Aws Generate Architecture Diagram

  aws generate architecture diagram: AWS Cloud Projects Ivo Pinto, Pedro Santos, 2024-10-25 Gain a deeper understanding of AWS services by building eight real-world projects Key Features Gain practical skills in architecting, deploying, and managing applications on AWS from seasoned experts Get hands-on experience by building different architectures in an easy-to-follow manner Understand the purpose of different aspects in AWS, and how to make the most of them Purchase of the print or Kindle book includes a free PDF eBook Book Description Tired of resumes that get lost in the pile? This book is your roadmap to creating an in-demand AWS portfolio that grabs attention and gets you hired.This comprehensive guide unlocks the vast potential of AWS for developers of all levels. Inside, you'll find invaluable guidance for crafting stunning websites with S3, CloudFront, and Route53. You'll build robust and scalable applications, such as recipe-sharing platforms, using DynamoDB and Elastic Load Balancing. For streamlined efficiency, the book will teach you how to develop serverless architectures with AWS Lambda and Cognito. Gradually, you'll infuse your projects with artificial intelligence by creating a photo analyzer powered by Amazon Rekognition. You'll also automate complex workflows for seamless content translation using Translate, CodePipeline, and CodeBuild. Later, you'll construct intelligent virtual assistants with Amazon Lex and Bedrock to answer web development queries. The book will also show you how to visualize your data with insightful dashboards built using Athena, Glue, and QuickSight.By the end of this book, you'll be ready to take your projects to the next level and succeed in the dynamic world of cloud computing. What you will learn Develop a professional CV website and gain familiarity with the core aspects of AWS Build a recipe-sharing application using AWS's serverless toolkit Leverage AWS AI services to create a photo friendliness analyzer for professional profiles Implement a CI/CD pipeline to automate content translation across languages Develop a web development Q&A chatbot powered by cutting-edge LLMs Build a business intelligence application to analyze website clickstream data and understand user behavior with AWS Who this book is for If you're a student who wants to start your career in cloud computing or a professional with experience in other technical areas like software development who wants to embrace a new professional path or complement your technical skills in cloud computing, this book is for you. A background in computer science or engineering and basic programming skills is recommended. All the projects in the book have theoretical explanations of the services used and do not assume any previous AWS knowledge.
  aws generate architecture diagram: Modern Data Architecture on AWS Behram Irani, 2023-08-31 Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services Key Features Learn to build modern data platforms on AWS using data lakes and purpose-built data services Uncover methods of applying security and governance across your data platform built on AWS Find out how to operationalize and optimize your data platform on AWS Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.What you will learn Familiarize yourself with the building blocks of modern data architecture on AWS Discover how to create an end-to-end data platform on AWS Design data architectures for your own use cases using AWS services Ingest data from disparate sources into target data stores on AWS Build data pipelines, data sharing mechanisms, and data consumption patterns using AWS services Find out how to implement data governance using AWS services Who this book is for This book is for data architects, data engineers, and professionals creating data platforms. The book's use case–driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner’s level understanding of AWS Cloud.
  aws generate architecture diagram: AWS for Solutions Architects Saurabh Shrivastava, Neelanjali Srivastav, Alberto Artasanchez, Imtiaz Sayed, Dr. Siddhartha Choubey Ph.D, 2023-04-28 Become a master Solutions Architect with this comprehensive guide, featuring cloud design patterns and real-world solutions for building scalable, secure, and highly available systems Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Gain expertise in automating, networking, migrating, and adopting cloud technologies using AWS Use streaming analytics, big data, AI/ML, IoT, quantum computing, and blockchain to transform your business Upskill yourself as an AWS solutions architect and explore details of the new AWS certification Book Description Are you excited to harness the power of AWS and unlock endless possibilities for your business? Look no further than the second edition of AWS for Solutions Architects! Packed with all-new content, this book is a must-have guide for anyone looking to build scalable cloud solutions and drive digital transformation using AWS. This updated edition offers in-depth guidance for building cloud solutions using AWS. It provides detailed information on AWS well-architected design pillars and cloud-native design patterns. You'll learn about networking in AWS, big data and streaming data processing, CloudOps, and emerging technologies such as machine learning, IoT, and blockchain. Additionally, the book includes new sections on storage in AWS, containers with ECS and EKS, and data lake patterns, providing you with valuable insights into designing industry-standard AWS architectures that meet your organization's technological and business requirements. Whether you're an experienced solutions architect or just getting started with AWS, this book has everything you need to confidently build cloud-native workloads and enterprise solutions. What you will learn Optimize your Cloud Workload using the AWS Well-Architected Framework Learn methods to migrate your workload using the AWS Cloud Adoption Framework Apply cloud automation at various layers of application workload to increase efficiency Build a landing zone in AWS and hybrid cloud setups with deep networking techniques Select reference architectures for business scenarios, like data lakes, containers, and serverless apps Apply emerging technologies in your architecture, including AI/ML, IoT and blockchain Who this book is for This book is for application and enterprise architects, developers, and operations engineers who want to become well versed with AWS architectural patterns, best practices, and advanced techniques to build scalable, secure, highly available, highly tolerant, and cost-effective solutions in the cloud. Existing AWS users are bound to learn the most, but it will also help those curious about how leveraging AWS can benefit their organization. Prior knowledge of any computing language is not needed, and there's little to no code. Prior experience in software architecture design will prove helpful.
  aws generate architecture diagram: AWS Tools for PowerShell 6 Ramesh Waghmare, 2017-08-03 Leverage the power of PowerShell to bring the best out of your AWS infrastructure About This Book A collection of real-world-tested Powershell scripts that can be used to manage your Windows server efficiently Follow step-by-step processes to solve your problems with Windows servers using AWS tools Design examples that work in the Amazon free usage tier, which lets you run the Windows platform on cloud Who This Book Is For This book will be useful for (but not limited to) Windows System administrators, cloud engineers, architects, DevOps engineers, and all those who want to accomplish tasks on the AWS Public Cloud using PowerShell. What You Will Learn Install the AWS Tools for PowerShell 6 Understand key services provided by Amazon Web services (AWS) Understand the Virtual Private Cloud Use PowerShell 6 for AWS Identity and Access Management (IAM) Use PowerShell 6 for AWS Elastic Compute Cloud (EC2) Use PowerShell 6 for AWS Simple Storage Service (S3) Use PowerShell 6 for AWS Relational Database Service (RDS) Build fault-tolerant and highly-available applications using PowerShell 6 In Detail AWS Tools for PowerShell 6 shows you exactly how to automate all the aspects of AWS. You can take advantage of the amazing power of the cloud, yet add powerful scripts and mechanisms to perform common tasks faster than ever before. This book expands on the Amazon documentation with real-world, useful examples and production-ready scripts to automate all the aspects of your new cloud platform. It will cover topics such as managing Windows with PowerShell, setting up security services, administering database services, and deploying and managing networking. You will also explore advanced topics such as PowerShell authoring techniques, and configuring and managing storage and content delivery. By the end of this book, you will be able to use Amazon Web Services to automate and manage Windows servers. You will also have gained a good understanding of automating the AWS infrastructure using simple coding. Style and approach This step-by-step guide starts with simple examples then expands to full-blown administrative tasks leading to the efficient management of Windows servers. Each topic covers a section related to Amazon Web Services products, and the examples are built on one another to deliver a comprehensive library of scripts for administrators.
  aws generate architecture diagram: Building and Delivering Microservices on AWS Amar Deep Singh, 2023-05-30 Quickly deliver microservices with CodeCommit, CodeBuild, CodeDeploy, and CodePipeline using software architecture patterns, microservices, and release pipelines Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn software architecture and microservices design patterns from an AWS certified professional architect Develop microservices using Spring Boot and automate the release using CodePipeline Deploy microservices using CodeDeploy to EC2 instances, containers, and on premises Book DescriptionReliable automation is crucial for any code change going into production. A release pipeline enables you to deliver features for your users efficiently and promptly. AWS CodePipeline, with its powerful integration and automation capabilities of building, testing, and deployment, offers a unique solution to common software delivery issues such as outages during deployment, a lack of standard delivery mechanisms, and challenges faced in creating sustainable pipelines. You’ll begin by developing a Java microservice and using AWS services such as CodeCommit, CodeArtifact, and CodeGuru to manage and review the source code. You’ll then learn to use the AWS CodeBuild service to build code and deploy it to AWS infrastructure and container services using the CodeDeploy service. As you advance, you’ll find out how to provision cloud infrastructure using CloudFormation templates and Terraform. The concluding chapters will show you how to combine all these AWS services to create a reliable and automated CodePipeline for delivering microservices from source code check-in to deployment without any downtime. Finally, you’ll discover how to integrate AWS CodePipeline with third-party services such as Bitbucket, Blazemeter, Snyk, and Jenkins. By the end of this microservices book, you’ll have gained the hands-on skills to build release pipelines for your applications.What you will learn Understand the basics of architecture patterns and microservice development Get to grips with the continuous integration and continuous delivery of microservices Delve into automated infrastructure provisioning with CloudFormation and Terraform Explore CodeCommit, CodeBuild, CodeDeploy, and CodePipeline services Get familiarized with automated code reviews and profiling using CodeGuru Grasp AWS Lambda function basics and automated deployment using CodePipeline Understand Docker basics and automated deployment to ECS and EKS Explore the CodePipeline integration with Jenkins Pipeline and on premises deployment Who this book is for This book is for software architects, DevOps engineers, SREs, and cloud engineers who want to learn more about automating their release pipelines for modifying features and releasing updates. Prior knowledge of AWS Cloud, Java, Maven, and Git will help you to get the most out of this book.
  aws generate architecture diagram: Data Engineering with AWS Gareth Eagar, 2021-12-29 The missing expert-led manual for the AWS ecosystem — go from foundations to building data engineering pipelines effortlessly Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Learn about common data architectures and modern approaches to generating value from big data Explore AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines Learn how to architect and implement data lakes and data lakehouses for big data analytics from a data lakes expert Book DescriptionWritten by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.What you will learn Understand data engineering concepts and emerging technologies Ingest streaming data with Amazon Kinesis Data Firehose Optimize, denormalize, and join datasets with AWS Glue Studio Use Amazon S3 events to trigger a Lambda process to transform a file Run complex SQL queries on data lake data using Amazon Athena Load data into a Redshift data warehouse and run queries Create a visualization of your data using Amazon QuickSight Extract sentiment data from a dataset using Amazon Comprehend Who this book is for This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts while gaining practical experience with common data engineering services on AWS will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.
  aws generate architecture diagram: AWS DevOps Engineer Professional Certification Guide Sumit Kapoor, 2024-04-21 Crack the exam and become an expert in provisioning, operating, and managing distributed application systems on the AWS platform KEY FEATURES ● This book offers real-world and hands-on examples that will prepare you to take the exam with confidence. ● Enhance your abilities for efficient interdepartmental communication, fostering cost-effective business solutions. ● Includes mock exams with explanations for self-assessment and boosting confidence. DESCRIPTION The AWS DevOps Engineer Professional Certification Guide is highly challenging and can significantly boost one's career. It features scenario-based questions with lengthy descriptions, making comprehension tough. This book focuses extensively on AWS Developer Tools, CloudFormation, Elastic Beanstalk, OpsWorks, and other crucial topics, representing the exam's domain. The readers can easily prepare for the AWS Certified DevOps Engineer - Professional exam with this guide drafted with a focus on managing infrastructure and applications on AWS. It covers secure version control with CodeCommit, automated code building with CodeBuild, and streamlined updates with CodeDeploy and CodePipeline. You will learn to create secure CI/CD pipelines and define AWS infrastructure and applications with CloudFormation. The readers will explore the management of multiple AWS accounts, security tools, and automation with OpsWorks and Elastic Beanstalk. You will also discover strategies for scalability, disaster recovery, monitoring with CloudWatch, and performance analysis with Kinesis Data Streams. Finally, you will learn to implement automated responses and security best practices with AWS Config and Inspector. Successfully passing this exam will help you gain advanced technical skills needed to become a DevOps subject matter expert and earn a good remuneration in the IT industry. WHAT YOU WILL LEARN ● Set up automated code building, testing, and deployment. ● Automate the configuration and deployment in AWS for efficiency. ● Design infrastructure and applications on AWS that handle high traffic and unexpected situations. ● Gain insights into infrastructure and application performance on AWS with advanced monitoring tools. ● Learn about best practices for securing infrastructure and applications on AWS, like access control, encryption, vulnerability scanning, and incident response procedures. WHO THIS BOOK IS FOR This book is ideal for IT professionals, like cloud engineers, DevOps engineers, and system administrators, who want to build and manage secure, scalable websites on AWS. It equips them with the knowledge to become a certified AWS DevOps Engineer - Professional. TABLE OF CONTENTS 1. Continuous Integration with CodeCommit and CodeBuild 2. Continuous Delivery with CodeDeploy and CodePipeline 3. Cross-Account CI/CD Pipelines and Testing 4. Infrastructure as Code Using CloudFormation 5. Automated Account Management and Security in AWS 6. Automation Using OpsWorks and Elastic Beanstalk 7. Implement High Availability, Scalability, and Fault Tolerance 8. Design and Automate Disaster Recovery Strategies 9. Automate Monitoring and Event Management 10. Auditing, Logging and Monitoring Containers and Applications 11. Troubleshooting and Restoring Operations 12. Setup Event-Driven Automated Actions 13. Implement Governance Strategies and Cost Optimization 14. Advanced Security, Access Control, and Identity Management 15. Mock Exam: 1 16. Mock Exam: 2
  aws generate architecture diagram: Solutions Architect's Handbook Saurabh Shrivastava, Neelanjali Srivastav, 2024-03-29 From fundamentals and design patterns to the latest techniques such as generative AI, machine learning and cloud native architecture, gain all you need to be a pro Solutions Architect crafting secure and reliable AWS architecture. Key Features Hits all the key areas -Rajesh Sheth, VP, Elastic Block Store, AWS Offers the knowledge you need to succeed in the evolving landscape of tech architecture - Luis Lopez Soria, Senior Specialist Solutions Architect, Google A valuable resource for enterprise strategists looking to build resilient applications - Cher Simon, Principal Solutions Architect, AWS Book DescriptionMaster the art of solution architecture and excel as a Solutions Architect with the Solutions Architect's Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. Large language models, generative AI, and innovations in deep learning are cutting-edge advancements shaping the future of technology. Topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient and secure architectures remain important in today's landscape. This book provides coverage of these emerging and key technologies and walks you through solution architecture design from key principles, providing you with the knowledge you need to succeed as a Solutions Architect. It will also level up your soft skills, providing career-accelerating techniques to help you get ahead. Unlock the potential of cutting-edge technologies, gain practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.What you will learn Explore various roles of a solutions architect in the enterprise Apply design principles for high-performance, cost-effective solutions Choose the best strategies to secure your architectures and boost availability Develop a DevOps and CloudOps mindset for collaboration, operational efficiency, and streamlined production Apply machine learning, data engineering, LLMs, and generative AI for improved security and performance Modernize legacy systems into cloud-native architectures with proven real-world strategies Master key solutions architect soft skills Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and some awareness of cloud technology.
  aws generate architecture diagram: Serverless Architectures with AWS Mohit Gupta, 2018-12-24 Serverless Architectures with AWS teaches you how to build serverless applications on AWS—applications that do not require the developer to provision, scale, or manage any servers. Using an event-driven approach and AWS Lambda as the primary service, the book explains the many benefits of serverless architectures. By the end of the book, you ...
  aws generate architecture diagram: 50 Kubernetes Concepts Every DevOps Engineer Should Know Michael Levan, 2023-01-30 A must-have Kubernetes book to learn key concepts for succeeding in any production environment, be it a greenfield Kubernetes environment or your cloud-native journey Key FeaturesAdvance in your Kubernetes journey with guidance from a seasoned k8s practitioner and trainerDiscover best practices for implementing Kubernetes in any production environmentGo beyond the basics and work with Kubernetes applications in every environmentBook Description Kubernetes is a trending topic among engineers, CTOs, CIOs, and other technically sound professionals. Due to its proliferation and importance for all cloud technologies, DevOps engineers nowadays need a solid grasp of key Kubernetes concepts to help their organization thrive. This book equips you with all the requisite information about how Kubernetes works and how to use it for the best results. You'll learn everything from why cloud native is important to implementing Kubernetes clusters to deploying applications in production. This book takes you on a learning journey, starting from what cloud native is and how to get started with Kubernetes in the cloud, on-premises, and PaaS environments such as OpenShift. Next, you'll learn about deploying applications in many ways, including Deployment specs, Ingress Specs, and StatefulSet specs. Finally, you'll be comfortable working with Kubernetes monitoring, observability, and security. Each chapter of 50 Kubernetes Concepts Every DevOps Engineer Should Know is built upon the previous chapter, ensuring that you develop practical skills as you work through the code examples in GitHub, allowing you to follow along while giving you practical knowledge. By the end of this book, you'll be able to implement Kubernetes in any environment, whether it's an existing environment, a greenfield environment, or your very own lab running in the cloud or your home. What you will learnFind out how Kubernetes works on-premises, in the cloud, and in PaaS environmentsWork with networking, cluster management, and application deploymentUnderstand why cloud native is crucial for Kubernetes applicationsDeploy apps in different states, including Stateless and StatefulMonitor and implement observability in your environmentExplore the functioning of Kubernetes security at the cluster, user, and application levelWho this book is for This book is for cloud engineers, developers, DevOps engineers, and infrastructure engineers responsible for inheriting a Kubernetes environment or creating a greenfield Kubernetes environment. If you are a professional who wants to get started with cloud-native applications and implement k8s best practices, then this book is a must-read. If you have engineered environments in the cloud and on-premises and understand how to deploy applications with a solid tenure in a developer role, this book will help you further your skills.
  aws generate architecture diagram: Hands-On Artificial Intelligence on Amazon Web Services Subhashini Tripuraneni, Charles Song, 2019-10-04 Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly Key FeaturesExplore popular machine learning and deep learning services with their underlying algorithmsDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language ServicesDesign robust architectures to enable experimentation, extensibility, and maintainability of AI appsBook Description From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. What you will learnGain useful insights into different machine and deep learning modelsBuild and deploy robust deep learning systems to productionTrain machine and deep learning models with diverse infrastructure specificationsScale AI apps without dealing with the complexity of managing the underlying infrastructureMonitor and Manage AI experiments efficientlyCreate AI apps using AWS pre-trained AI servicesWho this book is for This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected.
  aws generate architecture diagram: AWS for Solutions Architects Alberto Artasanchez, 2021-02-19 Apply cloud design patterns to overcome real-world challenges by building scalable, secure, highly available, and cost-effective solutions Key Features Apply AWS Well-Architected Framework concepts to common real-world use cases Understand how to select AWS patterns and architectures that are best suited to your needs Ensure the security and stability of a solution without impacting cost or performance Book DescriptionOne of the most popular cloud platforms in the world, Amazon Web Services (AWS) offers hundreds of services with thousands of features to help you build scalable cloud solutions; however, it can be overwhelming to navigate the vast number of services and decide which ones best suit your requirements. Whether you are an application architect, enterprise architect, developer, or operations engineer, this book will take you through AWS architectural patterns and guide you in selecting the most appropriate services for your projects. AWS for Solutions Architects is a comprehensive guide that covers the essential concepts that you need to know for designing well-architected AWS solutions that solve the challenges organizations face daily. You'll get to grips with AWS architectural principles and patterns by implementing best practices and recommended techniques for real-world use cases. The book will show you how to enhance operational efficiency, security, reliability, performance, and cost-effectiveness using real-world examples. By the end of this AWS book, you'll have gained a clear understanding of how to design AWS architectures using the most appropriate services to meet your organization's technological and business requirements.What you will learn Rationalize the selection of AWS as the right cloud provider for your organization Choose the most appropriate service from AWS for a particular use case or project Implement change and operations management Find out the right resource type and size to balance performance and efficiency Discover how to mitigate risk and enforce security, authentication, and authorization Identify common business scenarios and select the right reference architectures for them Who this book is for This book is for application and enterprise architects, developers, and operations engineers who want to become well-versed with AWS architectural patterns, best practices, and advanced techniques to build scalable, secure, highly available, and cost-effective solutions in the cloud. Although existing AWS users will find this book most useful, it will also help potential users understand how leveraging AWS can benefit their organization.
  aws generate architecture diagram: Learning Serverless Jason Katzer, 2020-10-29 Whether your company is considering serverless computing or has already made the decision to adopt this model, this practical book is for you. Author Jason Katzer shows early- and mid-career developers what's required to build and ship maintainable and scalable services using this model. With this book, you'll learn how to build a modern production system in the cloud, viewed through the lens of serverless computing. You'll discover how serverless can free you from the tedious task of setting up and maintaining systems in production. You'll also explore new ways to level up your career and design, develop, and deploy with confidence. In three parts, this book includes: The Path to Production: Examine the ins and outs of distributed systems, microservices, interfaces, and serverless architecture and patterns The Tools: Dive into monitoring, observability and alerting, logging, pipelines, automation, and deployment Concepts: Learn how to design security and privacy, how to manage quality through testing and staging, and how to plan for failure
  aws generate architecture diagram: AWS Certified Developer – Associate Guide Vipul Tankariya, Bhavin Parmar, 2019-06-03 Learn from the AWS subject-matter experts, explore real-world scenarios, and pass the AWS Certified Developer – Associate exam Key FeaturesThis fast-paced guide will help you clear the AWS Certified Developer – Associate (DVA-C01) exam with confidenceGain valuable insights to design, develop, and deploy cloud-based solutions using AWSDevelop expert core AWS skills with practice questions and mock testsBook Description This book will focus on the revised version of AWS Certified Developer Associate exam. The 2019 version of this exam guide includes all the recent services and offerings from Amazon that benefits developers. AWS Certified Developer - Associate Guide starts with a quick introduction to AWS and the prerequisites to get you started. Then, this book will describe about getting familiar with Identity and Access Management (IAM) along with Virtual private cloud (VPC). Next, this book will teach you about microservices, serverless architecture, security best practices, advanced deployment methods and more. Going ahead we will take you through AWS DynamoDB A NoSQL Database Service, Amazon Simple Queue Service (SQS) and CloudFormation Overview. Lastly, this book will help understand Elastic Beanstalk and will also walk you through AWS lambda. At the end of this book, we will cover enough topics, tips and tricks along with mock tests for you to be able to pass the AWS Certified Developer - Associate exam and develop as well as manage your applications on the AWS platform. What you will learnCreate and manage users, groups, and permissions using AWS IAM servicesCreate a secured VPC with Public and Private Subnets, NAC, and Security groupsLaunching your first EC2 instance, and working with itHandle application traffic with ELB and monitor AWS resources with CloudWatchWork with AWS storage services such as S3, Glacier, and CloudFrontGet acquainted with AWS DynamoDB a NoSQL database serviceUse SWS to coordinate work across distributed application componentsWho this book is for This book is for IT professionals and developers looking to clear the AWS Certified Developer Associate 2019 exam. Developers looking to develop and manage their applications on the AWS platform will also find this book useful. No prior AWS experience is needed.
  aws generate architecture diagram: Docker on Amazon Web Services Justin Menga, 2018-08-30 Run Docker on AWS and build real-world, secure, and scalable container platforms on cloud Key Features Configure Docker for the ECS environment Integrate Docker with different AWS tools Implement container networking and deployment at scale Book Description Over the last few years, Docker has been the gold standard for building and distributing container applications. Amazon Web Services (AWS) is a leader in public cloud computing, and was the first to offer a managed container platform in the form of the Elastic Container Service (ECS). Docker on Amazon Web Services starts with the basics of containers, Docker, and AWS, before teaching you how to install Docker on your local machine and establish access to your AWS account. You'll then dig deeper into the ECS, a native container management platform provided by AWS that simplifies management and operation of your Docker clusters and applications for no additional cost. Once you have got to grips with the basics, you'll solve key operational challenges, including secrets management and auto-scaling your infrastructure and applications. You'll explore alternative strategies for deploying and running your Docker applications on AWS, including Fargate and ECS Service Discovery, Elastic Beanstalk, Docker Swarm and Elastic Kubernetes Service (EKS). In addition to this, there will be a strong focus on adopting an Infrastructure as Code (IaC) approach using AWS CloudFormation. By the end of this book, you'll not only understand how to run Docker on AWS, but also be able to build real-world, secure, and scalable container platforms in the cloud. What you will learn Build, deploy, and operate Docker applications using AWS Solve key operational challenges, such as secrets management Exploit the powerful capabilities and tight integration of other AWS services Design and operate Docker applications running on ECS Deploy Docker applications quickly, consistently, and reliably using IaC Manage and operate Docker clusters and applications for no additional cost Who this book is for Docker on Amazon Web Services is for you if you want to build, deploy, and operate applications using the power of containers, Docker, and Amazon Web Services. Basic understanding of containers and Amazon Web Services or any other cloud provider will be helpful, although no previous experience of working with these is required.
  aws generate architecture diagram: Mastering DynamoDB Tanmay Deshpande, 2014-08-25 If you have interest in DynamoDB and want to know what DynamoDB is all about and become proficient in using it, this is the book for you. If you are an intermediate user who wishes to enhance your knowledge of DynamoDB, this book is aimed at you. Basic familiarity with programming, NoSQL, and cloud computing concepts would be helpful.
  aws generate architecture diagram: Security as Code BK Sarthak Das, Virginia Chu, 2023-01-03 DevOps engineers, developers, and security engineers have ever-changing roles to play in today's cloud native world. In order to build secure and resilient applications, you have to be equipped with security knowledge. Enter security as code. In this book, authors BK Sarthak Das and Virginia Chu demonstrate how to use this methodology to secure any application and infrastructure you want to deploy. With Security as Code, you'll learn how to create a secure containerized application with Kubernetes using CI/CD tooling from AWS and open source providers. This practical book also provides common patterns and methods to securely develop infrastructure for resilient and highly available backups that you can restore with just minimal manual intervention. Learn the tools of the trade, using Kubernetes and the AWS Code Suite Set up infrastructure as code and run scans to detect misconfigured resources in your code Create secure logging patterns with CloudWatch and other tools Restrict system access to authorized users with role-based access control (RBAC) Inject faults to test the resiliency of your application with AWS Fault Injector or open source tooling Learn how to pull everything together into one deployment
  aws generate architecture diagram: AI and Blockchain in Healthcare Bipin Kumar Rai, Gautam Kumar, Vipin Balyan, 2023-04-30 This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).
  aws generate architecture diagram: Cloud Native Architectures Tom Laszewski, Kamal Arora, Erik Farr, Piyum Zonooz, 2018-08-31 Learn and understand the need to architect cloud applications and migrate your business to cloud efficiently Key Features Understand the core design elements required to build scalable systems Plan resources and technology stacks effectively for high security and fault tolerance Explore core architectural principles using real-world examples Book Description Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. To harness this, businesses need to refresh their development models and architectures when they find they don’t port to the cloud. Cloud Native Architectures demonstrates three essential components of deploying modern cloud native architectures: organizational transformation, deployment modernization, and cloud native architecture patterns. This book starts with a quick introduction to cloud native architectures that are used as a base to define and explain what cloud native architecture is and is not. You will learn what a cloud adoption framework looks like and develop cloud native architectures using microservices and serverless computing as design principles. You’ll then explore the major pillars of cloud native design including scalability, cost optimization, security, and ways to achieve operational excellence. In the concluding chapters, you will also learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform. By the end of this book, you will have learned the techniques to adopt cloud native architectures that meet your business requirements. You will also understand the future trends and expectations of cloud providers. What you will learn Learn the difference between cloud native and traditional architecture Explore the aspects of migration, when and why to use it Identify the elements to consider when selecting a technology for your architecture Automate security controls and configuration management Use infrastructure as code and CICD pipelines to run environments in a sustainable manner Understand the management and monitoring capabilities for AWS cloud native application architectures Who this book is for Cloud Native Architectures is for software architects who are keen on designing resilient, scalable, and highly available applications that are native to the cloud.
  aws generate architecture diagram: Internet of Things from Scratch Renaldi Gondosubroto, 2024-02-16 Kickstart your IoT design and implementation journey with this comprehensive book, covering basics to advanced concepts through practical examples and industry-standard practices Key Features Master the different components that make up an IoT system to design and implement solutions Unlock the powerful capabilities of cloud computing that enhance the efficiency of your IoT deployments Integrate cutting-edge technologies, such as with generative AI, into your IoT projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDevelop the skills essential for building Internet of Things solutions with this indispensable guide. In an era where industries heavily rely on IoT, this book will quickly familiarize you with its foundations, widespread use, implementation guided by best practices, and the crucial technologies that allow it to work effectively. Starting with the use of IoT in real-life scenarios, this book offers comprehensive insights into basic IoT hardware, protocols, and technologies. You’ll then learn about architecting and implementing solutions such as wireless sensor networks, cloud computing with AWS, and crucial security considerations. You’ll understand how these systems are operated and monitored over time and work with simple to complex, industry-grade systems, adhering to best practices. In later chapters, you’ll be apprised of future IoT trends and strategies to manage the risks and opportunities that come with them. You’ll also get to grips with a diverse set of tools, including hardware such as ESP32 and Raspberry Pi, and software such as Mosquitto and ChatGPT for generative AI capabilities. By the end of this IoT book, you’ll be able to independently build and design complex, industry-standard solutions fully aligned with best practices.What you will learn Gain a holistic understanding of IoT basics through real-life use cases Explore communication protocols and technologies integral to IoT Use AWS to build resilient, low-latency networks Construct complex IoT networks, building upon foundational principles Integrate data analytics workloads and generative AI seamlessly with IoT Understand the security threat landscape of IoT and how to mitigate these risks Develop industry-grade projects within the open source IoT community Embrace a futuristic perspective of IoT by understanding both risks and rewards Who this book is for The book is for novice electronics engineers, embedded systems specialists, and IoT developers as well as intermediate practitioners looking to advance in the world of industry-based IoT applications. While no prior knowledge of IoT is assumed, familiarity with at least one programming language is recommended to get the most out of this book.
  aws generate architecture diagram: Generative AI with Amazon Bedrock Shikhar Kwatra, Bunny Kaushik, 2024-07-31 Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards Key Features Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects Master the core techniques to develop and deploy several AI applications at scale Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure. Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock. By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learn Explore the generative AI landscape and foundation models in Amazon Bedrock Fine-tune generative models to improve their performance Explore several architecture patterns for different business use cases Gain insights into ethical AI practices, model governance, and risk mitigation strategies Enhance your skills in employing agents to develop intelligence and orchestrate tasks Monitor and understand metrics and Amazon Bedrock model response Explore various industrial use cases and architectures to solve real-world business problems using RAG Stay on top of architectural best practices and industry standards Who this book is for This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.
  aws generate architecture diagram: ICT with Intelligent Applications Tomonobu Senjyu, Parikshit N. Mahalle, Thinagaran Perumal, Amit Joshi, 2021-12-05 This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fifth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2021), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.
  aws generate architecture diagram: AWS Certified Security - Specialty Zeal Vora, 2019-06-10 AWS Certified Security - Specialty is one of the newest certifications launched by AWS and has gained a tremendous amount of popularity in the industry. This exam assesses the ability of experienced cloud security professionals to validate their knowledge on securing the AWS environments. The Security Specialty certification exam covers a wide range of topics which a Security professional would deal with, ranging from Incident response, security logging and monitoring, infrastructure security, identity and access management and data protection. This book acts as a detailed, dedicated study guide for those aiming to give the security specialty certification as well as for those who intend to master the security aspect of AWS. The book is based on the popular video course by Zeal Vora for the AWS Certified Security - Specialty certification and this book acts a standalone guide by itself as well as a supplement for those who have studied through the video course. Things you will learn: Understanding Incident Response process in Cloud environments. Implement Vulnerability Assessment & Patch Management activities with tools like Inspect and EC2 Systems Manager. Understanding stateful and stateless packet inspections firewalls. Implementing AWS WAF, Bastion Hosts, IPSec Tunnels, Guard Duty and others. Implement Centralized Control with AWS Organizations, Federations, Delegations. Understanding data-protection mechanisms with various techniques including KMS Envelope encryptions, ACM, and others. Important exam preparation pointers and review questions. Practical knowledge of AWS security services and features to provide a secure production environment.
  aws generate architecture diagram: Amazon Web Services: the Definitive Guide for Beginners and Advanced Users Parul Dubey, Arvind Kumar Tiwari, Rohit Raja, 2023-10-19 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.
  aws generate architecture diagram: Enterprise Internet of Things Handbook Arvind Ravulavaru, 2018-04-30 Get familiar with the building blocks of IoT solutions using off–the-shelf IoT platforms. Key Features Work with various trending IoT platforms such as AWS IoT, Azure IoT, Google IoT, IBM Watson IoT, and Kaa IoT Gain hands-on knowledge working with Cloud-based IoT platforms, IoT Analytics, and so on. A practical guide that will help you build IoT strategies for your organization Book Description There is a lot of work that is being done in the IoT domain and according to Forbes the global IoT market will grow from $157B in 2016 to $457B by 2020. This is an amazing market both in terms technology advancement as well as money. In this book, we will be covering five popular IoT platforms, namely, AWS IoT, Microsoft Azure IoT, Google IoT Core, IBM Watson IoT, and Kaa IoT middleware. You are going to build solutions that will use a Raspberry Pi 3, a DHT11 Temperature and humidity sensor, and a dashboard to visualize the sensor data in real-time. Furthermore, you will also explore various components of each of the platforms that are needed to achieve the desired solution. Besides building solutions, you will look at how Machine Learning and IoT go hand in hand and later design a simple predictive web service based on this concept. By the end of this book, you will be in a position to implement an IoT strategy best-fit for your organization What you will learn Connect a Temperature and Humidity sensor and see how these two can be managed from various platforms Explore the core components of AWS IoT such as AWS Kinesis and AWS IoTRules Engine Build a simple analysis dashboard using Azure IoT and Power BI Understand the fundamentals of Google IoT and use Google core APIs to build your own dashboard Get started and work with the IBM Watson IoT platform Integrate Cassandra and Zeppelin with Kaa IoT dashboard Review some Machine Learning and AI and get to know more about their implementation in the IoT domain. Who this book is for This book is targeted at IoT architects and engineers, or any stakeholders working with IoT solutions in an organization. This book will also help decision makers and professionals from small- and medium-sized enterprises build an IoT strategy for their venture.
  aws generate architecture diagram: AWS Automation Cookbook Nikit Swaraj, 2017-11-24 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.
  aws generate architecture diagram: Pioneering Enterprise Architecture: Transforming Global Enterprises Ashutosh Ahuja, 2024-10-19 In today’s rapidly evolving business landscape, organizations must leverage technology to stay competitive. Pioneering Enterprise Architecture is a comprehensive guide for technology leaders, architects, and decision-makers who want to master the art of aligning technology with business strategy. Drawing from years of hands-on experience, Ashutosh Ahuja shares practical insights, proven strategies, and real-world case studies that will help you navigate the complexities of modern digital transformations. From cloud migration and AI adoption to enterprise modernization and sustainability, this book equips you with the tools to design future-ready architectures that drive scalability and success. Whether you are looking to streamline operations, improve decision-making, or enhance the customer experience, this book offers the actionable advice you need to future-proof your organization. You’ll discover how to tackle the challenges of legacy systems, manage large-scale transformations, and implement architectural frameworks that empower your business to thrive in a digital-first world. Key topics include: Designing scalable, flexible, and resilient architectures. Navigating cloud migration and hybrid solutions. Implementing AI and machine learning for business innovation. Aligning technology initiatives with sustainability goals. Managing risk and enhancing cybersecurity with Zero Trust architecture. Building a successful enterprise architecture strategy for the future. If you’re ready to transform your organization through effective enterprise architecture, Pioneering Enterprise Architecture is your ultimate guide.
  aws generate architecture diagram: Real-Time Big Data Analytics Sumit Gupta, Shilpi,, 2016-02-26 Design, process, and analyze large sets of complex data in real time About This Book Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm Implement strategies to solve the challenges of real-time data processing Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn Explore big data technologies and frameworks Work through practical challenges and use cases of real-time analytics versus batch analytics Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm Handle and process real-time transactional data Optimize and tune Apache Storm for varied workloads and production deployments Process and stream data with Amazon Kinesis and Elastic MapReduce Perform interactive and exploratory data analytics using Spark SQL Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.
  aws generate architecture diagram: Natural Language Processing with AWS AI Services Mona M, Premkumar Rangarajan, Julien Simon, 2021-11-26 Work through interesting real-life business use cases to uncover valuable insights from unstructured text using AWS AI services Key FeaturesGet to grips with AWS AI services for NLP and find out how to use them to gain strategic insightsRun Python code to use Amazon Textract and Amazon Comprehend to accelerate business outcomesUnderstand how you can integrate human-in-the-loop for custom NLP use cases with Amazon A2IBook Description Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production. To start with, you'll understand the importance of NLP in today's business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic. Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications. What you will learnAutomate various NLP workflows on AWS to accelerate business outcomesUse Amazon Textract for text, tables, and handwriting recognition from images and PDF filesGain insights from unstructured text in the form of sentiment analysis, topic modeling, and more using Amazon ComprehendSet up end-to-end document processing pipelines to understand the role of humans in the loopDevelop NLP-based intelligent search solutions with just a few lines of codeCreate both real-time and batch document processing pipelines using PythonWho this book is for If you're an NLP developer or data scientist looking to get started with AWS AI services to implement various NLP scenarios quickly, this book is for you. It will show you how easy it is to integrate AI in applications with just a few lines of code. A basic understanding of machine learning (ML) concepts is necessary to understand the concepts covered. Experience with Jupyter notebooks and Python will be helpful.
  aws generate architecture diagram: Building Serverless Web Applications Diego Zanon, 2017-07-28 Build scalable, efficient, and highly available web apps using AWS About This Book Get an in-depth understanding of the serverless model Build a complete serverless web application end to end Learn how to use the Serverless Framework to improve your productivity Who This Book Is For If you're looking to learn more about scalable and cost-efficient architectures, this book is for you. Basic knowledge of Node.js skills or familiarity with cloud services is required. For other topics, we cover the basics. What You Will Learn Get a grasp of the pros and cons of going serverless and its use cases Discover how you can use the building blocks of AWS to your advantage Set up the environment and create a basic app with the Serverless Framework Host static files on S3 and CloudFront with HTTPS support Build a sample application with a frontend using React as an SPA Develop the Node.js backend to handle requests and connect to a SimpleDB database Secure your applications with authentication and authorization Implement the publish-subscribe pattern to handle notifications in a serverless application Create tests, define the workflow for deployment, and monitor your app In Detail This book will equip you with the knowledge needed to build your own serverless apps by showing you how to set up different services while making your application scalable, highly available, and efficient. We begin by giving you an idea of what it means to go serverless, exploring the pros and cons of the serverless model and its use cases. Next, you will be introduced to the AWS services that will be used throughout the book, how to estimate costs, and how to set up and use the Serverless Framework. From here, you will start to build an entire serverless project of an online store, beginning with a React SPA frontend hosted on AWS followed by a serverless backend with API Gateway and Lambda functions. You will also learn to access data from a SimpleDB database, secure the application with authentication and authorization, and implement serverless notifications for browsers using AWS IoT. This book will describe how to monitor the performance, efficiency, and errors of your apps and conclude by teaching you how to test and deploy your applications. Style and approach This book takes a step-by-step approach on how to use the Serverless Framework and AWS services to build Serverless Applications. It will give you a hands-on feeling, allowing you to practice while reading. It provides a brief introduction of concepts while keeping the focus on the practical skills required to develop applications.
  aws generate architecture diagram: Mastering GitLab 12 Joost Evertse, 2019-08-02 An expert guide to helping you use DevOps techniques with the latest GitLab version to optimize and manage your software workflow Key FeaturesDelve into GitLab's architecture, and install and configure it to fit your environmentLearn about the underlying principles of Agile software development and DevOpsExplore Gitlab's features to manage enterprise cloud-native applications and servicesBook Description GitLab is an open source repository management and version control toolkit with functions for enterprises and personal software projects. It offers configurability options, extensions, and APIs that make it an ideal tool for enterprises to manage the software development life cycle. This book begins by explaining GitLab options and the components of the GitLab architecture. You will learn how to install and set up GitLab on-premises and in the cloud, along with understanding how to migrate code bases from different systems, such as GitHub, Concurrent Versions System, Team Foundation Version Control, and Subversion. Later chapters will help you implement DevOps culture by introducing the workflow management tools in GitLab and continuous integration/continuous deployment (CI/CD). In addition to this, the book will guide you through installing GitLab on a range of cloud platforms, monitoring with Prometheus, and deploying an environment with GitLab. You'll also focus on the GitLab CI component to assist you with creating development pipelines and jobs, along with helping you set up GitLab runners for your own project. Finally, you will be able to choose a high availability setup that fits your needs and helps you monitor and act on results obtained after testing. By the end of this book, you will have gained the expertise you need to use GitLab features effectively, and be able to integrate all phases in the development process. What you will learnInstall GitLab on premises and in the cloud using a variety of configurationsConduct data migration from the SVN, TFS, CVS, and GitHub platforms to GitLabUse GitLab runners to develop different types of configurations in software developmentPlan and perform CI/CD by using GitLab featuresMonitor and secure your software architecture using Prometheus and GrafanaImplement DevOps culture by introducing workflow management tools in GitLabWho this book is for If you are a software developer, DevOps professional, or any developer who wants to master GitLab for productive repository management in your day-to-day tasks, this book is for you. Basic understanding of the software development workflow is assumed.
  aws generate architecture diagram: Optimizing Your Modernization Journey with AWS Mridula Grandhi, 2023-07-07 A strategic guide that will help you make key decisions related to cloud-based architectures, modernize your infrastructure and applications, and transform your business using AWS with real-world case studies Key Features Learn cloud migration and modernization strategies on AWS Innovate your applications, data, architecture and networking by adopting AWS Leverage AWS technologies with real world use-cases to implement cloud operations Purchase of the print or Kindle book includes a free eBook in the PDF format Book Description AWS cloud technologies help businesses scale and innovate, however, adopting modern architecture and applications can be a real challenge. This book is a comprehensive guide that ensures your switch to AWS services is smooth and hitch-free. It will enable you to make optimal decisions to bring out the best ROI from AWS cloud adoption. Beginning with nuances of cloud transformation on AWS, you'll be able to plan and implement the migration steps. The book will facilitate your system modernization journey by getting you acquainted with various technical domains, namely, applications, databases, big data, analytics, networking, and security. Once you've learned about the different operations, budgeting, and management best practices such as the 6 Rs of migration approaches and the AWS Well-Architected Framework, you'll be able to achieve operational excellence in cloud adoption. You'll also learn how to deploy some of the important AWS tools and services with real-life case studies and use cases. By the end of this book, you'll be able to successfully implement cloud migration and modernization on AWS and make decisions that best suit your organization. What you will learn Strategize approaches for cloud adoption and digital transformation Understand the catalysts for business reinvention Select the right tools for cloud migration and modernization processes Leverage the potential of AWS to maximize the value of cloud investments Understand the importance of implementing secure workloads on the cloud Explore AWS services such as computation, databases, security, and networking Implement various real-life use cases and technology case studies for modernization Discover the benefits of operational excellence on the cloud Who this book is for If you are a cloud enthusiast, solutions architect, enterprise technologist, or a C-suite executive and want to learn about the strategies and AWS services to transform your IT portfolio, this book is for you. Basic knowledge of AWS services and an understanding of technologies such as computation, databases, networking, and security will be helpful.
  aws generate architecture diagram: Generative AI on AWS Chris Fregly, Antje Barth, Shelbee Eigenbrode, 2023-11-13 Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock
  aws generate architecture diagram: Mastering AWS for Cloud Professionals Manjit Chakraborty, Neeraj Roy, 2024-11-08 DESCRIPTION Unlock the power of AWS and elevate your cloud expertise with Mastering AWS for Cloud Professionals. This comprehensive guide illuminates the path to cloud mastery, offering a blend of theoretical knowledge and practical expertise. Dive deep into Amazon Web Services (AWS), exploring its vast potential to revolutionize business operations and IT infrastructure. This book offers a visually enriched approach to learning AWS, using diagrams and illustrations to simplify complex concepts. Drawing from real-world experiences, it provides practical insights into implementing AWS in enterprise environments. Learn containerization through practical case studies and industry-proven methodologies, and master AWS monitoring tools for optimizing cloud-based applications and infrastructure. This comprehensive guide ensures a deep understanding of AWS solutions for practical use. With real-life scenarios and practical examples woven throughout, you will not only understand AWS solutions but will also be able to apply them effectively. You will be well-versed in leveraging AWS services to design, deploy, and manage secure, scalable, and cost-effective cloud solutions. You will understand how to optimize your cloud environment for performance and efficiency, ensuring your applications are always available and reliable. KEY FEATURES ● Comprehensive exploration of cloud computing principles and AWS-specific methodologies. ● Simplify complex AWS concepts with clear, visual diagrams and illustrations. ● Bridge the gap between theory and practice with industry-relevant architectures. WHAT YOU WILL LEARN ● Master AWS architectural fundamentals and build flexible, scalable cloud solutions. ● Design and deploy high-performance, globally distributed applications. ● Harness the power of containerization and serverless computing paradigms. ● Architect microservices and apply AWS Well-Architected Framework best practices. ● Leverage data analytics and machine learning capabilities in cloud environments. ● Secure, monitor, analyze, and optimize AWS deployments using native observability tools. WHO THIS BOOK IS FOR This book is tailored for a diverse audience of technology professionals, including cloud architects, system engineers, software developers, and IT operations specialists. This comprehensive guide serves as an excellent resource for those preparing for the AWS Solution Architect certification exam. TABLE OF CONTENTS 1. AWS Architectural Fundamentals 2. AWS Networking: Basic Constructs 3. AWS Networking: Advanced Constructs 4. AWS Compute 5. AWS Storage 6. AWS Database 7. Data Analytics 8. Containers in AWS ECS 9. Containers in AWS EKS 10. Microservices 11. ML and GenAI 12. Security in AWS 13. Observability in AWS
  aws generate architecture diagram: Time Series Analysis on AWS Michaël Hoarau, 2022-02-28 Leverage AWS AI/ML managed services to generate value from your time series data Key FeaturesSolve modern time series analysis problems such as forecasting and anomaly detectionGain a solid understanding of AWS AI/ML managed services and apply them to your business problemsExplore different algorithms to build applications that leverage time series dataBook Description Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes. The book begins with Amazon Forecast, where you'll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You'll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you'll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data. By the end of this AWS book, you'll have understood how to use the three AWS AI services effectively to perform time series analysis. What you will learnUnderstand how time series data differs from other types of dataExplore the key challenges that can be solved using time series dataForecast future values of business metrics using Amazon ForecastDetect anomalies and deliver forewarnings using Lookout for EquipmentDetect anomalies in business metrics using Amazon Lookout for MetricsVisualize your predictions to reduce the time to extract insightsWho this book is for If you're a data analyst, business analyst, or data scientist looking to analyze time series data effectively for solving business problems, this is the book for you. Basic statistics knowledge is assumed, but no machine learning knowledge is necessary. Prior experience with time series data and how it relates to various business problems will help you get the most out of this book. This guide will also help machine learning practitioners find new ways to leverage their skills to build effective time series-based applications.
  aws generate architecture diagram: The Machine Learning Solutions Architect Handbook David Ping, 2022-01-21 Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutions Key Features Explore different ML tools and frameworks to solve large-scale machine learning challenges in the cloud Build an efficient data science environment for data exploration, model building, and model training Learn how to implement bias detection, privacy, and explainability in ML model development Book DescriptionWhen equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one. You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. By the end of this book, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional. What you will learn Apply ML methodologies to solve business problems Design a practical enterprise ML platform architecture Implement MLOps for ML workflow automation Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using an AI service and a custom ML model Use AWS services to detect data and model bias and explain models Who this book is for This book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. You’ll need basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts before you get started with this handbook.
  aws generate architecture diagram: Implementing AWS: Design, Build, and Manage your Infrastructure Yohan Wadia, Rowan Udell, Lucas Chan, Udita Gupta, 2019-01-31 Work through exciting recipes to administer your AWS cloud Key FeaturesBuild secure environments using AWS components and servicesExplore core AWS features with real-world applications and best practicesDesign and build Lambda functions using real-world examplesBook Description With this Learning Path, you’ll explore techniques to easily manage applications on the AWS cloud. You’ll begin with an introduction to serverless computing, its advantages, and the fundamentals of AWS. The following chapters will guide you on how to manage multiple accounts by setting up consolidated billing, enhancing your application delivery skills, with the latest AWS services such as CodeCommit, CodeDeploy, and CodePipeline to provide continuous delivery and deployment, while also securing and monitoring your environment's workflow. It’ll also add to your understanding of the services AWS Lambda provides to developers. To refine your skills further, it demonstrates how to design, write, test, monitor, and troubleshoot Lambda functions. By the end of this Learning Path, you’ll be able to create a highly secure, fault-tolerant, and scalable environment for your applications. This Learning Path includes content from the following Packt products: AWS Administration: The Definitive Guide, Second Edition by Yohan WadiaAWS Administration Cookbook by Rowan Udell, Lucas ChanMastering AWS Lambda by Yohan Wadia, Udita GuptaWhat you will learnExplore the benefits of serverless computing and applicationsDeploy apps with AWS Elastic Beanstalk and Amazon Elastic File SystemSecure environments with AWS CloudTrail, AWSConfig, and AWS ShieldRun big data analytics with Amazon EMR and Amazon RedshiftBack up and safeguard data using AWS Data PipelineCreate monitoring and alerting dashboards using CloudWatchEffectively monitor and troubleshoot serverless applications with AWSDesign serverless apps via AWS Lambda, DynamoDB, and API GatewayWho this book is for This Learning Path is specifically designed for IT system and network administrators, AWS architects, and DevOps engineers who want to effectively implement AWS in their organization and easily manage daily activities. Familiarity with Linux, web services, cloud computing platforms, virtualization, networking, and other administration-related tasks will assist in understanding the concepts in the book. Prior hands-on experience with AWS core services such as EC2, IAM, S3, and programming languages, such as Node.Js, Java, and C#, will also prove beneficial.
  aws generate architecture diagram: Analytics for the Internet of Things (IoT) Andrew Minteer, 2017-07-24 Break through the hype and learn how to extract actionable intelligence from the flood of IoT data About This Book Make better business decisions and acquire greater control of your IoT infrastructure Learn techniques to solve unique problems associated with IoT and examine and analyze data from your IoT devices Uncover the business potential generated by data from IoT devices and bring down business costs Who This Book Is For This book targets developers, IoT professionals, and those in the field of data science who are trying to solve business problems through IoT devices and would like to analyze IoT data. IoT enthusiasts, managers, and entrepreneurs who would like to make the most of IoT will find this equally useful. A prior knowledge of IoT would be helpful but is not necessary. Some prior programming experience would be useful What You Will Learn Overcome the challenges IoT data brings to analytics Understand the variety of transmission protocols for IoT along with their strengths and weaknesses Learn how data flows from the IoT device to the final data set Develop techniques to wring value from IoT data Apply geospatial analytics to IoT data Use machine learning as a predictive method on IoT data Implement best strategies to get the most from IoT analytics Master the economics of IoT analytics in order to optimize business value In Detail We start with the perplexing task of extracting value from huge amounts of barely intelligible data. The data takes a convoluted route just to be on the servers for analysis, but insights can emerge through visualization and statistical modeling techniques. You will learn to extract value from IoT big data using multiple analytic techniques. Next we review how IoT devices generate data and how the information travels over networks. You'll get to know strategies to collect and store the data to optimize the potential for analytics, and strategies to handle data quality concerns. Cloud resources are a great match for IoT analytics, so Amazon Web Services, Microsoft Azure, and PTC ThingWorx are reviewed in detail next. Geospatial analytics is then introduced as a way to leverage location information. Combining IoT data with environmental data is also discussed as a way to enhance predictive capability. We'll also review the economics of IoT analytics and you'll discover ways to optimize business value. By the end of the book, you'll know how to handle scale for both data storage and analytics, how Apache Spark can be leveraged to handle scalability, and how R and Python can be used for analytic modeling. Style and approach This book follows a step-by-step, practical approach to combine the power of analytics and IoT and help you get results quickly
  aws generate architecture diagram: AWS Security Dylan Shields, 2022-09-20 Running your systems in the cloud doesn’t automatically make them secure. Learn the tools and new management approaches you need to create secure apps and infrastructure on AWS. Written by security engineer Dylan Shields, AWS Security provides comprehensive coverage on the key tools and concepts you can use to defend AWS-based systems. You’ll learn how to honestly assess your existing security protocols, protect against the most common attacks on cloud applications, and apply best practices to configuring identity and access management and virtual private clouds.
  aws generate architecture diagram: Pipeline as Code Mohamed Labouardy, 2021-11-23 Start thinking about your development pipeline as a mission-critical application. Discover techniques for implementing code-driven infrastructure and CI/CD workflows using Jenkins, Docker, Terraform, and cloud-native services. In Pipeline as Code, you will master: Building and deploying a Jenkins cluster from scratch Writing pipeline as code for cloud-native applications Automating the deployment of Dockerized and Serverless applications Containerizing applications with Docker and Kubernetes Deploying Jenkins on AWS, GCP and Azure Managing, securing and monitoring a Jenkins cluster in production Key principles for a successful DevOps culture Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You’ll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you’ll soon be delivering software that’s quicker to market, faster to deploy, and with less last-minute production bugs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems. Code-driven pipelines are easy to use, modify, and maintain, and your entire CI pipeline becomes more efficient because you directly interact with core components like Jenkins, Terraform, and Docker. About the book In Pipeline as Code you’ll learn to build reliable CI/CD pipelines for cloud-native applications. With Jenkins as the backbone, you’ll programmatically control all the pieces of your pipeline via modern APIs. Hands-on examples include building CI/CD workflows for distributed Kubernetes applications, and serverless functions. By the time you’re finished, you’ll be able to swap manual UI-based adjustments with a fully automated approach! What's inside Build and deploy a Jenkins cluster on scale Write pipeline as code for cloud-native applications Automate the deployment of Dockerized and serverless applications Deploy Jenkins on AWS, GCP, and Azure Grasp key principles of a successful DevOps culture About the reader For developers familiar with Jenkins and Docker. Examples in Go. About the author Mohamed Labouardy is the CTO and co-founder of Crew.work, a Jenkins contributor, and a DevSecOps evangelist. Table of Contents PART 1 GETTING STARTED WITH JENKINS 1 What’s CI/CD? 2 Pipeline as code with Jenkins PART 2 OPERATING A SELF-HEALING JENKINS CLUSTER 3 Defining Jenkins architecture 4 Baking machine images with Packer 5 Discovering Jenkins as code with Terraform 6 Deploying HA Jenkins on multiple cloud providers PART 3 HANDS-ON CI/CD PIPELINES 7 Defining a pipeline as code for microservices 8 Running automated tests with Jenkins 9 Building Docker images within a CI pipeline 10 Cloud-native applications on Docker Swarm 11 Dockerized microservices on K8s 12 Lambda-based serverless functions PART 4 MANAGING, SCALING, AND MONITORING JENKINS 13 Collecting continuous delivery metrics 14 Jenkins administration and best practices
Knowledge Graphs and GraphRAG with AWS and Neo4j
Nov 26, 2024 · This reference architecture demonstrates how AWS services and Neo4j can be used to create knowledge graphs. Those graphs can then be used in a GraphRAG …

Guidance for High-Speed RAG Chatbots on AWS
This architecture diagram shows how to build an artificial intelligence (AI)-powered chatbot that lets you ask questions based on content in your PDF files in natural language. Once you …

Amazon Web Services (AWS) - Sparx Systems
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Guidance for Bringing Your Own Machine Learning Models …
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AWS Connected Vehicle Reference Architecture
AWS Connected Vehicle Reference Architecture Publication date: January 17, 2024 (Diagram history) This architecture enables you to use AWS IoT Core to modernize workloads, process …

Guidance for Conversational Chatbots Using Retrieval …
This architecture diagram demonstrates how to implement a Retrieval Augmented Generation (RAG) workflow by combining the capabilities of Amazon Kendra with large language models …

Modernize Applications with Microservices Using Amazon EKS
Modernize Applications with Microservices Using Amazon EKS Publication date: July 24, 2023 (Diagram history) This architecture enables you to integrate Amazon Elastic Kubernetes …

Presentation - pages.awscloud.com
By leveraging a process called Retrieval Augmented Generation (RAG), vector databases can help keep LLMs accurate while allowing all reasoning to happen in the model. Improve time-to …

Guidance for Generative AI Model Optimization Using …
This architecture diagram shows how data scientists can optimize Large Language Models (LLMs) within Amazon SageMaker to deliver responses that are not only faster, but also more …

Guidance for Automating Networking Monitoring and …
This architecture diagram illustrates the high-level automation process of deploying Amazon CloudWatch dashboards for network monitoring and alerting. The subsequent slides provide …

Near Real-Time IoT Analytics with AWS and
This architecture demonstrates how to build near real-time IOT analytics with machine learning by using IBM Cloud Pak for DATA (CP4D) running on AWS. Data from multiple sources across …

AWS Cloud Architecture Guide - docs.commvault.com
The guide covers several common use cases for protecting AWS compute and container-based resources, cloud databases, and storage services. This guide also addresses how to …

AWS Serverless Multi-Tier Architectures
Oct 20, 2021 · This whitepaper illustrates how innovations from Amazon Web Services (AWS) can be used to change the way you design multi-tier architectures and implement popular …

AWS Well-Architected Framework
By using the Framework you will learn architectural best practices for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. It provides a way for you to …

Smart Farm on AWS - Smart Farm on AWS Architecture
This Connected Farm reference architecture enables sensors, computer vision, and edge inference in agriculture by focusing on ensuring scalability, elasticity, and a responsiveness for …

Guidance for Automating Tasks Using Agents for Amazon …
This architecture diagram demonstrates how to use Agents and Knowledge Bases for Amazon Bedrock to build on existing enterprise resources and automate tasks, such as filing a new …

Modern Data Analytics Reference Architecture on AWS
May 31, 2022 · Modern Data Analytics Reference Architecture on AWS Diagram Publication date: May 31, 2022 (Diagram history) This architecture enables customers to build data analytics …

Guidance for Building Custom Chatbots for Order …
This architecture diagram shows how to build a serverless, scalable generative AI chatbot using both Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock.

How to Design a Least Privilege Architecture in AWS
Setting up and configuring multi-account architecture has long been considered challenging and complicated, especially for large organizations. A sample multi-account framework to start …

Knowledge Graphs and GraphRAG with AWS and Neo4j
Nov 26, 2024 · This reference architecture demonstrates how AWS services and Neo4j can be used to create knowledge graphs. …

Guidance for High-Speed RAG Chatbots on AWS
This architecture diagram shows how to build an artificial intelligence (AI)-powered chatbot that lets you ask questions based on …

Amazon Web Services (AWS) - Sparx Systems
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Generative AI Application Builder on AWS - Implementation Guide
This implementation guide provides an overview of the Generative AI Application Builder on AWS solution, its reference …

Guidance for Bringing Your Own Machine Learning Models into A…
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