English | 2022 | ISBN: 9355511914 | 436 pages | PDF | 5.43 MB

Accelerate the delivery of software, data, and machine learning

Key Features
Each chapter harmonizes the DevOps, Data Eeering, and Optimized Machine Learning cultures.

Equips readers with AGILE skills to continuously re-prioritize production backlogs.
Containerization, Docker, Kubernetes, DataOps, and MLOps are all rolled together.

Description
This book instructs readers on how to operationalize the creation of systems, software applications, and business information using the best practices of DevOps, DataOps, and MLOps, among other things.

From software unit packaging code and its dependencies to automating the software development lifecycle and deployment, the book provides a learning roadmap that bs with the basics and progresses to advanced topics. This book teaches you how to create a culture of cooperation, affinity, and tooling at scale using DevOps, Docker, Kubernetes, Data Eeering, and Machine Learning. Microservices design, setting up clusters and maintaining them, processing data pipelines, and automating operations with machine learning are all topics that will aid you in your career. When you use each of the xOps methods described in the book, you will notice a clear shift in your understanding of system development.

Throughout the book, you will see how every stage of software development is modernized with the most up-to-date technologies and the most effective project management approaches.

What you will learn
Learn about the Packaging code and all its dependencies in a container.
Utilize DevOps to automate every stage of software development.
Learn how to create Microservices that are focused on a specific issue.
Utilize Kubernetes to containerize applications in a variety of settings.
Using DataOps, you can align people, processes, and technology.

Who this book is for
This book is meant for the Software Eeering team, Data Professionals, IT Operations and Application Development Team with prior knowledge in software development.



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