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As container technologies steadily gained in popularity, there was an increasing need for a platform to orchestrate their deployment and monitor their execution. Multiple platforms exist to fulfill this role, but Kubernetes has become the de-facto standard. Every major cloud provider offers a hosted Kubernetes solution, and on AWS, that service is called Elastic Kubernetes Service (EKS). Kubernetes is only part of the solution. The Docker images deployed to a Kubernetes cluster are hosted in a Docker registry. In AWS, the Elastic Container Registry (ECR) provides a service for hosting Docker images. Combining ECR and EKS provides a complete Kubernetes solution for running containerized applications at scale. In this book, we document the process of creating a Node.js Docker image, pushing it to ECR, and deploying it to EKS.

Accelerate your business growth by employing Terraform for AWS projects with this comprehensive guide packed with practical implementation tips for start-ups, enterprises, and personal projects Key Features Learn Terraform on AWS from 12x AWS certified trainer Improve reusability and governance for large-scale Terraform projects Use infrastructure as code practices to fully automate AWS workloads Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionInfrastructure as code (IaC) and Terraform have become essential tools for managing cloud infrastructure and automating deployment processes. Mastering Terraform on AWS presents a step-by-step approach on how to master these tools and build a secure and scalable AWS infrastructure. The book starts with an introduction to patterns and anti-patterns of IaC and Terraform, explaining the common mistakes and pitfalls you must avoid. You’ll then learn about the importance of planning and designing infrastructure projects in AWS and making informed decisions for projects in AWS Terraform. You’ll find out how to implement Terraform in your projects and deploy serverless projects. Next, you’ll be able to deploy containers in AWS with Terraform, exploring the best practices for Terraform IaC projects. You’ll understand how you can leverage Terraform for enterprises, build Git workflows for IaC and Terraform projects, and automate deployment of Terraform projects. The last set of chapters will teach you how to govern AWS with Terraform and build a secure infrastructure. Finally, you’ll discover how to achieve a perfect AWS infrastructure with Terraform. By the end of this book, you’ll have gained a comprehensive understanding of the various aspects of Terraform and IaC, along with the knowledge required to build, manage, and deploy complex infrastructures on AWS.What you will learn Get to grips with Terraform frameworks and best practices Use Terraform providers and modules Develop your first AWS resource in Terraform Build an infrastructure project with Terraform Govern an infrastructure project in Terraform Deploy Terraform projects to AWS with CI/CD Who this book is for This book is for cloud and DevOps engineers, developers, and architects responsible for writing or designing infrastructure as code to deploy resources in AWS. You are expected to have a basic understanding of AWS and should have experience deploying resources through the user interface (UI).

Start deploying, managing, and scaling containerized applications into AWS container infrastructure using Docker on Amazon EC2, Amazon Elastic Container Service (ECS), and AWS Elastic Kubernetes Service (EKS). This step by step practical book will cover all the available container services on AWS and review the usage of each one based on your required scale and cost. Further, you will see how to set up each environment and finally deploy, manage, and scale containerized applications on each one. In the chapter about Elastic Kubernetes Service (EKS), you will learn the process of building and managing Kubernetes clusters on AWS and see how to provision hosts in a matter of minutes, while deploying containers in seconds and making them available globally. Deploy Containers on AWS shows you how to get started with AWS container offerings and manage production or test environments of containerized applications using a hands-on approach with step-by-step instructions. What You Will LearnDeploy and manage containers with Docker on Amazon EC2Store and retrieve container images using the Amazon EC2 container registryOrchestrate containers with Amazon Elastic Container Service (ECS)Run Kubernetes-managed infrastructure on AWS (EKS)Monitor, manage, back up, and restore containers on AWS Who This Book Is ForDevelopers, cloud and systems administrators, and architects

Learn how to deploy and test Linux-based Docker containers with the help of real-world use cases Key FeaturesUnderstand how to make a deployment workflow run smoothly with Docker containersLearn Docker and DevOps concepts such as continuous integration and continuous deployment (CI/CD)Gain insights into using various Docker tools and librariesBook Description Docker is the de facto standard for containerizing apps, and with an increasing number of software projects migrating to containers, it is crucial for engineers and DevOps teams to understand how to build, deploy, and secure Docker environments effectively. Docker for Developers will help you understand Docker containers from scratch while taking you through best practices and showing you how to address security concerns. Starting with an introduction to Docker, you'll learn how to use containers and VirtualBox for development. You'll explore how containers work and develop projects within them after you've explored different ways to deploy and run containers. The book will also show you how to use Docker containers in production in both single-host set-ups and in clusters and deploy them using Jenkins, Kubernetes, and Spinnaker. As you advance, you'll get to grips with monitoring, securing, and scaling Docker using tools such as Prometheus and Grafana. Later, you'll be able to deploy Docker containers to a variety of environments, including the cloud-native Amazon Elastic Kubernetes Service (Amazon EKS), before finally delving into Docker security concepts and best practices. By the end of the Docker book, you'll be able to not only work in a container-driven environment confidently but also use Docker for both new and existing projects. What you will learnGet up to speed with creating containers and understand how they workPackage and deploy your containers to a variety of platformsWork with containers in the cloud and on the Kubernetes platformDeploy and then monitor the health and logs of running containersExplore best practices for working with containers from a security perspectiveBecome familiar with scanning containers and using third-party security tools and librariesWho this book is for If you're a software engineer new to containerization or a DevOps engineer responsible for deploying Docker containers in the cloud and building DevOps pipelines for container-based projects, you'll find this book useful. This Docker containers book is also a handy reference guide for anyone working with a Docker-based DevOps ecosystem or interested in understanding the security implications and best practices for working in container-driven environments.

This book is designed to introduce you to using containers and Kubernetes for full-stack development. You'll learn how to develop a full-stack application using Node.js and MongoDB and how to and manage them using Docker, then Docker Compose, and finally Kubernetes.

Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.

This effective self-study system delivers complete coverage of every topic on the AWS Certified Developer Associate Exam Take the challenging AWS Certified Developer Associate Exam with confidence using the comprehensive information contained in this effective test preparation guide. Written by an Amazon Web Services certified expert and experienced trainer, AWS Certified Developer Associate All-in-One Exam Guide (Exam DVA-C01) covers every subject on the exam and clearly explains how to create, deploy, migrate, monitor, and debug cloud-native applications. Designed to help you pass the exam with ease, this guide also serves as an ideal on-the-job reference. Covers all topics on the exam, including: Getting started with AWS Journey AWS high availability and fault tolerance Working with cloud storage Authentication and authorization Creating SQL and NoSQL databases in AWS Cloud AWS application integration and management Developing cloud-native applications in AWS Building, deploying, and debugging cloud applications Electronic content includes: 130 practice questions Test engine containing full-length practice exams and customizable quizzes

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.