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See live demos of modern application development technologies.

Orchestrating Data Pipelines with Data Flow with Glenn Renfro

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12:00 PM PDT on Tuesday, May 25, 2021

Orchestrating Data Pipelines with Data Flow with Glenn Renfro

Orchestrating Data Pipelines with Data Flow with Glenn Renfro

May 25 2021

In this episode

With the quantity and types of data that must be processed in real time by enterprises today, we may be asking ourselves, “How do we create solutions to process this data and how do we orchestrate these solutions?” This discussion shows how Spring Cloud Data Flow (SCDF) can continuously deploy, scale, monitor, and manage your stream and batch workloads by using the capabilities on Kubernetes.

This session walks you through the tooling capabilities of SCDF. In addition to the core orchestration features, you will also see a demo of creating a real-time streaming pipeline on Kubernetes, using recipes such as functional composition of the applications, and managing workloads. You will also see a demo on scheduling and continuously deploying batch workloads on Kubernetes, creating a single-step batch job with no coding, and distributing batch job processing across multiple machines.

Guests

Glenn Renfro

Glenn Renfro

As a VMware engineer, Glenn Renfro is a core committer for Spring Cloud Task, Spring Batch, and Spring Cloud Data Flow. He has 14 years of experience in designing, building, and delivering enterprise-level applications in Java and 21 years total of software development experience.

Hosts

Tiffany Jernigan

Tiffany Jernigan

Tiffany is a senior developer advocate at VMware and is focused on Kubernetes. She previously worked as a software developer and developer advocate (nerd whisperer) for containers at Amazon. She also formerly worked at Docker and Intel. Prior to that, she graduated from Georgia Tech with a degree in electrical engineering. In her free time she likes to spend time with her fiancé, family, and friends, as well as dabble in photography. You can find her on Twitter @tiffanyfayj.