Over 30 hands-on recipes that will get you up and running with Amazon Simple Storage Service (S3) efficiently About This Book Learn how to store, manage, and access your data with AWS SDKs Study the Amazon S3 pricing model and learn how to calculate costs by simulating practical scenarios Optimize your Amazon S3 bucket by following step-by-step instructions of how to deliver your content with CloudFront, secure the S3 bucket with IAM, and lower costs with object life cycle management Who This Book Is For This book is for cloud developers who have experience of using Amazon S3 and are also familiar with Amazon S3. What You Will Learn Host a static website on Amazon S3 Calculate costs with AWS Simple Monthly Calculators Deploy a static website via CloudFormation Distribute your content via CloudFront Secure resources with bucket policies and IAM Protect objects using server-side and client-side encryption Enable Cross-Origin Resource Sharing Manage objects' life cycles to lower costs Optimize performance for uploading as well as downloading objects Enable S3 event notifications and create Lambda functions Manage common operations with AWS SDKs In Detail Amazon S3 is one of the most famous and trailblazing cloud object storage services, which is highly scalable, low-latency, and economical. Users only pay for what they use and can store and retrieve any amount of data at any time over the Internet, which attracts Hadoop users who run clusters on EC2. The book starts by showing you how to install several AWS SDKs such as iOS, Java, Node.js, PHP, Python, and Ruby and shows you how to manage objects. Then, you'll be taught how to use the installed AWS SDKs to develop applications with Amazon S3. Furthermore, you will explore the Amazon S3 pricing model and will learn how to annotate S3 billing with cost allocation tagging. In addition to this, the book covers several practical recipes about how to distribute your content with CloudFront, secure your content with IAM, optimize Amazon S3 performance, and notify S3 events with Lambada. By the end of this book, you will be successfully implementing pro-level practices, techniques, and solutions in Amazon S3. Style and approach A step-by-step practical guide that will show you how to efficiently store, manage, and control your data in Amazon S3.

This practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you'll encounter on your cloud journey. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities. Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further. Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you: Redact personal identifiable information (PII) from text using Amazon Comprehend Automate password rotation for Amazon RDS databases Use VPC Reachability Analyzer to verify and troubleshoot network paths Lock down Amazon Simple Storage Service (S3) buckets Analyze AWS Identity and Access Management policies Autoscale a containerized service

Secure your Amazon Web Services (AWS) infrastructure with permission policies, key management, and network security, while following cloud security best practices Key Features Explore useful recipes for implementing robust cloud security solutions on AWS Monitor your AWS infrastructure and workloads using CloudWatch, CloudTrail, Config, GuardDuty, and Macie Prepare for the AWS Certified Security - Specialty exam by exploring various security models and compliance offerings Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs a security consultant, implementing policies and best practices to secure your infrastructure is critical. This cookbook discusses practical solutions for safeguarding infrastructure, covering services and features within AWS that help implement security models, such as the CIA triad (confidentiality, integrity, and availability) and the AAA triad (authentication, authorization, and accounting), as well as non-repudiation. This updated second edition starts with the fundamentals of AWS accounts and organizations. The book then guides you through identity and access management, data protection, network security, and encryption. You’ll explore critical topics such as securing EC2 instances, managing keys with KMS and CloudHSM, and implementing endpoint security. Additionally, you’ll learn to monitor your environment using CloudWatch, CloudTrail, and AWS Config, while maintaining compliance with services such as GuardDuty, Macie, and Inspector. Each chapter presents practical recipes for real-world scenarios, allowing you to apply security concepts. By the end of this book, you’ll be well versed in techniques required for securing AWS deployments and be prepared to gain the AWS Certified Security – Specialty certification.What you will learn Manage AWS accounts and users with AWS Organizations and IAM Identity Center Secure data and infrastructure with IAM policies, RBAC, and encryption Enhance web security with TLS, load balancers, and firewalls Use AWS services for logging, monitoring, and auditing Ensure compliance with machine-learning-powered AWS services Explore identity management with Cognito, AWS directory services, and external providers such as Entra ID Follow best practices to securely share data across accounts Who this book is for If you’re an IT security professional, cloud security architect, or a cloud application developer working on security-related roles and are interested in using AWS infrastructure for secure application deployments, then this Amazon Web Services book is for you. You’ll also find this book useful if you’re looking to achieve AWS certification. Prior knowledge of AWS and cloud computing is required to get the most out of this book.

Discover how to build a cloud-based data warehouse at petabyte-scale that is burstable and built to scale for end-to-end analytical solutions Key FeaturesDiscover how to translate familiar data warehousing concepts into Redshift implementationUse impressive Redshift features to optimize development, productionizing, and operations processesFind out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queriesBook Description Amazon Redshift is a fully managed, petabyte-scale AWS cloud data warehousing service. It enables you to build new data warehouse workloads on AWS and migrate on-premises traditional data warehousing platforms to Redshift. This book on Amazon Redshift starts by focusing on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll then learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. Because of the massive amount of data involved in data warehousing, designing your database for analytical processing lets you take full advantage of Redshift's columnar architecture and managed services. As you advance, you'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, which help minimize the operational efforts that you have to invest in managing regular ETL pipelines and ensure the timely and accurate refreshing of your data warehouse. Finally, you'll gain a clear understanding of Redshift use cases, data ingestion, data management, security, and scaling so that you can build a scalable data warehouse platform. By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution and have understood the best practice solutions to commonly faced problems. What you will learnUse Amazon Redshift to build petabyte-scale data warehouses that are agile at scaleIntegrate your data warehousing solution with a data lake using purpose-built features and services on AWSBuild end-to-end analytical solutions from data sourcing to consumption with the help of useful recipesLeverage Redshift's comprehensive security capabilities to meet the most demanding business requirementsFocus on architectural insights and rationale when using analytical recipesDiscover best practices for working with big data to operate a fully managed solutionWho this book is for This book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, such as data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, and cloud concepts and familiarity with Redshift will be beneficial.

Automate release processes, deployment, and continuous integration of your application as well as infrastructure automation with the powerful services offered by AWS About This Book Accelerate your infrastructure's productivity by implementing a continuous delivery pipeline within your environment Leverage AWS services and Jenkins 2.0 to perform complete application deployments on Linux servers This recipe-based guide that will help you minimize application deployment downtime Who This Book Is For This book is for developers and system administrators who are responsible for hosting their application and managing instances in AWS. It's also ideal for DevOps engineers looking to provide continuous integration, deployment, and delivery. A basic understanding of AWS, Jenkins, and some scripting knowledge is needed. What You Will Learn Build a sample Maven and NodeJS Application using CodeBuild Deploy the application in EC2/Auto Scaling and see how CodePipeline helps you integrate AWS services Build a highly scalable and fault tolerant CI/CD pipeline Achieve the CI/CD of a microservice architecture application in AWS ECS using CodePipeline, CodeBuild, ECR, and CloudFormation Automate the provisioning of your infrastructure using CloudFormation and Ansible Automate daily tasks and audit compliance using AWS Lambda Deploy microservices applications on Kubernetes using Jenkins Pipeline 2.0 In Detail AWS CodeDeploy, AWS CodeBuild, and CodePipeline are scalable services offered by AWS that automate an application's build and deployment pipeline. In order to deliver tremendous speed and agility, every organization is moving toward automating an entire application pipeline. This book will cover all the AWS services required to automate your deployment to your instances. You'll begin by setting up and using one of the AWS services for automation – CodeCommit. Next, you'll learn how to build a sample Maven and NodeJS Application using CodeBuild. After you've built the application, you'll see how to use CodeDeploy to deploy the application in EC2/Autoscaling. You'll also build a highly scalable and fault tolerant continuous integration (CI)/continuous deployment (CD) pipeline using some easy-to-follow recipes. Following this, you'll achieve CI/CD for Microservices application and reduce the risk within your software development lifecycle. You'll also learn to set up an infrastructure using CloudFormation Template and Ansible, and see how to automate AWS resources using AWS Lambda. Finally, you'll learn to automate instances in AWS and automate the deployment lifecycle of applications.By the end of this book, you'll be able to minimize application downtime and implement CI/CD, gaining total control over your software development lifecycle. Style and approach This book takes a "How to do it" approach, providing with easy solutions to automate common maintenance and deployment tasks.

Get started with Amazon S3 for virtually unlimited cloud and Internet storage About This Book Familiarize yourself with the concepts of Amazon S3 Understand basic operations of bucket, folders, and objects using Amazon S3 SDK Java Leverage the power of Amazon S3 to effectively store and retrieve data Who This Book Is For This book is intended for System Engineers/ Developers, Software Architects, Project managers, and users who want to explore Amazon S3 SDK Java. If you want to learn about Amazon S3 quickly, then this book is for you. Basic knowledge of Java programming is expected. What You Will Learn Start with the basic concepts of Amazon S3 to get you going Use Copy Object and Multipart Copy Object for objects of different sizes Understand how to use the amazon management console for Amazon S3 Learn how to use the AWS SDK of Java and consume the Amazon S3 Get to grips with managing the bucket life cycle Configure CORS to share resources to a different domain Discover how to develop and deploy the static website on Amazon S3 using different services of Amazon In Detail Amazon Simple Storage Service (Amazon S3), provides developers and IT teams with secure, durable, and highly-scalable object storage. Amazon S3 is easy to use, with a simple web services interface to store and retrieve any amount of data from anywhere on the web. S3 is automatically web scalable and responds to the requirements of your application and traffic, and therefore offers a key element to help companies deal dynamically with any spike in traffic for their application (such as a free e-book offer). This book starts with the basics of the Amazon S3 and its features, and you will quickly get an understanding how to use the Amazon Management Console for Amazon S3 which is the simplest way to manage Amazon S3. Next, we will cover basic operations on bucket, folder, objects. Once the basic operations are understood, you will know how to use Amazon S3 using Java SDK. Following that, you will learn about Copy Objects and Multipart copy objects for large objects size. You will also learn to manage the life cycle of bucket and how to share resources to the different domain by configuring CORS. The book will then guide you through the development and deployment of a static website on Amazon S3 using different services of Amazon. By the end of the book, you will be able to create a scalable application using Amazon S3. Style and approach This fast-paced book is a pragmatic guide to writing Amazon S3 applications. Each chapter is blended beautifully with lucid concepts and pertinent examples.

Become an AWS SysOps administrator and explore best practices to maintain a well-architected, resilient, and secure AWS environment Key FeaturesExplore AWS Cloud functionalities through a recipe-based approachGet to grips with a variety of techniques for automating your infrastructureDiscover industry-proven best practices for architecting reliable and efficient workloadsBook Description AWS is an on-demand remote computing service providing cloud infrastructure over the internet with storage, bandwidth, and customized support for APIs. This updated second edition will help you implement these services and efficiently administer your AWS environment. You will start with the AWS fundamentals and then understand how to manage multiple accounts before setting up consolidated billing. The book will assist you in setting up reliable and fast hosting for static websites, sharing data between running instances and backing up data for compliance. By understanding how to use compute service, you will also discover how to achieve quick and consistent instance provisioning. You’ll then learn to provision storage volumes and autoscale an app server. Next, you’ll explore serverless development with AWS Lambda, and gain insights into using networking and database services such as Amazon Neptune. The later chapters will focus on management tools like AWS CloudFormation, and how to secure your cloud resources and estimate costs for your infrastructure. Finally, you’ll use the AWS well-architected framework to conduct a technology baseline review self-assessment and identify critical areas for improvement in the management and operation of your cloud-based workloads. By the end of this book, you’ll have the skills to effectively administer your AWS environment. What you will learnSecure your account by creating IAM users and avoiding the use of the root loginSimplify the creation of a multi-account landing zone using AWS Control TowerMaster Amazon S3 for unlimited, cost-efficient storage of dataExplore a variety of compute resources on the AWS Cloud, such as EC2 and AWS LambdaConfigure secure networks using Amazon VPC, access control lists, and security groupsEstimate your monthly bill by using cost estimation toolsLearn to host a website with Amazon Route 53, Amazon CloudFront, and S3Who this book is for If you are an administrator, DevOps engineer, or an IT professional interested in exploring administrative tasks on the AWS Cloud, then this book is for you. Familiarity with cloud computing platforms and some understanding of virtualization, networking, and other administration-related tasks is assumed.

A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key FeaturesPerform ML experiments with built-in and custom algorithms in SageMakerExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learnUse the different features and capabilities of SageMaker to automate relevant ML processesBook Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What you will learnTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problemsPush the limits of customization in SageMaker using custom container imagesUse AutoML capabilities with SageMaker Autopilot to create high-quality modelsWork with effective data analysis and preparation techniquesExplore solutions for debugging and managing ML experiments and deploymentsDeal with bias detection and ML explainability requirements using SageMaker ClarifyAutomate intermediate and complex deployments and workflows using a variety of solutionsWho this book is for This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.

Over 70 recipes to help you use Apache Spark as your single big data computing platform and master its libraries About This Book This book contains recipes on how to use Apache Spark as a unified compute engine Cover how to connect various source systems to Apache Spark Covers various parts of machine learning including supervised/unsupervised learning & recommendation engines Who This Book Is For This book is for data engineers, data scientists, and those who want to implement Spark for real-time data processing. Anyone who is using Spark (or is planning to) will benefit from this book. The book assumes you have a basic knowledge of Scala as a programming language. What You Will Learn Install and configure Apache Spark with various cluster managers & on AWS Set up a development environment for Apache Spark including Databricks Cloud notebook Find out how to operate on data in Spark with schemas Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming Master supervised learning and unsupervised learning using MLlib Build a recommendation engine using MLlib Graph processing using GraphX and GraphFrames libraries Develop a set of common applications or project types, and solutions that solve complex big data problems In Detail While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark. Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand Spark 2.x's real-time processing capabilities and deploy scalable big data solutions. This is a valuable resource for data scientists and those working on large-scale data projects.

Want to build Facebook applications that truly stand out among the thousands already available? In addition to providing easy-to-follow recipes that offer practical ways to design and build scalable applications using the Facebook Platform and its new profile design, this Cookbook also explains proven strategies for attracting users in this highly competitive environment. With plenty of examples and practical solutions, Facebook Cookbook answers some of the hardest questions Facebook application developers contend with -- including how and where to get started. This Cookbook will help you: Learn to build an application that scales to accommodate a sudden influx of users Explore changes from Facebook's old profile design to the new look and feel Take advantage of new integration points in the new profile design Get tips for designing applications with hosting and deployment costs in mind Discover which widgets and controls to use for building the most attractive user interface design Learn the differences between standard HTML, JavaScript, and SQL, and the versions used on the Facebook Platform Target large, defined groups on Facebook, including those who want to find jobs, hire employees, market a business, advertise, and more If you can build simple web applications with HTML, Facebook Cookbook will help you build applications with the potential to reach millions of users around the globe. Learn what it takes to design applications that stand above the rest.