Andrei Varanovich leads the Data & AI team at InSpark (The Netherlands) where his primary focus is on building cloud-first data solutions on Azure. Passionate about technology, people and professional communities. Earned Microsoft Most Valuable Professional award every year since 2009. Holds a PhD in Computer Science from the University of Koblenz-Landau, Germany.
October 2, 2018 05:00 PM PT
The term “Lambda Architecture” stands for a generic, scalable and fault-tolerant data processing architecture. As the hyper-scale now offers a various PaaS services for data ingestion, storage and processing, the need for a revised, cloud-native implementation of the lambda architecture is arising.
In this talk we demonstrate the blueprint for such an implementation in Microsoft Azure, with Azure Databricks -- a PaaS Spark offering – as a key component. We go back to some core principles of functional programming and link them to the capabilities of Apache Spark for various end-to-end big data analytics scenarios.
We also illustrate the “Lambda architecture in use” and the associated tread-offs using the real customer scenario – Rijksmuseum in Amsterdam – a terabyte-scale Azure-based data platform handles data from 2.500.000 visitors per year.
Session hashtag: #SAISDev6