Conference: Jun 26-28, 2017
Workshops: Jun 29-30, 2017
Track: Stream Processing @ Scale
Location:
- Salon E
Day of week:
- Monday
Stream processing has become the most dynamic, fastest growing area of the big data space. As streaming applications become more mainstream, technologies to build those applications become more mature and feature rich. For example, Apache Spark 2.0 introduced better support for streaming use cases, Google donated their DataFlow API to the Apache Foundation, and Apache Flink was built from the ground up to support streaming.
Is it possible to process unbounded streams of data with near real-time low latency, while also providing the accuracy, consistency and flexibility that modern businesses demand? This track focuses on the latest developments in processing unbounded streams of data and how to build robust, scalable data pipeline in practice with the latest tools, technologies and ideas.
by Andrew Psaltis
IoT/Data Architect working with Streaming Systems @Hortonworks
Our needs for real-time data are growing at an unprecedented rate; it is only a matter of time before you will be faced with building a real-time streaming pipeline. Often a major key decision you would need to quickly make is which stream-processing framework should you use. What if instead you could use a unified API that allows you to express complex data processing workflows, including advanced windowing and event timing and aggregate computations? Apache Beam aims to provide this...
by Ted Malaska
Committer to Flume, Avro, Pig, YARN & Architect @Cloudera
by Pat Patterson
Community Champion @StreamSets & Lecturer California State University, Monterey Bay
A lot has changed and a lot has stayed the same with Ingest and Stream Processing over the years. But today there are many options than even for Ingest and Stream Processing that one may wonder why one solution versus the other. The problem is that in this space, one size does not fit all, and that makes it all the more confusing. This talk aims at giving the audience a direction to choose when it comes to Ingest and Stream Processing.
...by Richard Kasperowski
Author of The Core Protocols: A Guide to Greatness
Open Space
by Sean T. Allen
VP Engineering @Sendence
How Did I Get Here? Building Confidence in a Distributed Stream Processor
When we build a distributed application, how do we have confidence that our results are correct? We can test our business logic over and over but if the engine executing it isn't trustworthy, we can't trust our results.
How can we build trust in our execution engines? We need to test them. It's hard...
by Neha Narkhede
Co-Creator Apache Kafka/Co-Founder & Head of Engineering @Confluent
Most applications continuously transform streams of inputs into streams of outputs. Yet the idea of directly modeling stream processing in applications is just coming into it's own after a few decades on the periphery.
This talk will cover the basic challenges of reliable, distributed, stateful stream processing. It will cover how Apache Kafka was designed to support capturing and processing distributed data streams by building...
by Igor Maravić
Software Engineer @Spotify
by Neville Li
Software Engineer @Spotify
Spotify’s data is increasing at a rate of 60 billion events per day. The current event delivery system, which is based on Kafka 0.7, is slowly but certainly reaching its limitations. To be able to seamlessly scale the event delivery system with Spotify’s growth, we decided to base the new event delivery system on Google Cloud Pubsub and Google Cloud Dataflow.
Spotify’s event delivery system is one of the foundational pieces of...
Tracks
Monday, 13 June
-
Architectures You've Always Wondered About
Case studies from: Google, Linkedin, Alibaba, Twitter, and more...
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Stream Processing @ Scale
Technologies and techniques to handle ever increasing data streams
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Culture As Differentiator
Stories of companies and team for whom engineering culture is a differentiator - in delivering faster, in attracting better talent, and in making their businesses more successful.
-
Practical DevOps for Cloud Architectures
Real-world lessons and practices that enable the devops nirvana of operating what you build
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Incredible Power of an Open-Sourced .NET
.NET is more than you may think. From Rx to C# 7 designed in the open, learn more about the power of open source .NET
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Sponsored Solutions Track 1
Tuesday, 14 June
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Better than Resilient: Antifragile
Failure is a constant in production systems, learn how to wield it to your advantage to build more robust systems.
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Innovations in Java and the Java Ecosystem
Cutting Edge Java Innovations for the Real World
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Modern CS in the Real World
Real-world Industry adoption of modern CS ideas
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Containers: From Dev to Prod
Beyond the buzz and into the how and why of running containers in production
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Security War Stories
Expert-level security track led by well known and respected leaders in the field
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Sponsored Solutions Track 2
Wednesday, 15 June
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Microservices and Monoliths
Practical lessons on services. Asks the question when and when to NOT go with Microservices?
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Modern API Architecture - Tools, Methods, Tactics
API-based application development, and the tooling and techniques to support effectively working with APIs in the small or at scale. Using internal and external APIs
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Commoditized Machine Learning
Barriers to entry for applied ML are lower than ever before, jumpstart your journey
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Full Stack JavaScript
Browser, server, devices - JavaScript is everywhere
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Optimizing Yourself
Keeping life in balance is always a challenge. Learning lifehacks
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Sponsored Solutions Track 3
