Ai Integration In Software Development And Operations
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AI Integration in Software Development and Operations
Author: Abhinav Krishna Kaiser
language: en
Publisher: Springer Nature
Release Date: 2024-12-20
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. 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.
Artificial Intelligence for Cloud-Native Software Engineering
Artificial intelligence is transforming software engineering by automating development, testing, deployment, and security processes, leading to more efficient and high-quality software solutions. AI-powered tools enhance scalability, reliability, and real-time analytics, enabling businesses to optimize operations and improve decision-making. As cloud-native architectures gain traction, AI-driven innovations are reshaping the way software is designed, maintained, and evolved, driving a new era of intelligent and adaptive technology solutions. Artificial Intelligence for Cloud-Native Software Engineering explores the transformative impact of AI on the software engineering lifecycle, highlighting its role in automating and enhancing various stages of software development. It provides a comprehensive overview of how AI technologies can assist software architects and engineers in creating high-quality, enterprise-grade software efficiently. Covering topics such as source code creation, data security, and multiparameter optimization, this book is an excellent resource for software engineers, computer scientists, professionals, researchers, scholars, academicians, and more.
Synergizing AI, DevOps, and Deep Learning: Integrating NLP for Next-Generation Innovations
Author: Venkata Mohit Tamanampudi
language: en
Publisher: Libertatem Media Private Limited
Release Date: 2023-04-12
This book explores the powerful intersection of Artificial Intelligence (AI), DevOps, Natural Language Processing (NLP), and Deep Learning, focusing on how these technologies can be combined to build more efficient, automated, and intelligent systems. It delves into the principles behind AI and DevOps, offering a roadmap for integrating these practices to enable continuous delivery and automation of machine learning models. NLP is highlighted as a critical technology that bridges human-computer interaction, while Deep Learning provides the backbone for powerful, data-driven decision-making systems. Readers will gain practical insights into building scalable systems, utilizing AI-driven DevOps pipelines, and integrating NLP for developing smart, interactive applications. The book will provide real-world examples and step-by-step guides for adopting cutting-edge AI/ML methodologies with the speed and agility of DevOps processes, making it an essential read for data scientists, AI engineers, and DevOps practitioners.