Swift For Devops
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Swift for DevOps
⚙️ Swift for DevOps: Automating Development Workflows 🚀 Unlock the Power of Swift DevOps to Streamline Your Development Process Are you a Swift developer eager to master DevOps for IT infrastructure and elevate your software delivery? Whether you’re just beginning to learn Swift programming or an experienced Apple Swift developer, this book teaches you how to use DevOps principles with Swift to automate and optimize your development workflows. Swift for DevOps guides you through everything from Swift coding language essentials to advanced automation techniques. Discover how Swift for backend and Swift iOS development can power continuous integration, automated testing, and infrastructure management—making your apps more reliable and your deployments seamless. 💡 What You’ll Learn Inside: ✅ Understanding Swift DevOps Explore the fundamentals of Swift DevOps, and learn how to work in DevOps environments using the Swift programming language. ✅ Automating CI/CD Pipelines with Swift Master the tools and frameworks that integrate with Swift for continuous integration and deployment, reducing manual errors and speeding up releases. ✅ Automated Testing with Swift Build robust test suites and automate testing processes to ensure quality in your Swift iOS and backend apps. ✅ Infrastructure as Code with Swift Learn how to write and manage infrastructure scripts, enabling scalable and repeatable environments with Swift-powered automation. ✅ Hands-On Swift Coding Playground Practice your Swift skills with real-world DevOps examples using interactive Swift coding playgrounds. 🎯 Who Should Read This Book? Developers looking to combine Swift for app development with DevOps automation Beginners wanting a comprehensive Swift programming tutorial focused on DevOps Professionals curious about how to use DevOps practices with Swift for backend and iOS Teams aiming to streamline workflows and boost productivity using Swift coding language 🌟 Why This Book is Essential Unlike generic coding guides, Swift for DevOps merges the power of the Swift computer language with modern DevOps practices. Whether you’re improving your iOS app deployment or automating backend workflows, this book empowers you with skills that make you a true Swift dev and automation expert. 🛒 Take control of your software pipeline with Swift DevOps! Order Swift for DevOps: Automating Development Workflows today and start building faster, smarter, and more reliable applications. 👉 Click “Buy Now” to master Swift-powered DevOps automation!
Swift in the Cloud
Author: Leigh Williamson
language: en
Publisher: John Wiley & Sons
Release Date: 2017-08-04
Write and run Swift language programs in the Cloud Written by the team of developers that has helped bring the Swift language to Cloud computing, this is the definitive guide to writing and running Swift language programs for cloud environment. In Swift in the Cloud, you'll find full coverage of all aspects of creating and running Swift language applications in Cloud computing environments, complete with examples of real code that you can start running and experimenting with today. Since Apple introduced the Swift language in 2014, it has become one of the most rapidly adopted computer programming languages in history—and now you too can start benefitting from using the same programming language for all components of a scalable, robust business software solution. Create server applications using Swift and run them on pay-as-you-go cloud infrastructure Quickly write and test Swift code snippets in your own cloud sandbox Use Docker containers to deploy Swift applications into multiple cloud environments without having to change code Grasp the elements and structure of the Swift.org open technology project Find out how to avoid the complexities of runtime configuration by using Cloud Foundry buildpacks for Swift Build high performing web applications and REST APIs with an open source Swift based web server framework Scale up your cloud services by running Swift modules in an asynchronous, open source, 'serverless' cloud environment Whether you are already using Swift to build mobile applications or a seasoned web developer, Swift in the Cloud will help you leverage server-side Swift to power your next generation of applications.
LLM Engineer's Handbook
Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Build and refine LLMs step by step, covering data preparation, RAG, and fine-tuning Learn essential skills for deploying and monitoring LLMs, ensuring optimal performance in production Utilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applications Book DescriptionArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems. Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects. By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.What you will learn Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine it with the help of hands-on examples Get started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring Perform supervised fine-tuning and LLM evaluation Deploy end-to-end LLM solutions using AWS and other tools Design scalable and modularLLM systems Learn about RAG applications by building a feature and inference pipeline Who this book is for This book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios