Book + Content Update Program SQL Server 2016 High Availability Unleashed provides start-to-finish coverage of SQL Server’s powerful high availability (HA) solutions for your traditional on-premise databases, cloud-based databases (Azure or AWS), hybrid databases (on-premise coupled with the cloud), and your emerging Big Data solutions. This complete guide introduces an easy-to-follow, formal HA methodology that has been refined over the past several years and helps you identity the right HA solution for your needs. There is also additional coverage of both disaster recovery and business continuity architectures and considerations. You are provided with step-by-step guides, examples, and sample code to help you set up, manage, and administer these highly available solutions. All examples are based on existing production deployments at major Fortune 500 companies around the globe. This book is for all intermediate-to-advanced SQL Server and Big Data professionals, but is also organized so that the first few chapters are great foundation reading for CIOs, CTOs, and even some tech-savvy CFOs. Learn a formal, high availability methodology for understanding and selecting the right HA solution for your needs Deep dive into Microsoft Cluster Services Use selective data replication topologies Explore thorough details on AlwaysOn and availability groups Learn about HA options with log shipping and database mirroring/ snapshots Get details on Microsoft Azure for Big Data and Azure SQL Explore business continuity and disaster recovery Learn about on-premise, cloud, and hybrid deployments Provide all types of database needs, including online transaction processing, data warehouse and business intelligence, and Big Data Explore the future of HA and disaster recovery In addition, this book is part of InformIT’s exciting Content Update Program, which provides content updates for major technology improvements! As significant updates are made to SQL Server, sections of this book will be updated or new sections will be added to match the updates to the technologies. As updates become available, they will be delivered to you via a free Web Edition of this book, which can be accessed with any Internet connection. To learn more, visit informit.com/cup. How to access the Web Edition: Follow the instructions inside to learn how to register your book to access the FREE Web Edition. * The companion material is not available with the online edition on O'Reilly Learning

This book introduces you to the world of Big Data processing using Apache Spark and Python. You will learn to set up and run Spark on different systems, process massive datasets, and create solutions to real-world Big Data challenges with over 15 hands-on examples included. What this Book will help me do Understand the basics of Apache Spark and its ecosystem. Learn how to process large datasets with Spark RDDs using Python. Implement machine learning models with Spark's MLlib library. Master real-time data processing with Spark Streaming modules. Deploy and run Spark jobs on cloud clusters using AWS EMR. Author(s) Frank Kane spent 9 years working at Amazon and IMDb, handling and solving real-world machine learning and Big Data problems. Today, as an instructional designer and educator, he brings his wealth of experience to learners around the globe by creating accessible, practical learning resources. His teaching is clear, engaging, and designed to prepare students for real-world applications. Who is it for? This book is ideal for data scientists or data analysts seeking to delve into Big Data processing with Apache Spark. Readers who have foundational knowledge of Python, as well as some understanding of data processing principles, will find this book useful to sharpen their skills further. It is designed for those eager to learn the practical applications of Big Data tools in today's industry environments. By the end of this book, you should feel confident tackling Big Data challenges using Spark and Python.

Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company's needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions

Effective Business Intelligence with QuickSight introduces you to Amazon QuickSight, a modern BI tool that enables interactive visualizations powered by the cloud. With comprehensive tutorials, you'll master how to load, prepare, and visualize your data for actionable insights. This book provides real-world examples to showcase how QuickSight integrates into the AWS ecosystem. What this Book will help me do Understand how to effectively use Amazon QuickSight for business intelligence. Learn how to connect QuickSight to data sources like S3, RDS, and more. Create interactive dashboards and visualizations with QuickSight tools. Gain expertise in managing users, permissions, and data security in QuickSight. Execute a real-world big data project using AWS Data Lakes and QuickSight. Author(s) None Nadipalli is a seasoned data architect with extensive experience in cloud computing and business intelligence. With expertise in the AWS ecosystem, she has worked on numerous large-scale data analytics projects. Her writing focuses on providing practical knowledge through easy-to-follow examples and actionable insights. Who is it for? This book is ideal for business intelligence architects, developers, and IT executives seeking to leverage Amazon QuickSight. It is suited for readers with foundational knowledge of AWS who want to enhance their capabilities in BI and data visualization. If your goal is to modernize your business intelligence systems and explore advanced analytics, this book is perfect for you.

In this episode, we dive deep on a 1988 classic: Tom Hanks, under the direction of Penny Marshall, was a 12-year-old in a 30-year-old's body... Actually, that's a different "Big" from what we actually cover in this episode. In this instant classic, the star is BigQuery, the director is Google, and Michael Healy, a data scientist from Search Discovery, delivers an Oscar-worthy performance as Zoltar. In under 48 minutes, Michael (Helbling) and Tim drastically increased their understanding of what Google BigQuery is and where it fits in the analytics landscape. If you'd like to do the same, give it a listen! Technologies, books, and sites referenced in this episode were many, including: Google BigQuery and the BigQuery API Libraries, Google Cloud Services, Google Dremel, Apache Drill, Amazon Redshift (AWS), Rambo III (another 1988 movie!), Hadoop, Cloudera, the Observepoint Tag Debugger, Our Mathematical Universe by Max Tegmark, A Brief History of Time by Stephen Hawking, and a video of math savant Scott Flansburg.

Discover how to build a full-featured, interactive web application from scratch using Node.js and MongoDB in this comprehensive guide. You will learn to set up your development environment, create a web server with Express.js, and integrate MongoDB for data persistence. By the end of this book, you will have the knowledge and skills to develop and deploy robust web applications ready for the cloud. What this Book will help me do Set up a Node.js development environment and connect it to MongoDB. Develop a web server using Express.js and write integrated APIs. Implement dynamic HTML pages leveraging the Handlebars template engine. Build efficient and scalable data-driven features using Mongoose ODM. Deploy web applications seamlessly to cloud platforms like Heroku, AWS, or Azure. Author(s) This book was co-authored by experts None Satheesh, None Joseph D'mello, and Jason Krol, who bring years of experience in software development and expertise in modern web technologies. With a focus on practical application and best practices, the authors aim to empower readers to succeed in real-world development projects using the innovative Node.js and MongoDB stack. Who is it for? This book is tailored for developers who have a basic understanding of JavaScript and HTML and wish to advance their web development skills. If you are motivated to learn how to leverage Node.js and MongoDB for full-stack development or are curious about building and deploying complete web applications, this book is ideal for you. It addresses learners from early career to experienced developers looking to strengthen their skills in modern development stacks.

This comprehensive guide introduces you to Amazon's DynamoDB, a NoSQL database designed for high scalability and performance. Using this book, you will learn how to build robust web and mobile applications on DynamoDB and integrate it seamlessly with other AWS services for a complete cloud solution. What this Book will help me do Understand the key design concepts of DynamoDB and leverage its performance and scalability in your projects. Learn best practices for operating and managing DynamoDB tables, including optimizing throughput and designing efficient indexes. Master techniques for securing data in DynamoDB, including encryption and access management approaches. Explore integration strategies with other AWS services such as S3, EMR, and Lambda, to develop complex, real-world applications. Learn cost-effective solutions and tips for managing DynamoDB usage to avoid unnecessary expenses while maximizing resources. Author(s) None Deshpande, an expert in AWS and NoSQL databases, brings years of practical experience and engineering best practices to this book. With a strong focus on clear and actionable insights, Deshpande is dedicated to enabling developers to unlock the full potential of DynamoDB and related services for scalable application development. Who is it for? This book is most suited for developers and architects familiar with AWS who aim to deepen their understanding of DynamoDB. It is ideal for individuals looking to harness NoSQL databases for robust and scalable application solutions. The topics covered range from foundational knowledge to advanced integrations, making the book approachable yet comprehensive for both learners and seasoned practitioners.

In "DynamoDB Applied Design Patterns", you'll dive deep into the effective design patterns that optimize the performance of applications using DynamoDB. Through practical examples and best practices, this guide empowers developers to create scalable, efficient, and robust DynamoDB implementations. What this Book will help me do Master how to design effective data models using DynamoDB's native features such as tables, attributes, and indexes. Learn to utilize DynamoDB features like global and local secondary indexes to optimize performance. Gain in-depth knowledge on managing and querying DynamoDB using AWS services and tools. Integrate DynamoDB seamlessly with AWS services such as Redshift, S3, and MapReduce. Leverage advanced DynamoDB API features to retrieve data efficiently for diverse application use cases. Author(s) Uchit Hamendra Vyas is a highly skilled professional specializing in AWS and cloud computing. With years of experience as a developer and architect, he brings practical insights into designing efficient database solutions. His approachable teaching style makes complex topics clear and accessible. Who is it for? This book is designed for developers working with or interested in using DynamoDB in their projects. It assumes a moderate familiarity with database design and AWS concepts. Readers aiming to enhance their DynamoDB skills and optimize performance will greatly benefit. If you're looking to take your NoSQL database knowledge to the next level, this book is for you.

"Mastering DynamoDB" will guide you through the advanced usage and operational subtleties of DynamoDB, Amazon's fully managed NoSQL database solution. By mastering the topics in this book, readers will unlock the tools to efficiently build scalable and high-performance applications using DynamoDB, leveraging its unique architecture and features. What this Book will help me do Gain a deep understanding of DynamoDB's data model and how it supports scalable performance. Master advanced DynamoDB architecture concepts for reliability and data handling. Learn to integrate DynamoDB securely with other AWS services to build a comprehensive ecosystem. Use tools and libraries to automate processes like autoscaling, testing, and data backups for DynamoDB. Develop mobile and web applications using DynamoDB as a backend, ensuring high availability and speedy operations. Author(s) None Deshpande, the author of "Mastering DynamoDB", is an experienced cloud computing and database professional. With a strong background in AWS technologies and particular expertise in DynamoDB, None brings hands-on knowledge to the forefront. The author is dedicated to making complex concepts accessible and practical for learners, aiding in their professional growth. Who is it for? This book is ideal for developers and IT professionals who want to deepen their expertise in cloud-based NoSQL databases. Readers should ideally have intermediate experience with programming, AWS services, and an interest in enhancing their skills around scalable database systems. Those seeking practical insights for advanced database integration and application development will benefit the most. If you aim to build robust, high-performance applications, "Mastering DynamoDB" is for you.

The "RabbitMQ Cookbook" is a hands-on guide to mastering RabbitMQ, a powerful and versatile message broker enabling efficient communication between distributed applications. Through practical recipes, you will learn the concepts and techniques for building scalable, reliable, and robust messaging systems. What this Book will help me do Implement and optimize RabbitMQ message brokers for distributed systems. Create RabbitMQ integrations with protocols like MQTT and STOMP. Develop scalable and high-availability RabbitMQ cluster solutions. Deploy and manage RabbitMQ in cloud environments like AWS. Extend RabbitMQ functionalities by creating custom plugins in Erlang. Author(s) The authors of "RabbitMQ Cookbook" are seasoned software architects and developers with extensive hands-on experience with RabbitMQ. They have utilized RabbitMQ in real-world projects to provide innovative solutions for scalable distributed systems. Their collaborative approach focuses on breaking down complex topics into actionable, practical lessons that empower readers to develop their skills. Who is it for? This book is perfect for software developers and architects aiming to design scalable and distributed systems. If you have a basic understanding of web, cloud, and multithreading concepts, this book will provide you with valuable tools and techniques to incorporate RabbitMQ effectively into your projects. It bridges the gap between theoretical concepts and practical implementation with detailed examples.

Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS). Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample MapReduce log analysis application. Using code samples and example configurations, you’ll learn how to assemble the building blocks necessary to solve your biggest data analysis problems. Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools

The go-to guidebook for deploying Big Data solutions with Hadoop Today's enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating Hadoop processes in real time are also covered in depth. With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them. The ultimate guide for developers, designers, and architects who need to build and deploy Hadoop applications Covers storing and processing data with various technologies, automating data processing, Hadoop security, and delivering real-time solutions Includes detailed, real-world examples and code-level guidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in the programmer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprise architects and developers need to maximize the power of Hadoop.

Hadoop Beginner's Guide introduces you to the essential concepts and practical applications of Apache Hadoop, one of the leading frameworks for big data processing. You will learn how to set up and use Hadoop to store, manage, and analyze vast amounts of data efficiently. With clear examples and step-by-step instructions, this book is the perfect starting point for beginners. What this Book will help me do Understand the trends leading to the adoption of Hadoop and determine when to use it effectively in your projects. Build and configure Hadoop clusters tailored to your specific needs, enabling efficient data processing. Develop and execute applications on Hadoop using Java and Ruby, with practical examples provided. Leverage Amazon AWS and Elastic MapReduce to deploy Hadoop on the cloud and manage hosted environments. Integrate Hadoop with relational databases using tools like Hive and Sqoop for effective data transfer and querying. Author(s) The author of Hadoop Beginner's Guide is an experienced data engineer with a focus on big data technologies. They have extensive experience deploying Hadoop in various industries and are passionate about making complex systems accessible to newcomers. Their approach combines technical depth with an understanding of the needs of learners, ensuring clarity and relevance throughout the book. Who is it for? This book is designed for professionals who are new to big data processing and want to learn Apache Hadoop from scratch. It is ideal for system administrators, data analysts, and developers with basic programming knowledge in Java or Ruby looking to get started with Hadoop. If you have an interest in leveraging Hadoop for scalable data management and analytics, this book is for you. By the end, you'll gain the confidence and skills to utilize Hadoop effectively in your projects.

Cloud services are just as susceptible to network outages as any other platform. This concise book shows you how to prepare for potentially devastating interruptions by building your own resilient and reliable applications in the public cloud. Guided by engineers from 9apps—an independent provider of Amazon Web Services and Eucalyptus cloud solutions—you’ll learn how to combine AWS with open source tools such as PostgreSQL, MongoDB, and Redis. This isn’t a book on theory. With detailed examples, sample scripts, and solid advice, software engineers with operations experience will learn specific techniques that 9apps routinely uses in its cloud infrastructures. Build cloud applications with the "rip, mix, and burn" approach Get a crash course on Amazon Web Services Learn the top ten tips for surviving outages in the cloud Use elasticsearch to build a dependable NoSQL data store Combine AWS and PostgreSQL to build an RDBMS that scales well Create a highly available document database with MongoDB Replica Set and SimpleDB Augment Redis with AWS to provide backup/restore, failover, and monitoring capabilities Work with CloudFront and Route 53 to safeguard global content delivery

The Complete Guide to Building Cloud Computing Solutions with Amazon SimpleDB Using SimpleDB, any organization can leverage Amazon Web Services (AWS), Amazon’s powerful cloud-based computing platform–and dramatically reduce the cost and resources associated with application infrastructure. Now, for the first time, there’s a complete developer’s guide to building production solutions with Amazon SimpleDB. Pioneering SimpleDB developer Mocky Habeeb brings together all the hard-to-find information you need to succeed. Mocky tours the SimpleDB platform and APIs, explains their essential characteristics and tradeoffs, and helps you determine whether your applications are appropriate for SimpleDB. Next, he walks you through all aspects of writing, deploying, querying, optimizing, and securing Amazon SimpleDB applications–from the basics through advanced techniques. Throughout, Mocky draws on his unsurpassed experience supporting developers on SimpleDB’s official Web forums. He offers practical tips and answers that can’t be found anywhere else, and presents extensive working sample code–from snippets to complete applications. With A Developer’s Guide to Amazon SimpleDB you will be able to Evaluate whether a project is suited for Amazon SimpleDB Write SimpleDB applications that take full advantage of SimpleDB’s availability, scalability, and flexibility Effectively manage the entire SimpleDB application lifecycle Deploy cloud computing applications faster and more easily Work with SELECT and bulk data operations Fine tune queries to optimize performance Integrate SimpleDB security into existing organizational security plans Write and enhance runtime SimpleDB clients Build complete applications using AJAX and SimpleDB Understand low-level issues involved in writing clients and frameworks Solve common SimpleDB usage problems and avoid hidden pitfalls This book will be an indispensable resource for every IT professional evaluating or using SimpleDB to build cloud-computing applications, clients, or frameworks.

Server bottlenecks and failures are a fact of life in any database deployment, but they don't have to bring everything to a halt. MySQL has several features that can help you protect your system from outages, whether it's running on hardware, virtual machines, or in the cloud. MySQL High Availability explains how to use these replication, cluster, and monitoring features in a wide range of real-life situations. Written by engineers who designed many of the tools covered inside, this book reveals undocumented or hard-to-find aspects of MySQL reliability and high availability -- knowledge that’s essential for any organization using this database system. "MySQL replication is widely deployed but has never been adequately explained. This book changes that."-- Mark Callaghan, MySQL contributor and leader of MySQL engineering efforts at a few of the world's largest Internet companies Explore the binary log, a file for replication that helps in disaster recovery and troubleshooting Get techniques for improving response time and handling large data sets Monitor database activity and performance, as well as major operating system parameters Keep track of what masters and slaves are doing, and deal with failures and restarts, corruption, and other incidents Automate key tasks with code from an open source library written by the authors Learn techniques for using MySQL in virtualized environments, such as Amazon Web Services Use MySQL Cluster to achieve high availability

Master Oracle Recovery Master Protect your databases from hardware, software, and operator failures using the detailed information in this Oracle Press guide. Oracle RMAN 11g Backup and Recovery explains how to configure databases, generate accurate archives, and carry out system restores. Work from the command line or Oracle Enterprise Manager, automate the backup process, perform Oracle Flashback recoveries, and integrate cloud computing technology. This authoritative resource also shows you how to create reports, optimize performance, and implement third-party administration utilities. Set up, configure, and maintain Oracle Recovery Manager (Oracle RMAN) Manage physical and virtual media with Oracle Secure Backup Work with Oracle RMAN catalogs, packages, and control files Use the Amazon Web Services cloud as an offsite storage solution Create online, offline, and incremental system backups Perform full and partial Oracle RMAN database restores Correct user-induced errors with Oracle Flashback Product clone and standby databases on local or remote servers Use Oracle Real Application Clusters and synch and split technology For a complete list of Oracle Press titles, visit www.OraclePressBooks.com

Build a simple serverless application using AWS Lambda and S3 bucket with Pulumi.

Learn the fundamentals of DevOps best practices. You will become familiar with the core concepts needed to deploy cloud resources continuously. Walk through configuring Pulumi GitHub Actions to deploy AWS resources programmatically and accelerate your cloud projects with the skeleton code provided.

How to create and manage EKS clusters in AWS with Pulumi.