Applying Geospatial Analytics at a Massive Scale using Kafka, Spark and Elasticsearch on DC/OS

Applying Geospatial Analytics at a Massive Scale using Kafka, Spark and Elasticsearch on DC/OS


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Applying Geospatial Analytics at a Massive Scale using Kafka, Spark and Elasticsearch on DC/OS – Adam Mollenkopf, Esri

This session will explore how DC/OS and Mesos are being used at Esri to establish a foundational operating environment to enable the consumption of high velocity IoT data using Apache Kafka, streaming analytics using Apache Spark, high-volume storage and querying of spatiotemporal data using Elasticsearch, and recurring batch analytics using Apache Spark & Metronome. Additionally, Esri will share their experience in making their application for DC/OS portable so that it can easily be deployed amongst public cloud providers (Microsoft Azure, Amazon EC2), private cloud providers and on-premise environments. Demonstrations will be performed throughout the presentation to cement these concepts for the attendees.

About

Adam Mollenkopf
Esri
Real-Time & Big Data GIS Capability Lead
Redlands, CA
Twitter Tweet Websiteesri.com
Adam Mollenkopf is responsible for the strategic direction Esri takes towards enabling real-time and big data capabilities in the ArcGIS platform. This includes having the ability to ingest real-time data streams from a wide variety of sources, performing continuous and recurring spatiotemporal analytics on data as it is received & disseminating analytic results to communities of interest. He leads a team of experienced individuals in the area of stream processing and big data analytics.

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