Past Meetup

Building Faster Streaming Applications with Apache Storm 1.1

This Meetup is past

134 people went

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Stream processing has become the defacto standard for building real-time ETL and Stream Analytics applications. We see batch workloads move into Stream processing to to act on the data and derive insights faster. With the explosion of data with "Perishable Insights" such IoT and machine-generated data, Stream Processing + Predictive Analytics is driving tremendous business value.

Storm is over 4 years old as an open source project, and an Apache project for more than 3 years, Apache Storm is one of the most mature, enterprise-ready and widely adopted real-time data platforms available. Apache Storm is used across a wide range of industries, from Fortune 500 companies, to three-letter government agencies, to big data startups. Come to this meetup explore how Storm has evolved over the years and what is new with Storm 1.1. We will discuss new features, performance improvements, project roadmaps, and it's relationship with other open source streaming solutions. Additionally, we will look at the state of streaming SQL in Apache Storm, the upcoming Apache Beam integration, and a new effort at Apache that will allow users to create streaming analytics applications visually, without the need to delve into the world of a software developer.

To develop Streaming applications faster, we are introducing new open source tool - Streamline. It is a self-service framework & API that will ease building streaming application and deploy the streaming application across multiple frameworks/engines that users prefer in a snap. It simplifies integration with Machine Learning models for scoring and classification of data for Predictive Analytics. It provides an elegant way to build Analytics dashboards to derive business insights out of the streaming data and to allow the business users to consume it easily.


6:00pm: Doors open

6:00pm - 6:15pm: Networking, Pizza and Drinks

6:15pm - 6:30pm: Introduction & Storm 1.1 Release

6:30pm - 7:15pm: Storm Worker Improvements - Roshan Naik

7:15pm - 8:00pm: Storm in Retail Context: Catalog data processing using Kafka, Storm & microservices - Karthik Deivasigamani - WalMart Labs

8:00pm - 8:45pm Schema Registry & StreamLine - Sriharsha Chintalapani