Redis Essentials

Harness the power of Redis to integrate and manage your projects efficiently About This Book Learn how to use Redis's data types efficiently to manage large data sets Scale Redis to multiple servers with Twemproxy, Redis Sentinel, and Redis Cluster A fast-paced guide, full of real-world examples to help you get the best out of the features offered by Redis Who This Book Is For If you are a competent developer with experience of working with data structure servers and want to boost your project's performance by learning about features of Redis, then this book is for you. What You Will Learn Build analytics applications using Bitmaps and Hyperloglogs Enhance scalability with Twemproxy, Redis Sentinel, and Redis Cluster Build a Time Series implementation in Node.js and Redis Create your own Redis commands by extending Redis with Lua Get to know security techniques to protect your data (SSL encryption, firewall rules, basic authorization) Persist data to disk and learn the trade-offs of AOF and RDB Understand how to use Node.js, PHP, Python, and Ruby clients for Redis Avoid common pitfalls when designing your next solution In Detail Redis is the most popular in-memory key-value data store. It's very lightweight and its data types give it an edge over the other competitors. If you need an in-memory database or a high-performance cache system that is simple to use and highly scalable, Redis is what you need. Redis Essentials is a fast-paced guide that teaches the fundamentals on data types, explains how to manage data through commands, and shares experiences from big players in the industry. We start off by explaining the basics of Redis followed by the various data types such as Strings, hashes, lists, and more. Next, Common pitfalls for various scenarios are described, followed by solutions to ensure you do not fall into common traps. After this, major differences between client implementations in PHP, Python, and Ruby are presented. Next, you will learn how to extend Redis with Lua, get to know security techniques such as basic authorization, firewall rules, and SSL encryption, and discover how to use Twemproxy, Redis Sentinel, and Redis Cluster to scale infrastructures horizontally. At the end of this book, you will be able to utilize all the essential features of Redis to optimize your project's performance. Style and approach A practical guide that offers the foundation upon which you can begin to understand the capabilities of Redis using a step-by-step approach. This book is full of real-world problems and in-depth knowledge of the concepts and features of Redis, with plenty of examples.

Unleash the Full Potential of High-Performance Data Storage with "Mastering Redis Database" In the rapidly evolving landscape of data management, the ability to handle and process data with speed and efficiency has become paramount. "Mastering Redis Database" is your definitive guide to mastering one of the most powerful and versatile NoSQL databases – Redis. Whether you're a seasoned data professional or a newcomer to the world of data caching and in-memory databases, this book equips you with the knowledge and skills needed to harness the true capabilities of Redis. About the Book: "Mastering Redis Database" takes you on an enlightening journey through the intricacies of Redis, from its foundational concepts to advanced techniques. From simple caching to complex data structures, this book covers it all. Each chapter is carefully crafted to provide both a deep understanding of the concepts and practical applications in real-world scenarios. Key Features: · Redis Foundations: Build a strong understanding of Redis's architecture, data types, and its role as an in-memory data store. · Data Structures: Learn how to leverage Redis's versatile data structures, including strings, lists, sets, sorted sets, and hashes, for efficient data storage and retrieval. · Advanced Techniques: Master advanced topics such as pub/sub messaging, Lua scripting, transactions, and data partitioning, allowing you to tackle complex scenarios with confidence. · Caching Strategies: Dive into Redis's caching capabilities, including cache eviction policies, TTL, and cache patterns, to enhance your application's performance. · High Availability and Replication: Explore Redis's mechanisms for ensuring high availability and data replication, providing fault tolerance and data durability. · Scaling Redis: Discover strategies for scaling Redis horizontally and vertically, enabling your applications to handle increasing data loads. · Integration and Ecosystem: Explore how Redis seamlessly integrates with other tools and frameworks, enabling you to build robust data pipelines and applications. · Real-World Use Cases: Gain insights from real-world examples spanning industries, from e-commerce and gaming to social media and real-time analytics. · Administration and Monitoring: Learn best practices for managing Redis instances, monitoring performance, and ensuring data security. Who This Book Is For: "Mastering Redis Database" is designed for developers, database administrators, and anyone seeking to leverage the power of in-memory databases. Whether you're new to Redis or aiming to deepen your expertise, this book provides the insights and tools to navigate the intricacies of Redis. Why You Should Read This Book: In a data-driven era where speed and performance are paramount, Redis stands as a leader in in-memory data storage. "Mastering Redis Database" empowers you to fully unlock its potential, enabling you to build applications that deliver lightning-fast responses, real-time analytics, and seamless user experiences. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Start defining your infrastructure using Docker Compose and leverage it for everyday development or deployment Key FeaturesDistribute your code in an easier way for developers to get startedSet up complex infrastructure for development and CI/CD purposesDeploy simple multi-container applications using Docker ComposeBook Description Software development is becoming increasingly complex due to the various software components used. Applications need to be packaged with software components to facilitate their operations, making it complicated to run them. With Docker Compose, a single command can set up your application and the needed dependencies. This book starts with an overview of Docker Compose and its usage and then shows how to create an application. You will also get to grips with the fundamentals of Docker volumes and network, along with Compose commands, their purpose, and use cases. Next, you will set up databases for daily usage using Compose and, leveraging Docker networking, you will establish communication between microservices. You will also run entire stacks locally on Compose, simulate production environments, and enhance CI/CD jobs using Docker Compose. Later chapters will show you how to benefit from Docker Compose for production deployments, provision infrastructure on public clouds such as AWS and Azure, and wrap up with Compose deployments on said infrastructure. By the end of this book, you will have learned how to effectively utilize Docker Compose for day-to-day development. What you will learnCreate multi-container applications using Docker ComposeUse Docker Compose for daily developmentConnect microservices leveraging Docker network fundamentalsAdd monitoring to services leveraging PrometheusDeploy to production using Docker ComposeTranslate Compose files to Kubernetes deploymentsWho this book is for This book is for software engineers, developer advocates, and DevOps engineers looking to set up multi-container Docker applications using Compose without the need to set up a Docker orchestration engine. It is also for team leads looking to increase the productivity of an organization's software teams by streamlining the provisioning of complex development environments locally using Docker Compose. Readers are expected to understand containerization and must possess fundamental Docker knowledge to get started with this book.

Discover the multi-model capabilities of Redis Stack as a document store and vector database, with support for time series, stream processing, probabilistic data structures, and more Key Features Model, index, and search data using JSON and vector data types Modernize your applications with vector similarity search, documents hybrid search, and more Configure a scalable, highly available, and secure server using RedisInsight Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn modern applications, efficiency in both operational and analytical aspects is paramount, demanding predictable performance across varied workloads. This book introduces you to Redis Stack, an extension of Redis and guides you through its broad data modeling capabilities. With practical examples of real-time queries and searches, you’ll explore Redis Stack’s new approach to providing a rich data modeling experience all within the same database server. You’ll learn how to model and search your data in the JSON and hash data types and work with features such as vector similarity search, which adds semantic search capabilities to your applications to search for similar texts, images, or audio files. The book also shows you how to use the probabilistic Bloom filters to efficiently resolve recurrent big data problems. As you uncover the strengths of Redis Stack as a data platform, you’ll explore use cases for managing database events and leveraging introduce stream processing features. Finally, you’ll see how Redis Stack seamlessly integrates into microservices architectures, completing the picture. By the end of this book, you’ll be equipped with best practices for administering and managing the server, ensuring scalability, high availability, data integrity, stored functions, and more.What you will learn Get started with data modeling using JSON and hash documents, vectors, and time series Implement microservices patterns and resolve typical use cases Use probabilistic data structures to analyze datasets and streams Integrate Redis Stack into your Java, Python, C#, Golang, and Node.js projects Develop powerful data flows using triggers and stream processing features Manage your database server for scalability, high availability, and security Visualize and manage your data with RedisInsight Who this book is for This book is for database administrators, database developers, software developers, and software architects who want to discover the powerful real-time, multi-model capabilities of the Redis Stack database. A basic understanding of Redis and databases in general, coupled with software development skills in at least one of Java, Python, C#, Golang, or JavaScript languages will help you understand the concepts covered in this book.

Understand how to use K3s and k3OS for different use cases and discover best practices for building an edge computing system Key FeaturesA guide to implementing an edge computing environmentReduce latency and costs for real-time applications running at the edgeFind stable and relevant cloud native open source software to complement your edge environmentsBook Description Edge computing is a way of processing information near the source of data instead of processing it on data centers in the cloud. In this way, edge computing can reduce latency when data is processed, improving the user experience on real-time data visualization for your applications. Using K3s, a light-weight Kubernetes and k3OS, a K3s-based Linux distribution along with other open source cloud native technologies, you can build reliable edge computing systems without spending a lot of money. In this book, you will learn how to design edge computing systems with containers and edge devices using sensors, GPS modules, WiFi, LoRa communication and so on. You will also get to grips with different use cases and examples covered in this book, how to solve common use cases for edge computing such as updating your applications using GitOps, reading data from sensors and storing it on SQL and NoSQL databases. Later chapters will show you how to connect hardware to your edge clusters, predict using machine learning, and analyze images with computer vision. All the examples and use cases in this book are designed to run on devices using 64-bit ARM processors, using Raspberry Pi devices as an example. By the end of this book, you will be able to use the content of these chapters as small pieces to create your own edge computing system. What you will learnConfigure k3OS and K3s for development and production scenariosPackage applications into K3s for shipped-node scenariosDeploy in occasionally connected scenarios, from one node to one million nodesManage GitOps for applications across different locationsUse open source cloud native software to complement your edge computing systemsImplement observability event-driven and serverless edge applicationsCollect and process data from sensors at the edge and visualize it into the cloudWho this book is for This book is for engineers (developers and/or operators) seeking to bring the cloud native benefits of GitOps and Kubernetes to the edge. Anyone with basic knowledge of Linux and containers looking to learn Kubernetes using examples applied to edge computing and hardware systems will benefit from this book.

Become an expert in Terraform on Google Cloud by using Infrastructure as Code for provisioning multiple yet consistent environments to increase productivity in no time Key FeaturesGet up and running with Terraform on Google CloudLearn Terraform concepts using Google Cloud code examplesApply Terraform to deploy realistic multi-tiered architectures quickly and repeatedlyBook Description Google Cloud has adopted Terraform as the standard Infrastructure as Code tool. This necessitates a solid understanding of Terraform for any cloud architect or engineer working on Google Cloud. Yet no specific resources are available that focus on how to use Terraform on Google Cloud. This is the first book that teaches Terraform specifically for Google Cloud. You will take a journey from the basic concepts through to deploying complex architectures using Terraform. Using extensive code examples, you will receive guidance on how to authenticate Terraform in Google Cloud. As you advance, you'll get to grips with all the essential concepts of the Terraform language as applied to Google Cloud and deploy complete working architectures at the push of a button. Finally, you'll also be able to improve your Terraform workflow using Google Cloud native and third-party tools. By the end of this Terraform book, you will have gained a thorough understanding of Terraform and how to use it on Google Cloud, and be able to develop effective Terraform code, build reusable code, and utilize public domain Terraform modules to deploy on Google Cloud faster and more securely. What you will learnAuthenticate Terraform in Google Cloud using multiple methodsWrite efficient Terraform codeUse modules to share Terraform templatesManage multiple environments in Google CloudApply Terraform to deploy multi-tiered architecturesUse public modules to deploy complex architectures quicklyIntegrate Terraform into your Google Cloud environmentWho this book is for This book is for Google Cloud architects and engineers who want to increase their productivity by using Terraform to automate the provisioning of Google Cloud deployments. A basic understanding of Google Cloud, such as the ability to provision resources using the Google Cloud console and using Cloud Shell, is assumed. Certification in Google Cloud is not required but helpful.

With social media producing such huge amounts of data, the importance of gathering this rich data, often called "the digital gold rush", processing it and retrieving information is vital. This practical book combines various state-of-the-art tools, technologies and techniques to help us understand Social Media Analytics, Data Mining and Graph Databases, and how to better utilize their potential. Graph Databases: Applications on Social Media Analytics and Smart Cities reviews social media analytics with examples using real-world data. It describes data mining tools for optimal information retrieval; how to crawl and mine data from Twitter; and the advantages of Graph Databases. The book is meant for students, academicians, developers and simple general users involved with Data Science and Graph Databases to understand the notions, concepts, techniques, and tools necessary to extract data from social media, which will aid in better information retrieval, management and prediction.

This book gathers the refereed proceedings of the Intelligent Algorithms in Software Engineering Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Software engineering research and its applications to intelligent algorithms have now assumed an essential role in computer science research. In this book, modern research methods, together with applications of machine and statistical learning in software engineering research, are presented.