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Podcasts
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.
ASP.NET has been the preferred choice of web developers for a long time. With ASP.NET Core 3, Microsoft has made internal changes to the framework along with introducing new additions that will change the way you approach web development. This second edition has been thoroughly updated to help you make the most of the latest features in the framework, right from gRPC and conventions to Blazor, which has a new chapter dedicated to it.You’ll begin with an overview of the essential topics, exploring the Model-View-Controller (MVC) pattern, various platforms, dependencies, and frameworks. Next, you’ll learn how to set up and configure the MVC environment, before delving into advanced routing options. As you advance, you’ll get to grips with controllers and actions to process requests, and later understand how to create HTML inputs for models. Moving on, you'll discover the essential aspects of syntax and processes when working with Razor. You'll also get up to speed with client-side development and explore the testing, logging, scalability, and security aspects of ASP.NET Core. Finally, you'll learn how to deploy ASP.NET Core to several environments, such as Azure, Amazon Web Services (AWS), and Docker.By the end of the book, you’ll be well versed in development in ASP.NET Core and will have a deep understanding of how to interact with the framework and work cross-platform.
This book is a comprehensive guide to the Streamlit open-source Python library and simplifying the process of creating web applications. Through hands-on guidance and realistic examples, you’ll progress from crafting simple to sophisticated web applications from scratch. This book covers everything from understanding Streamlit's central principles, modules, basic features, and widgets to advanced skills such as dealing with databases, hashes, sessions, and multipages.Starting with fundamental concepts like operation systems virtualization, IDEs, development environments, widgets, scripting, and the anatomy of web apps, the initial chapters set the groundwork. You’ll then apply this knowledge to develop some real web apps, gradually advancing to more complex apps, incorporating features like natural language processing (NLP), computer vision, dashboards with interactive charts, file uploading, and much more. The book concludes by delving into the implementation of advanced skills and deployment techniques.By the end of this book, you’ll have transformed into a proficient developer, equipped with advanced skills for handling databases, implementing secure login processes, managing session states, creating multipage applications, and seamlessly deploying them on the cloud.
Python is a multi-domain, interpreted programming language that is easy to learn and implement. With its wide support for frameworks to develop GUIs, you can build interactive and beautiful GUI-based applications easily using Python. This third edition of Python GUI Programming Cookbook follows a task-based approach to help you create effective GUIs with the smallest amount of code. Every recipe in this book builds upon the last to create an entire, real-life GUI application. These recipes also help you solve problems that you might encounter while developing GUIs. This book mainly focuses on using Python’s built-in tkinter GUI framework. You'll learn how to create GUIs in Python using simple programming styles and object-oriented programming (OOP). As you add more widgets and expand your GUI, you will learn how to connect to networks, databases, and graphical libraries that greatly enhance the functionality of your GUI. You’ll also learn how to use threading to ensure that your GUI doesn't become unresponsive. Toward the end, you’ll learn about the versatile PyQt GUI framework, which comes along with its own visual editor that allows you to design GUIs using drag and drop features. By the end of the book, you’ll be an expert in designing Python GUIs and be able to develop a variety of GUI applications with ease.
Just because you know how to swing a hammer doesn't mean you know how to build a house. Now that you've learned how to use QlikView, it's time to learn how to develop meaningful QlikView applications that deliver what your business users need.You will explore the requirements and the data from several business departments in order to deliver the most amazing analysis and data visualizations. In doing so, you will practice using advanced QlikView functions, chart object property options, and extensions to solve real-worldchallenges.
Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
Kieran Kavanagh, Priyanka Vergadia
Most companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies.You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process.By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.