Scaling Python with Ray: Adventures in Cloud and Serverless Patterns

By:

Karau, Holden

By:

Lublinsky, Boris

Publication details: Mumbai: Shroff Publishers & Distributors Pvt. Ltd., 2023Description: 249ISBN:

9789355423757

DDC classification:

005.133 (PYT) KAR

Summary: 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, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified system for batch and stream processing Apply advanced data processing with Ray Build microservices with Ray Implement reliable Ray applications

List(s) this item appears in: New Arrivals for the Month of September - 2023

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Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Alliance College of Engineering and Design	CSE & IT	005.133 (PYT) KAR (Browse shelf(Opens below))	Available		E12614

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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, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness.

If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to:

Implement stateful applications with Ray actors
Build workflow management in Ray
Use Ray as a unified system for batch and stream processing
Apply advanced data processing with Ray
Build microservices with Ray
Implement reliable Ray applications

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