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Scaling Python with Ray: Exploring Actors, Distributed Data, and Friends in Serverless and Cloud Environments - Softcover

 
9781098118808: Scaling Python with Ray: Exploring Actors, Distributed Data, and Friends in Serverless and Cloud Environments

Synopsis

Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, authors Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while avoiding single points of failure and manual scheduling.

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About the Authors

Holden Karau is a queer transgender Canadian, Apache Spark committer, Apache Software Foundation member, and an active open source contributor. As a software engineer, she's worked on a variety of distributed computing, search, and classification problems at Apple, Google, IBM, Alpine, Databricks, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor of mathematics in computer science. Outside of software, she enjoys playing with fire, welding, riding scooters, eating poutine, and dancing.

Boris Lublinsky is a Chief Architect for IBM's Discovery Accelerator Platform, where he specializes in Kubernetes, serverless, workflows, and complex systems design. Boris has over 30 years of experience in enterprise architecture and software development. He is the co-author of Applied SOA (Wiley), Professional Hadoop Solutions (Wiley), Serving Machine Learning Models (Oâ Reilly), and Kubeflow for Machine Learning (Oâ Reilly). He is also a contributor to several open-source projects. Boris is a frequent speaker at numerous industry conferences and co-founder of several Chicago user groups.

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  • PublisherO'Reilly Media, Inc, USA
  • Publication date2022
  • ISBN 10 1098118804
  • ISBN 13 9781098118808
  • BindingPaperback
  • LanguageEnglish
  • Edition number1
  • Number of pages250

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