Ai Powered Devops
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| Author | : Eran Kinsbruner |
| Publisher | : Independently Published |
| Total Pages | : 357 |
| Release | : 2020-08-10 |
| Genre | : |
| ISBN | : |
The book "Accelerating Software Quality: Machine Learning and Artificial Intelligence in the Age of DevOps" is a complete asset for software developers, testers, and managers that are on their journey to a more mature DevOps workflow, and struggle with better automation and data-driven decision making. DevOps is a mature process across the entire market, however, with existing Non-AI/ML technologies and models, it comes short in expediting release cycle, identifying productivity gaps and addressing them. This book, that was implemented by myself with the help of leaders from the DevOps and test automation space, is covering topics from basic introduction to AI and ML in software development and testing, implications of AI and ML on existing apps, processes, and tools, practical tips in applying commercial and open-source AI/ML tools within existing tool chain, chat-bots testing, visual based testing using AI, automated security scanning for vulnerabilities, automated code reviews, API testing and management using AI/ML, reducing effort and time through test impact analysis (TIA), robotic process automation (RPA), AIOps for smarter code deployments and production defects prevention, and many more.When properly leveraging such tools, DevOps teams can benefit from greater code quality and functional and non-functional test automation coverage. This increases their release cycle velocity, reduces noise and software waste, and enhances their app quality.The book is divided into 3 main sections: *Section 1 covers the fundamentals of AI and ML in software development and testing. It includes introductions, definitions, 101 for testing AI-Based applications, classifications of AI/ML and defects that are tied to AI/ML, and more.*Section 2 focuses on practical advises and recommendations for using AI/ML based solutions within software development activities. This section includes topics like visual AI test automation, AI in test management, testing conversational AI applications, RPA benefits, API testing and much more.*Section 3 covers the more advanced and future-looking angles of AI and ML with projections and unique use cases. Among the topics in this section are AI and ML in logs observability, AIOps benefits to an entire DevOps teams, how to maintain AI/ML test automation, Test impact analysis with AI, and more.The book is packed with many proven best practices, real life examples, and many other open source and commercial solution recommendations that are set to shape the future of DevOps together with ML/AI
| Author | : Sumanth Tatineni |
| Publisher | : Libertatem Media Private Limited |
| Total Pages | : 251 |
| Release | : 2024-03-15 |
| Genre | : Computers |
| ISBN | : 8197138214 |
Unlock the future of software development with Integrating Artificial Intelligence with DevOps: Advanced Techniques, Predictive Analytics, and Automation for Real-Time Optimization and Security in Modern Software Development. This comprehensive monograph is a must-read for professionals seeking to revolutionize their DevOps workflows through the power of AI. Dive deep into the intricate integration of Artificial Intelligence within DevOps practices and discover advanced methodologies that enhance every stage of the software development lifecycle. From predictive analytics and intelligent automation to real-time optimization and robust security measures, this book offers a wealth of knowledge for optimizing software delivery. Explore practical applications, in-depth case studies, and best practices that illustrate the transformative potential of AI in DevOps. Each chapter builds on the previous, providing a seamless and cohesive narrative that guides readers through foundational concepts to advanced implementations. Whether you're looking to improve CI/CD pipelines, automate testing and monitoring, manage infrastructure more efficiently, or enhance security with AI-driven techniques, this book equips you with the tools and insights needed to ensure high-quality, secure, and efficient software delivery. Join the vanguard of modern software development with Integrating Artificial Intelligence with DevOps, and harness AI to achieve real-time optimization and unparalleled security in your DevOps processes.
| Author | : Stephen Fleming |
| Publisher | : Stephen Fleming |
| Total Pages | : 100 |
| Release | : 2020-07-14 |
| Genre | : Computers |
| ISBN | : |
What comes to your mind after reading the below statements from a renowned industry research firm? It is predicted that a large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023. Also, Only 47% of machine learning models are making it into production (Comes MLOPS!) Do you have similar thoughts? Is it just a new Buzzword or repackaging of the existing system? If it’s for real, how is it going to impact the Business/Industry? How my business or job would get impacted? If it has just started, how can I leverage from wherever I am? Which are the major players/startups in this area? Depending on your role, it may be useful for you to know about AIOPS & MLOPS: If you are a Business Consultant trying to make the system more efficient and profitable, reaping the benefits of Automation in your application development process If you are a Technology Consultant and want to make your operation more Agile, Automated and easily deployable If you are a Technology Professional looking for a role in these upcoming areas to be an early adopter in your organization or just starting your career and want to understand the ecosystem If you are from HR or Training field and want to understand the job/Training requirements for these upcoming roles Beyond the apparent hustle and bustle of buzzwords and nomenclature every year, I genuinely believe that AI would drastically change the software development and deployment model in the next two years, and all these new startups would drive this change. It’s astonishing how fast this cycle is moving. Especially for us who had seen the world before the internet came into our daily lives!!This book is my attempt to update you on the unfolding story of AIOPS and MLOPS as “story till now. “ So here is to our Continuous Learning and Progress! Cheers.
| Author | : Noah Gift |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 720 |
| Release | : 2018-07-12 |
| Genre | : Computers |
| ISBN | : 0134863917 |
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
| Author | : Aditya Pratap Bhuyan |
| Publisher | : Aditya Pratap Bhuyan |
| Total Pages | : 391 |
| Release | : 2024-09-26 |
| Genre | : Computers |
| ISBN | : |
In today’s rapidly evolving digital landscape, organizations are increasingly seeking faster, more efficient ways to develop, test, and deploy software. "DevOps Unleashed: Bridging Development and Operations for Continuous Success" is a comprehensive guide that demystifies the world of DevOps and its transformative impact on modern enterprises. Written by Aditya Pratap Bhuyan, a seasoned expert with over 20 years of experience in enterprise and cloud applications, this book is tailored for professionals at all levels, offering both technical insights and a deep understanding of the cultural changes essential for DevOps success. With more than 40 industry certifications and extensive experience in Java, Spring, microservices, cloud computing, and container technologies like Docker and Kubernetes, Aditya brings a wealth of knowledge to this book. He not only covers the tools and technologies that form the backbone of a successful DevOps strategy but also emphasizes the importance of collaboration and breaking down silos between development and operations teams. "DevOps Unleashed" begins by exploring the origins of DevOps, examining how it evolved from traditional software development practices to a modern, agile framework. Aditya delves into the cultural mindset needed to fully embrace DevOps, illustrating how collaboration, communication, and continuous improvement are as vital as the technical aspects. The book is divided into well-structured chapters that cover key pillars of DevOps, such as Continuous Integration/Continuous Delivery (CI/CD), Infrastructure as Code (IaC), automation, monitoring, and security. Aditya walks readers through setting up CI/CD pipelines, automating infrastructure with tools like Terraform, and leveraging real-time monitoring tools like Prometheus and Grafana to ensure system health. The practical hands-on examples, case studies, and real-world scenarios make complex topics accessible for both novices and seasoned practitioners. One of the standout aspects of the book is its focus on DevSecOps—integrating security at every stage of the software development lifecycle. Aditya emphasizes the growing importance of security in DevOps pipelines and provides practical strategies for automating security checks and ensuring compliance. For those looking to go beyond the basics, the book also covers advanced DevOps topics such as chaos engineering, site reliability engineering (SRE), and the role of AI and machine learning in automating DevOps processes. This book is not just about tools or methodologies—it’s about adopting a new mindset. Aditya helps readers understand that DevOps is a journey, one that requires continuous learning, adaptation, and a commitment to innovation. Whether you’re an engineer, a team lead, or an executive looking to implement DevOps at scale, "DevOps Unleashed" offers a roadmap to success. By the end of this book, readers will have gained a holistic understanding of DevOps—both its cultural foundations and technical implementations—and be equipped to build, scale, and optimize DevOps practices in their own organizations.
| Author | : Noah Gift |
| Publisher | : O'Reilly Media |
| Total Pages | : 506 |
| Release | : 2019-12-12 |
| Genre | : Computers |
| ISBN | : 1492057665 |
Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
| Author | : Mariya Yao |
| Publisher | : |
| Total Pages | : 246 |
| Release | : 2018-04-30 |
| Genre | : Artificial intelligence |
| ISBN | : 9780998289021 |
This bestselling book gives business leaders and executives a foundational education on how to leverage artificial intelligence and machine learning solutions to deliver ROI for your business.
| Author | : Matthew Skelton |
| Publisher | : IT Revolution |
| Total Pages | : 210 |
| Release | : 2019-09-17 |
| Genre | : Business & Economics |
| ISBN | : 1942788827 |
Effective software teams are essential for any organization to deliver value continuously and sustainably. But how do you build the best team organization for your specific goals, culture, and needs? Team Topologies is a practical, step-by-step, adaptive model for organizational design and team interaction based on four fundamental team types and three team interaction patterns. It is a model that treats teams as the fundamental means of delivery, where team structures and communication pathways are able to evolve with technological and organizational maturity. In Team Topologies, IT consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help readers choose and evolve the right team patterns for their organization, making sure to keep the software healthy and optimize value streams. Team Topologies is a major step forward in organizational design for software, presenting a well-defined way for teams to interact and interrelate that helps make the resulting software architecture clearer and more sustainable, turning inter-team problems into valuable signals for the self-steering organization.
| Author | : Mark Treveil |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 171 |
| Release | : 2020-11-30 |
| Genre | : Computers |
| ISBN | : 1098116429 |
More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized
| Author | : Behram Irani |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 416 |
| Release | : 2024-08-30 |
| Genre | : Computers |
| ISBN | : 1835081207 |
Leverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasks Key Features First book on the market to thoroughly explore all of Amazon Q Developer’s features Gain an understanding of Amazon Q Developer's capabilities across the software development life cycle through real-world examples Build apps with Amazon Q Developer by auto-generating code in various languages within supported IDEs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows. This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You’ll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience. By the end of this book, you’ll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently.What you will learn Understand the importance of generative AI-powered assistants in developers' daily work Enable Amazon Q Developer for IDEs and with AWS services to leverage code suggestions Customize Amazon Q Developer to align with organizational coding standards Utilize Amazon Q Developer for code explanation, transformation, and feature development Understand code references and scan for code security issues using Amazon Q Developer Accelerate building solutions and troubleshooting errors on AWS Who this book is for This book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer's features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.
