Modern Network Observability. A hands-on approach using open source tools such as Telegraf, Prometheus, and Grafana

David Flores, Christian Adell, Josh VanDeraa, Eric Chou, ...

As modern IT services and software architectures such as microservices rely increasingly on network performance, the relevance of networks has never been greater. Network observability has emerged as a critical evolution of traditional monitoring, providing the deep visibility needed to manage today’s complex, dynamic environments. In Modern Network Observability, authors David Flores, Christian Adell, and Josh VanDeraa share their extensive experience to guide you through building and deploying a flexible observability stack using open-source tools.This book begins by addressing the limitations of monolithic monitoring solutions, showing you how to transform them into a composable, flexible observability stack. Through practical implementations, you’ll learn how to collect, normalize, and analyze network data from diverse sources, build intuitive dashboards, and set up actionable alerts that help you stay ahead of potential issues. Later, you’ll cover advanced topics, such as integrating observability data into your network automation strategy, ensuring your network operations align with business objectives.By the end of this book, you'll be able to proactively manage your network, minimize downtime, and ensure resilient, efficient, and future-proof operations.

Accelerate Deep Learning Workloads with Amazon SageMaker. Train, deploy, and scale deep learning models effectively using Amazon SageMaker

Vadim Dabravolski

Over the past 10 years, deep learning has grown from being an academic research field to seeing wide-scale adoption across multiple industries. Deep learning models demonstrate excellent results on a wide range of practical tasks, underpinning emerging fields such as virtual assistants, autonomous driving, and robotics. In this book, you will learn about the practical aspects of designing, building, and optimizing deep learning workloads on Amazon SageMaker. The book also provides end-to-end implementation examples for popular deep-learning tasks, such as computer vision and natural language processing. You will begin by exploring key Amazon SageMaker capabilities in the context of deep learning. Then, you will explore in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMaker. You will learn how to train and serve deep learning models using popular open-source frameworks and understand the hardware and software options available for you on Amazon SageMaker. The book also covers various optimizations technique to improve the performance and cost characteristics of your deep learning workloads.By the end of this book, you will be fluent in the software and hardware aspects of running deep learning workloads using Amazon SageMaker.

Entity Framework Core Cookbook. Transactions, stored procedures, query libraries, and more - Second Edition

Ricardo Peres

Entity Framework is a highly recommended Object Relation Mapping tool used to build complex systems. In order to survive in this growing market, the knowledge of a framework that helps provide easy access to databases, that is, Entity Framework has become a necessity. This book will provide .NET developers with this knowledge and guide them through working efficiently with data using Entity Framework Core. You will start off by learning how to efficiently use Entity Framework in practical situations. You will gain a deep understanding of mapping properties and find out how to handle validation in Entity Framework. The book will then explain how to work with transactions and stored procedures along with improving Entity Framework using query libraries. Moving on, you will learn to improve complex query scenarios and implement transaction and concurrency control. You will then be taught to improve and develop Entity Framework in complex business scenarios. With the concluding chapter on performance and scalability, this book will get you ready to use Entity Framework proficiently.

Couchbase Essentials. Harness the power of Couchbase to build flexible and scalable applications

John C Zablocki, John Zablocki

Learning Phalcon PHP. Learn Phalcon interactively and build high-performance web applications

Calin Rada, Ioan C Rada

Hands-On Design Patterns with C++. Solve common C++ problems with modern design patterns and build robust applications - Second Edition

Fedor G. Pikus

C++ is a general-purpose programming language designed for efficiency, performance, and flexibility. Design patterns are commonly accepted solutions to well-recognized design problems. In essence, they are a library of reusable components, only for software architecture, and not for a concrete implementation. This book helps you focus on the design patterns that naturally adapt to your needs, and on the patterns that uniquely benefit from the features of C++. Armed with the knowledge of these patterns, you’ll spend less time searching for solutions to common problems and tackle challenges with the solutions developed from experience. You’ll also explore that design patterns are a concise and efficient way to communicate, as patterns are a familiar and recognizable solution to a specific problem and can convey a considerable amount of information with a single line of code. By the end of this book, you’ll have a deep understanding of how to use design patterns to write maintainable, robust, and reusable software.

Data Wrangling on AWS. Clean and organize complex data for analysis

Navnit Shukla, Sankar M, Sampat Palani

Data wrangling is the process of cleaning, transforming, and organizing raw, messy, or unstructured data into a structured format. It involves processes such as data cleaning, data integration, data transformation, and data enrichment to ensure that the data is accurate, consistent, and suitable for analysis. Data Wrangling on AWS equips you with the knowledge to reap the full potential of AWS data wrangling tools.First, you’ll be introduced to data wrangling on AWS and will be familiarized with data wrangling services available in AWS. You’ll understand how to work with AWS Glue DataBrew, AWS data wrangler, and AWS Sagemaker. Next, you’ll discover other AWS services like Amazon S3, Redshift, Athena, and Quicksight. Additionally, you’ll explore advanced topics such as performing Pandas data operation with AWS data wrangler, optimizing ML data with AWS SageMaker, building the data warehouse with Glue DataBrew, along with security and monitoring aspects.By the end of this book, you’ll be well-equipped to perform data wrangling using AWS services.

Introduction to R for Business Intelligence. Profit optimization using data mining, data analysis, and Business Intelligence

Jay Gendron

Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards.After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.