Wydawca: Packt Publishing
Emmanouil Gkatziouras, Chris Jenkins, Rom Adams, Chen...
Securing Secrets in containerized apps poses a significant challenge for Kubernetes IT professionals. This book tackles the critical task of safeguarding sensitive data, addressing the limitations of Kubernetes encryption, and establishing a robust Secrets management system for heightened security for Kubernetes.Starting with the fundamental Kubernetes architecture principles and how they apply to the design of Secrets management, this book delves into advanced Kubernetes concepts such as hands-on security, compliance, risk mitigation, disaster recovery, and backup strategies. With the help of practical, real-world guidance, you’ll learn how to mitigate risks and establish robust Secrets management as you explore different types of external secret stores, configure them in Kubernetes, and integrate them with existing Secrets management solutions.Further, you'll design, implement, and operate a secure method of managing sensitive payload by leveraging real use cases in an iterative process to enhance skills, practices, and analytical thinking, progressively strengthening the security posture with each solution.By the end of this book, you'll have a rock-solid Secrets management solution to run your business-critical applications in a hybrid multi-cloud scenario, addressing operational risks, compliance, and controls.
KVM Virtualization Cookbook. Learn how to use KVM effectively in production
Konstantin Ivanov
Virtualization technologies such as KVM allow for better control over the available server resources, by deploying multiple virtual instances on the same physical host, or clusters of compute resources. With KVM it is possible to run various workloads in isolation with the hypervisor layer providing better tenant isolation and higher degree of security. This book will provide a deep dive into deploying KVM virtual machines using qemu and libvirt and will demonstrate practical examples on how to run, scale, monitor, migrate and backup such instances. You will also discover real production ready recipes on deploying KVM instances with OpenStack and how to programatically manage the life cycle of KVM virtual machines using Python. You will learn numerous tips and techniques which will help you deploy & plan the KVM infrastructure. Next, you will be introduced to the working of libvirt libraries and the iPython development environment. Finally, you will be able to tune your Linux kernel for high throughput and better performance. By the end of this book, you will gain all the knowledge needed to be an expert in working with the KVM virtualization infrastructure.
LangChain in your Pocket. LangChain Essentials: From Basic Concepts to Advanced Applications
Mehul Gupta
LangChain in your Pocket offers a detailed exploration into the LangChain framework, designed to enhance your skills in developing sophisticated language understanding models and applications. This book begins with the basics, introducing you to the fundamental concepts of LangChain through a simple Hello World example. As you progress, you'll delve into various LangChain modules, learning how to create agents, manage memory, and utilize output parsers effectively.The journey continues as you explore the RAG Framework, vector databases, and their applications in natural language processing, providing you with the tools to tackle common NLP problems efficiently. The book also addresses critical aspects of working with large language models (LLMs), such as prompt engineering, handling hallucinations, and evaluating model outputs. Advanced topics like autonomous AI agents and the integration of LangSmith and LangServe are covered, giving you a holistic view of what you can achieve with LangChain.By the end of this book, you will not only understand the technical aspects of LangChain but also how to apply these principles in real-world scenarios, making it an essential resource for anyone looking to advance their capabilities in AI and language processing.
Martin Bean
This book is intended for PHP web developers who have an interest in Laravel and who know the basics of the framework in theory, but don't really know how to use it in practice. No experience of using frameworks is required, but it is assumed you are at least familiar with building dynamic websites in PHP already.
Terry Matula, Alfred Nutile
Laravel is a prominent member of a new generation of web frameworks. It is one of the most popular PHP frameworks and is also free and an open source. Laravel 5 is a substantial upgrade with a lot of new toys, at the same time retaining the features that made Laravel wildly successful. It comes with plenty of architectural as well as design-based changes.The book is a blend of numerous recipes that will give you all the necessary tips you need to build an application. It starts with basic installation and configuration tasks and will get you up-and-running in no time. You will learn to create and customize your PHP app and tweak and re-design your existing apps for better performance. You will learn to implement practical recipes to utilize Laravel’s modular structure, the latest method injection, route caching, and interfacing techniques to create responsive modern-day PHP apps that stand on their own against other apps. Efficient testing and deploying techniques will make you more confident with your Laravel skills as you move ahead with this book.Towards the end of the book, you will understand a number of add-ons and new features essential to finalize your application to make it ready for subscriptions. You will be empowered to get your application out to the world.
Terry Matula
When creating a web application, there are many PHP frameworks from which to choose. Some are very easy to set up, and some have a much steeper learning curve. Laravel offers both paths. You can do a quick installation and have your app up-and-running in no time, or you can use Laravel's extensibility to create an advanced and fully-featured app.Laravel Application Development Cookbook provides you with working code examples for many of the common problems that web developers face. In the process, it will also allow both new and existing Laravel users to expand their knowledge of the framework.This book will walk you through all aspects of Laravel development. It begins with basic set up and installation procedures, and continues through more advanced use cases. You will also learn about all the helpful features that Laravel provides to make your development quick and easy. For more advanced needs, you will also see how to utilize Laravel's authentication features and how to create a RESTful API.In the Laravel Application Development Cookbook, you will learn everything you need to know about a great PHP framework, with working code that will get you up-and-running in no time.
Miquel Noguer i Alonso
Large language models are revolutionizing finance from market analysis to compliance automation but applying them in practice can be challenging. LLMs in Finance is a step-by-step guide that demystifies these powerful models and shows you how to implement them in real financial projects. You'll begin with the fundamentals of how LLMs work, including the transformer architecture, prompt engineering, and fine-tuning for financial data. Next, you'll build applications: intelligent agents for trading; tools for banking tasks like credit scoring and fraud detection; and automated solutions for risk management and regulatory compliance. To deploy these solutions, you'll learn how to scale LLM implementations, from choosing the right hardware to adopting effective cloud strategies. You'll also explore advanced methods to improve model performance, including reinforcement learning for fine-tuning. Finally, learn how to address AI bias and ensure your LLM solutions comply with ethical and regulatory requirements. Real-world case studies illustrate how financial organizations are leveraging LLMs in trading systems, customer service chatbots, and more. By the end of the book, you'll have the expertise to build LLM-powered applications and pick up on trends such as multimodal AI
Luca Massaron, Alberto Boschetti, Bastiaan Sjardin
Large Python machine learning projects involve new problems associated with specialized machine learning architectures and designs that many data scientists have yet to tackle. But finding algorithms and designing and building platforms that deal with large sets of data is a growing need. Data scientists have to manage and maintain increasingly complex data projects, and with the rise of big data comes an increasing demand for computational and algorithmic efficiency. Large Scale Machine Learning with Python uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy. Dive into scalable machine learning and the three forms of scalability. Speed up algorithms that can be used on a desktop computer with tips on parallelization and memory allocation. Get to grips with new algorithms that are specifically designed for large projects and can handle bigger files, and learn about machine learning in big data environments. We will also cover the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.