Everything is a data source, and today’s online activities, financial operations, and IoT devices and sensors generate data at an ever-increasing rate. So how do we ingest, process, and manage that data? We need an architecture to ingest these incoming influxes of data that is flexible, scalable, fast, and resilient.
Alena Hall walks you through setting up and building a distributed streaming architecture on Azure using open source frameworks like Apache Kafka and Spark Streaming. You’ll use these distributed systems to process data coming from multiple sources in real time and perform machine learning tasks. Along the way, you’ll discover how to effectively and interactively experiment with streams.
Lena Hall is a senior software engineer and developer advocate at Microsoft working on Azure, where she focuses on large-scale distributed systems and modern architectures. Lena has more than 10 years of experience in software engineering with a focus on distributed cloud programming, real-time system design, highly scalable and performant systems, big data analysis, data science, functional programming, and machine learning. Previously, she was a senior software engineer at Microsoft Research. She’s an elected member of the F# Software Foundation’s board of trustees, co-organizes a conference called ML4ALL, and is often an invited member of program committees for conferences like Kafka Summit, Lambda World, and others. Lena holds a master’s degree in computer science.
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