Steffen Hausmann

In the fast-paced world of mortgage lending, speed and accuracy are crucial. To support their underwriters, Vontive transformed written rules for loan eligibility from a Google Doc into SQL queries for evaluation in a Postgres database.

Next time you want to integrate with a new destination for a demo, concept or production application, the Async Sink framework will bootstrap development, allowing you to move quickly without compromise.

At the end of this session you will be ready to accelerate your streaming data analytics development lifecycle. We will explore how the notebook development environment of Apache Zeppelin integrates with Apache Flink, enables us to quickly develop and build jobs and deploy them to a production Flink cluster.

In this workshop, you explore an end to end example that combines batch and streaming aspects in one uniform Beam pipeline. Check out the prerrequisites and additional registration.

Build real-time applications using Apache Flink with Apache Kafka and Amazon Kinesis Data Streams. Apache Flink is a framework and engine for building streaming applications for use cases such as real-time analytics and complex event processing.

We will explore an end to end example that combines batch and streaming aspects in one uniform Beam pipeline, and deploy it to a fully managed environment with Amazon Kinesis Data Analytics.

In this session, we walk through how to perform real-time analytics on ride-sharing and taxi data, and we explore how to build a reliable, scalable, and highly available streaming architecture based on managed services. You learn how to deploy, operate, and scale an Apache Flink application with Amazon Kinesis Data Analytics for Java applications.

Bring your Apache Kafka cluster to Amazon Managed Streaming for Kafka. Amazon MSK is a fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data.

In this chalk talk, we discuss the benefits of different AWS streaming services and walk through some use cases for each. We share best practices based on real customer examples and discuss a framework that you can use to determine which set of services best suit your specific use case.