Python

Cloud Native Python. Build and deploy resilent applications on the cloud using microservices, AWS, Azure and more

Manish Sethi

Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform

Cloud Observability with Azure Monitor. A practical guide to monitoring your Azure infrastructure and applications using industry best practices

José Ángel Fernández, Manuel Lázaro Ramírez

Cloud observability is complex and costly due to the use of hybrid and multi-cloud infrastructure as well as various Azure tools, hampering IT teams’ ability to monitor and analyze issues. The authors distill their years of experience with Microsoft to share the strategic insights and practical skills needed to optimize performance, ensure reliability, and navigate the dynamic landscape of observability on Azure.You’ll get an in-depth understanding of cloud observability and Azure Monitor basics, before getting to grips with the configuration and optimization of data sources and pipelines for effective monitoring. You’ll learn about advanced data analysis techniques using metrics and the Kusto Query Language (KQL) for your logs, design proactive incident response strategies with automated alerts, and visualize reports via dashboards. Using hands-on examples and best practices, you’ll explore the integration of Azure Monitor with Azure Arc and third-party tools, such as Datadog, Elastic Stack, or Dynatrace. You’ll also implement artificial intelligence for IT Operations (AIOps) and secure monitoring for hybrid and multi-cloud environments, aligned with emerging trends.By the end of this book, you’ll be able to develop robust and cost-optimized observability solutions for monitoring your Azure infrastructure and apps using Azure Monitor.

Codeless Deep Learning with KNIME. Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

Kathrin Melcher, Rosaria Silipo

KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.

Coding with ChatGPT and Other LLMs. Navigate LLMs for effective coding, debugging, and AI-driven development

Dr. Vincent Austin Hall

Keeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall—who holds a PhD in machine learning and has extensive experience in licensed software development—this book helps both new and experienced coders to quickly adopt best practices and stay relevant in the field.You’ll learn how to use LLMs such as ChatGPT and Gemini to produce efficient, explainable, and shareable code and discover techniques to maximize the potential of LLMs. The book focuses on integrated development environments (IDEs) and provides tips to avoid pitfalls, such as bias and unexplainable code, to accelerate your coding speed. You’ll master advanced coding applications with LLMs, including refactoring, debugging, and optimization, while examining ethical considerations, biases, and legal implications. You’ll also use cutting-edge tools for code generation, architecting, description, and testing to avoid legal hassles while advancing your career.By the end of this book, you’ll be well-prepared for future innovations in AI-driven software development, with the ability to anticipate emerging LLM technologies and generate ideas that shape the future of development.

Continuous Testing, Quality, Security, and Feedback. Essential strategies and secure practices for DevOps, DevSecOps, and SRE transformations

Marc Hornbeek, Dan Wakeman

Organizations struggle to integrate and execute continuous testing, quality, security, and feedback practices into their DevOps, DevSecOps, and SRE approaches to achieve successful digital transformations. This book addresses these challenges by embedding these critical practices into your software development lifecycle.Beginning with the foundational concepts, the book progresses to practical applications, helping you understand why these practices are crucial in today’s fast-paced software development landscape. You’ll discover continuous strategies to avoid the common pitfalls and streamline the quality, security, and feedback mechanisms within software development processes. You’ll explore planning, discovery, and benchmarking through systematic engineering approaches, tailored to organizational needs. You’ll learn how to select toolchains, integrating AI/ML for resilience, and implement real-world case studies to achieve operational excellence. You’ll learn how to create strategic roadmaps, aligned with digital transformation goals, and measure outcomes recognized by DORA. You’ll explore emerging trends that are reshaping continuous practices in software development.By the end of this book, you’ll have the knowledge and skills to drive continuous improvement across the software development lifecycle.

Crafting Test-Driven Software with Python. Write test suites that scale with your applications' needs and complexity using Python and PyTest

Alessandro Molina

Test-driven development (TDD) is a set of best practices that helps developers to build more scalable software and is used to increase the robustness of software by using automatic tests. This book shows you how to apply TDD practices effectively in Python projects.You’ll begin by learning about built-in unit tests and Mocks before covering rich frameworks like PyTest and web-based libraries such as WebTest and Robot Framework, discovering how Python allows you to embrace all modern testing practices with ease. Moving on, you’ll find out how to design tests and balance them with new feature development and learn how to create a complete test suite with PyTest. The book helps you adopt a hands-on approach to implementing TDD and associated methodologies that will have you up and running and make you more productive in no time. With the help of step-by-step explanations of essential concepts and practical examples, you’ll explore automatic tests and TDD best practices and get to grips with the methodologies and tools available in Python for creating effective and robust applications.By the end of this Python book, you will be able to write reliable test suites in Python to ensure the long-term resilience of your application using the range of libraries offered by Python for testing and development.

Creating Actionable Insights Using CRM Analytics. Learn how to build insightful and actionable data analytics dashboards

Mark Tossell

CRM Analytics, formerly known as Tableau CRM and Einstein Analytics, is a powerful and versatile data analytics platform that enables organizations to extract, combine, transform, and visualize their data to create valuable business insights.Creating Actionable Insights Using CRM Analytics provides a hands-on approach to CRM Analytics implementation and associated methodologies that will have you up and running and productive in no time. The book provides you with detailed explanations of essential concepts to help you to gain confidence and become competent in using the CRM Analytics platform for data extraction, combination, transformation, visualization, and action. As you make progress, you'll understand what CRM Analytics is and where it provides business value. You'll also learn how to bring your data together in CRM Analytics, build datasets and lenses for data analysis, create effective analytics dashboards for visualization and consumption by end users, and build dashboard actions that take the user from data to insight to action with ease.By the end of this book, you'll be able to solve business problems using CRM Analytics and design, build, test, and deploy analytics dashboards efficiently.

Cryptography Algorithms. A guide to algorithms in blockchain, quantum cryptography, zero-knowledge protocols, and homomorphic encryption

Massimo Bertaccini

Cryptography Algorithms is designed to help you get up and running with modern cryptography algorithms. You'll not only explore old and modern security practices but also discover practical examples of implementing them effectively.The book starts with an overview of cryptography, exploring key concepts including popular classical symmetric and asymmetric algorithms, protocol standards, and more. You'll also cover everything from building crypto codes to breaking them. In addition to this, the book will help you to understand the difference between various types of digital signatures. As you advance, you will become well-versed with the new-age cryptography algorithms and protocols such as public and private key cryptography, zero-knowledge protocols, elliptic curves, quantum cryptography, and homomorphic encryption. Finally, you'll be able to apply the knowledge you've gained with the help of practical examples and use cases.By the end of this cryptography book, you will be well-versed with modern cryptography and be able to effectively apply it to security applications.