03757nam a22004335i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001300153050001400166072001600180072002300196072001500219100008600234245019000320250001800510264005400528300006500582336002600647337002600673338003600699347002400735505050700759520165801266650002902924650002602953650002902979650002603008700007503034710003403109773002603143776003603169776003603205776003603241856004603277979-8-8688-1044-2DE-He21320251030114633.0cr nn 008mamaa241221s2024    xxu|    s    |||| 0|eng d  a97988688104427 a10.1007/979-8-8688-1044-22doi 4aQ334-342 4aTA347.A78 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema1 aKaiser, Abhinav Krishna.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aAI Integration in Software Development and Operationsh[electronic resource] :bTransformation Through AI Infusion in DevOps, Testing, and SRE /cby Abhinav Krishna Kaiser, Vamshi Meda.  a1st ed. 2024. 1aBerkeley, CA :bApress :bImprint: Apress,c2024.  aXIX, 318 p. 50 illus., 49 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aChapter 1: First Steps in AI and DevOps -- Chapter 2: Double Click on Machine Learning -- Chapter 3: Software Development and AI Augmentation -- Chapter 4: Planning and Requirements Management in Projects -- Chapter 5: Integrating Generative AI in Software Design and Architecture -- Chapter 6: AI Infusion in Software Build and Development -- Chapter 7: Infusing AI into Software Testing -- Chapter 8: AI in Continuous Delivery -- Chapter 9: Operations, Observability and Site Reliability Engineering.  aDiscover 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. You will: 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. 0aArtificial intelligence. 0aSoftware engineering.14aArtificial Intelligence.24aSoftware Engineering.1 aMeda, Vamshi.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z979886881043508iPrinted edition:z979886881045908iPrinted edition:z979886881342940uhttps://doi.org/10.1007/979-8-8688-1044-2