Название: AI Integration in Software Development and Operations: Transformation Through AI Infusion in Devops, Testing, and SRE
Автор: Abhinav Krishna, Vamshidhar Meda
Издательство: Apress
Год: 2024
Страниц: 314
Язык: английский
Формат: pdf
Размер: 10.1 MB

Discover how Artificial Intelligence (AI) is transforming the fields of software development, testing, and IT operations by enhancing efficiency, reducing human error, and accelerating processes. This book showcases the practical applications of AI-driven tools, such as automating coding, testing, and operational tasks, predicting potential issues, and optimizing performance.

Aimed at digital leaders, practitioners, and customers, this book provides strategic insights and actionable guidance on how to integrate AI technologies to boost productivity, enhance product quality, and streamline development cycles. It serves as a comprehensive guide for those looking to leverage AI to drive innovation, cut costs, and stay competitive in an ever-evolving technological landscape.

You'll explore how AI can be integrated into software development, testing, and IT operations to improve efficiency, accuracy, and speed. Through real-world use cases, you'll see how AI-driven tools can automate tasks, reduce human error, and improve processes across the development lifecycle. AI Integration in Software Development and Operations offers actionable insights on using AI to accelerate innovation, enhance product quality, and optimize costs in your modern software and IT environments.

In software development, AI can assist in generating code snippets, identifying potential defects early in the process, and even offering intelligent recommendations to developers. In testing, AI-driven algorithms can generate test cases, perform intelligent regression testing, and improve the speed and accuracy of error detection. When it comes to IT operations, AI can boost observability, automate routine maintenance tasks, and predict outages before they occur, ensuring high availability, great performance, and increased customer satisfaction.

This book presents a collection of real-world use cases in which AI plays a critical role in improving the efficiency, scalability, and quality of these processes. It delves into how AI can help analyze data and help developers with decision points, and it provides the hidden messages in the data. Furthermore, the book highlights how AI can significantly reduce the risks associated with human error, which remains one of the most common causes of downtime, security breaches, and project delays.

What You Will Learn:

Review the SDLC lifecycle, DevOps, SRE and accompanying topics
Understand machine learning basics, AI techniques, and data preprocessing for DevOps
Explore how AI integration into all phases of SDLC boosts productivity, increases
effectiveness, and reduces human error
Gain a familiarity with AI tools, their use cases, and the value in integrating them

Who This Book is For:
Software engineers, developers, programmers, DevOps engineers, and AI practitioners who are interested in integrating AI into their DevOps practices.






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