Combining Dataops, Mlops and Devops : Outperform Analytics and Software Development With Expert Practices on Process Optimization and Automation

Accelerate the delivery of software, data, and machine learning

Key Features

● Each chapter harmonizes the DevOps, Data Engineering, 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 begins 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 Engineering, 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 Engineering team, Data Professionals, IT Operations and Application Development Team with prior knowledge in software development.

Table of Contents

1. Container – Containerization is the New Virtualization

2. Docker with Containers for Developing and Deploying Software

3.DevOps to Build at Scale a Culture of Collaboration, Affinity, and Tooling

4. Docker Containers for Microservices Architecture Design

5. Kubernetes – The Cluster Manager for Container

6. Data Engineering with DataOps

7. MLOps: Engineering Machine Learning Operations

8. xOps Best Practices