 2017 in Prague. I had the opportunity to follow a presentation made by Randy Abernethy and Jens Geyer of RM-X, a cloud native consulting company, about the use of Apache Thrift in the building of high performance microservices. The focus was that Thrift is very fast and [...]

By |2018-06-05T22:36:50+00:00October 28th, 2017|Categories: Open Source Summit Europe 2017|0 Comments