The Definitive Guide to AWS Application Integration


Book Description

Build reliable, asynchronous, and distributed applications using message queuing and task orchestration capabilities of Amazon Web Services (AWS) Application Integration. This book prepares you to build distributed applications and administrators, and manage queues, workflows, and state machines. You'll start by reviewing key AWS prerequisite services such as EC2, Lambda, S3, DynamoDB, CloudWatch, and IAM. Simple Queue Service (SQS) and SNS Simple Notification Service (SNS) are then covered to show how applications interact with each other in a reliable and resilient fashion. Next, workflow building with (Simple Workflow Service (SWF) for orchestration of tasks is explained and in the final chapter learn the techniques for building a state using Step Functions, Simple Workflow Service along with Flow Framework. The book illustrates all the concepts using numerous examples that work with SDK, CLI, and Console. Most of the code examples are in Java, followed by Python and JavaScript. What You Will LearnUnderstand the important prerequisites of AWS, such as EC2, Lambda, S3, and DynamoDB Work with SQS, SNS, and SWS functionsReview Step functions Who This Book Is For AWS developers and software developers proficient in Java, Python and JavaScript.




The Definitive Guide to AWS Application Integration


Book Description

Build reliable, asynchronous, and distributed applications using message queuing and task orchestration capabilities of Amazon Web Services (AWS) Application Integration. This book prepares you to build distributed applications and administrators, and manage queues, workflows, and state machines. You'll start by reviewing key AWS prerequisite services such as EC2, Lambda, S3, DynamoDB, CloudWatch, and IAM. Simple Queue Service (SQS) and SNS Simple Notification Service (SNS) are then covered to show how applications interact with each other in a reliable and resilient fashion. Next, workflow building with (Simple Workflow Service (SWF) for orchestration of tasks is explained and in the final chapter learn the techniques for building a state using Step Functions, Simple Workflow Service along with Flow Framework. The book illustrates all the concepts using numerous examples that work with SDK, CLI, and Console. Most of the code examples are in Java, followed by Python and JavaScript. What You Will LearnUnderstand the important prerequisites of AWS, such as EC2, Lambda, S3, and DynamoDB Work with SQS, SNS, and SWS functionsReview Step functions Who This Book Is For AWS developers and software developers proficient in Java, Python and JavaScript.




Amazon Web Services: the Definitive Guide for Beginners and Advanced Users


Book Description

Amazon Web Services: A Comprehensive Guide for Beginners and Advanced Users is your go-to companion for learning and mastering AWS. It presents 10 easy-to-read chapters that build a foundation for cloud computing while also equipping readers with the skills necessary to use AWS for commercial projects. Readers will learn how to use AWS cloud computing services for seamless integrations, effective monitoring, and optimizing cloud-based web applications. What you will learn from this guide: 1. Identity and Access Management in AWS: Learn about IAM roles, security of the root account, and password policies, ensuring a robust foundation in access management. 2. Amazon EC2 Instance: Explore the different types of EC2 instances, pricing strategies, and hands-on experiences to launch, manage, and terminate EC2 instances effectively. This knowledge will help to make informed choices about pricing strategies. 3. Storage Options and Solutions: A detailed examination of storage options within Amazon EC2 instances. Understanding Amazon Elastic Block Store (EBS), Amazon Elastic File Storage (EFS), and more, will enhance your ability to handle data storage efficiently. 4. Load Balancing and Auto Scaling: Learn about different types of load balancers and how auto-scaling groups operate, to master the art of managing varying workloads effectively. 5. Amazon Simple Storage Service (S3): Understand S3 concepts such as buckets, objects, versioning, storage classes, and practical applications. 6. AWS Databases and Analytics: Gain insights into modern databases, AWS cloud databases, and analytics services such as Amazon Quicksight, AWS Glue, and Amazon Redshift. 7. Compute Services and Integrations: Understand the workings of Docker, virtual machines, and various compute services offered by AWS, including AWS Lambda and Amazon Lightsail, Amazon MQ and Amazon SQS. 8. Cloud Monitoring: Understand how to set up alarms, analyze metrics, and ensure the efficient monitoring of your cloud environment using Amazon CloudWatch and CloudTrail. Key Features: Comprehensive Introduction to Cloud Computing and AWS Guides readers to the complete set of features in AWS Easy-to-understand language and presentation with diagrams and navigation guides References for further reading Whether you're a student diving into cloud specialization as part of your academic curriculum or a professional seeking to enhance your skills, this guide provides a solid foundation for learning the potential of the AWS suite of applications to deploy cloud computing projects.




Amazon Redshift: The Definitive Guide


Book Description

Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value




Computing, Communication and Learning


Book Description

This volume constitutes the refereed proceedings of the First International Conference on Computing, Communication and Learning, CoCoLe 2022, held in Warangal, India, in October 2022. The 25 full papers and 1 short paper presented were carefully reviewed and selected from 117 submissions. The CoCoLe conference focuses on three broad areas of computer science and other allied branches, namely computing, communication, and learning.




The Definitive Guide to AWS Infrastructure Automation


Book Description

Discover the pillars of AWS infrastructure automation, starting with API-driven infrastructure concepts and its immediate benefits such as increased agility, automation of the infrastructure life cycle, and flexibility in experimenting with new architectures. With this base established, the book discusses infrastructure-as-code concepts in a general form, establishing principled outcomes such as security and reproducibility. Inescapably, we delve into how these concepts enable and underpin the DevOps movement. The Definitive Guide to AWS Infrastructure Automation begins by discussing services and tools that enable infrastructure-as-code solutions; first stop: AWS's CloudFormation service. You’ll then cover the ever-expanding ecosystem of tooling emerging in this space, including CloudFormation wrappers such as Troposphere and orchestrators such as Sceptre, to completely independent third-party tools such as Terraform and Pulumi. As a bonus, you’ll also work with AWS' newly-released CDK (Cloud Development Kit). You’ll then look at how to implement modular, robust, and extensible solutions across a few examples -- in the process building out each solution with several different tools to compare and contrast the strengths and weaknesses of each. By the end of the journey, you will have gained a wide knowledge of both the AWS-provided and third-party ecosystem of infrastructure-as-code/provisioning tools, and the strengths and weaknesses of each. You’ll possess a mental framework for how to craft an infrastructure-as-code solution to solve future problems based on examples discussed throughout the book. You’ll also have a demonstrable understanding of the hands-on operation of each tool, situational appropriateness of each tool, and how to leverage the tool day to day. What You Will Learn Discover the technological and organizational benefits to infrastructure-as-code solutions Examine the overall landscape of infrastructure-as-code tooling and solutions available to consumers of AWS services See the strengths and weaknesses of these tools relative to one another as examined through hands-on implementation of several solutions Gain hands-on experience, best practices, and tips and tricks learned through several years’ real-world experience delivering solutions using these very tools in a wide variety of scenarios Engineer solid solutions that leave room for new requirements and changes without requiring needless refactoring Who This Book Is For DevOps engineers, cloud engineers and architects focused on the AWS ecosystem, software engineers/developers working within the AWS ecosystem, and engineering leaders looking for best practices.




Information Technology in Biomedicine


Book Description

This book presents a comprehensive study in the field of advances in medical data science and contains carefully selected articles contributed by experts of information technology. Continuous growth of the amount of medical information and the variety of multimodal content necessitates the demand for a fast and reliable technology able to process data and deliver results in a user-friendly manner at the time and place the information is needed. Computational approaches for understanding human complexity, AI-powered applications in image and signal processing, bioinformatics, sound and motion as activity stimulus, joint activities in biomedical engineering and physiotherapy, disorder in children, selected comparative studies give new meaning to optimization of the functional requirements of the healthcare system for the benefit of the patients. It is an interdisciplinary collection of papers that have both theoretical and applied dimensions. It includes the following research areas: Computational methods for understanding human complexity Image and signal analysis Multidimensional medical data analysis Sound and motion Joint activities in biomedical engineering and physiotherapy This book is a great reference tool for scientists who deal with problems of designing and implementing information processing tools employed in systems that assist the clinicians, radiologists, and physiotherapists in patient diagnosis and treatment. It also serves students in exploring innovations in quantitative medical data analysis, data mining, and artificial intelligence.




Apache Iceberg: The Definitive Guide


Book Description

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool—a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.




The Definitive Guide to Data Integration


Book Description

Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.




Amazon DynamoDB - The Definitive Guide


Book Description

Harness the potential and scalability of DynamoDB to effortlessly construct resilient, low-latency databases Key Features Discover how DynamoDB works behind the scenes to make the most of its features Learn how to keep latency and costs minimal even when scaling up Integrate DynamoDB with other AWS services to create a full data analytics system Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis book will help you master Amazon DynamoDB, the fully managed, serverless, NoSQL database service designed for high performance at any scale. Authored by Aman Dhingra, senior DynamoDB specialist solutions architect at AWS, and Mike Mackay, former senior NoSQL specialist solutions architect at AWS, this guide draws on their expertise to equip you with the knowledge and skills needed to harness DynamoDB's full potential. This book not only introduces you to DynamoDB's core features and real-world applications, but also provides in-depth guidance on transitioning from traditional relational databases to the NoSQL world. You'll learn essential data modeling techniques, such as vertical partitioning, and explore the nuances of DynamoDB's indexing capabilities, capacity modes, and consistency models. The chapters also help you gain a solid understanding of advanced topics such as enhanced analytical patterns, implementing caching with DynamoDB Accelerator (DAX), and integrating DynamoDB with other AWS services to optimize your data strategies. By the end of this book, you’ll be able to design, build, and deliver low-latency, high-throughput DynamoDB solutions, driving new levels of efficiency and performance for your applications.What you will learn Master key-value data modeling in DynamoDB for efficiency Transition from RDBMSs to NoSQL with optimized strategies Implement read consistency and ACID transactions effectively Explore vertical partitioning for specific data access patterns Optimize data retrieval using secondary indexes in DynamoDB Manage capacity modes, backup strategies, and core components Enhance DynamoDB with caching, analytics, and global tables Evaluate and design your DynamoDB migration strategy Who this book is for This book is for software architects designing scalable systems, developers optimizing performance with DynamoDB, and engineering managers guiding decision-making. Data engineers will learn to integrate DynamoDB into workflows, while product owners will explore its innovative capabilities. DBAs transitioning to NoSQL will find valuable insights on DynamoDB and RDBMS integration. Basic knowledge of software engineering, Python, and cloud computing is helpful. Hands-on AWS or DynamoDB experience is beneficial but not required.