Machine Learning in Microservices

With the rising need for agile development and very short time-to-market system deployments, incorporating machine learning algorithms into decoupled fine-grained microservices systems provides the perfect technology mix for modern systems. Machine Learning in Microservices is your essential guide to staying ahead of the curve in this ever-evolving world of technology.
The book starts by introducing you to the concept of machine learning microservices architecture (MSA) and comparing MSA with service-based and event-driven architectures, along with how to transition into MSA. Next, you’ll learn about the different approaches to building MSA and find out how to overcome common practical challenges faced in MSA design. As you advance, you’ll get to grips with machine learning (ML) concepts and see how they can help better design and run MSA systems. Finally, the book will take you through practical examples and open source applications that will help you build and run highly efficient, agile microservices systems.
By the end of this microservices book, you’ll have a clear idea of different models of microservices architecture and machine learning and be able to combine both technologies to deliver a flexible and highly scalable enterprise system.

Type
ebook
Category
publication date
2023-03-10
what you will learn

Recognize the importance of MSA and ML and deploy both technologies in enterprise systems
Explore MSA enterprise systems and their general practical challenges
Discover how to design and develop microservices architecture
Understand the different AI algorithms, types, and models and how they can be applied to MSA
Identify and overcome common MSA deployment challenges using AI and ML algorithms
Explore general open source and commercial tools commonly used in MSA enterprise systems

no of pages
270
duration
540
key features
Design, build, and run microservices systems that utilize the full potential of machine learning * Discover the latest models and techniques for combining microservices and machine learning to create scalable systems * Implement machine learning in microservices architecture using open source applications with pros and cons
approach
Readers will be taken through a set of specific software patterns and learn, in detail, how to apply these patterns and build working software on top of existing systems. At each step along the way, the reader will learn about the subcomponents and subsystems which comprise the larger system and which may be used in the future to solve different types of challenges.
audience
This book is for machine learning solution architects, system and machine learning developers, and system and solution integrators of private and public sector organizations. Basic knowledge of DevOps, system architecture, and artificial intelligence (AI) systems is assumed, and working knowledge of the Python programming language is highly desired.
meta description
Implement real-world machine learning in a microservices architecture as well as design, build, and deploy intelligent microservices systems using examples and case studies
Purchase of the print or Kindle book includes a free PDF eBook
short description
Agile development and quick time-to-market deployments are crucial for competitive markets and dynamic needs, and deploying artificial intelligence technologies in microservices architecture creates flexible and adaptive systems. This practical guide helps developers and architects to design and deploy intelligent microservices systems.
subtitle
Productionizing microservices architecture for machine learning solutions
keywords
Python book; Machine Learning python; Agile project; a.i. artificial intelligence; agile software; AL/ML; a.i. artificial intelligence
Product ISBN
9781804617748