AWS8-containers

You are working as a Solutions Architect for a company that is migrating its containerized applications to AWS. The company has decided to use Amazon Elastic Container Registry (ECR) to store and manage their Docker container images. You need to ensure that the container images are securely stored and accessed within the AWS environment. Which of the following approaches would you recommend to achieve this goal?

• A. Create a public ECR repository and grant access to all authenticated AWS users.
• B. Create a private ECR repository and configure IAM policies to control access to the repository.
• C. Create a public ECR repository and use AWS Secrets Manager to store and manage the access credentials.
• D. Create a private ECR repository and use AWS Key Management Service (KMS) to encrypt the container images.

Answer explanation

A. "Incorrect. Creating a public ECR repository and granting access to all authenticated AWS users would not provide secure storage and access for the container images. Public repositories are accessible to anyone with an AWS account, which is not a secure approach for sensitive or proprietary container images." B. "Correct. Creating a private ECR repository and configuring IAM policies to control access is the recommended approach for securely storing and accessing container images within the AWS environment. IAM policies allow you to grant or restrict access to specific users, groups, or roles, ensuring that only authorized entities can access the repository." C. "Incorrect. While AWS Secrets Manager is a service for securely storing and managing secrets (such as passwords, API keys, and other sensitive data), it is not the recommended approach for controlling access to ECR repositories. IAM policies are the preferred method for managing access to ECR repositories." D. "Incorrect. While AWS Key Management Service (KMS) can be used to encrypt container images stored in ECR, it does not directly address the requirement of controlling access to the repository. KMS is a service for managing encryption keys, but access control to ECR repositories is typically handled through IAM policies."

You are working as a Solutions Architect for a company that runs a containerized application on Amazon Elastic Container Service (ECS). The application consists of multiple microservices, each running in its own container. The company wants to ensure that the containers are distributed across multiple Availability Zones (AZs) for high availability and fault tolerance. Which of the following strategies should you implement to achieve this requirement?

• A. Create an ECS cluster with multiple container instances spread across multiple AZs, and configure the service to use the Spread deployment type.
• B. Create multiple ECS clusters, one in each AZ, and deploy the services across these clusters.
• C. Create an ECS cluster with multiple container instances in a single AZ, and configure the service to use the Binpack deployment type.
• D. Create an ECS cluster with a single container instance, and configure the service to use the Daemon deployment type.

Answer explanation

A. Correct. Creating an ECS cluster with multiple container instances spread across multiple Availability Zones (AZs) and configuring the service to use the Spread deployment type ensures that the containers are distributed evenly across the AZs. This strategy provides high availability and fault tolerance by ensuring that if one AZ fails, the application can continue running in the other AZs. B. Incorrect. Creating multiple ECS clusters, one in each AZ, and deploying the services across these clusters is not a recommended approach. It increases the complexity of managing multiple clusters and can lead to inefficient resource utilization. Additionally, it does not guarantee that the containers will be distributed evenly across the AZs. C. Incorrect. Creating an ECS cluster with multiple container instances in a single AZ and configuring the service to use the Binpack deployment type does not provide high availability or fault tolerance across multiple AZs. The Binpack deployment type packs containers into the fewest possible instances, which can lead to all containers running in a single AZ, defeating the purpose of distributing them across multiple AZs. D. Incorrect. Creating an ECS cluster with a single container instance and configuring the service to use the Daemon deployment type is not suitable for distributing containers across multiple AZs. The Daemon deployment type ensures that a single instance of the task runs on each active container instance in the cluster, which does not provide high availability or fault tolerance across multiple AZs.

A company is planning to migrate their on-premises applications to Amazon Elastic Kubernetes Service (EKS). They have the following requirements: 1. Ensure high availability and fault tolerance for their Kubernetes control plane. 2. Automatically scale the number of worker nodes based on application demand. 3. Secure their Kubernetes cluster with industry-standard best practices. 4. Integrate their existing monitoring and logging tools with the Kubernetes cluster. Which of the following approaches should the Solutions Architect recommend to meet these requirements?

• A. Deploy a single-node EKS cluster in a single Availability Zone, configure Auto Scaling for worker nodes, enable AWS CloudTrail for auditing, and use Amazon CloudWatch for monitoring and logging.
• B. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Control Tower for security best practices, and use Amazon CloudWatch for monitoring and logging.
• C. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Fargate for serverless compute, and use Amazon CloudWatch for monitoring and logging.
• D. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Managed Microsoft AD for RBAC, and integrate with third-party monitoring and logging tools.

Answer explanation

A. "Incorrect. Deploy a single-node EKS cluster in a single Availability Zone, configure Auto Scaling for worker nodes, enable AWS CloudTrail for auditing, and use Amazon CloudWatch for monitoring and logging." Explanation: This option does not meet the requirement of high availability and fault tolerance for the Kubernetes control plane, as it deploys a single-node EKS cluster in a single Availability Zone. B. "Correct. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Control Tower for security best practices, and use Amazon CloudWatch for monitoring and logging." Explanation: This option meets all the requirements: 1. It deploys a multi-node EKS cluster across multiple Availability Zones, ensuring high availability and fault tolerance for the Kubernetes control plane. 2. It configures Auto Scaling for worker nodes, allowing automatic scaling based on application demand. 3. It enables AWS Control Tower, which provides a landing zone for setting up a secure, multi-account AWS environment following best practices. 4. It uses Amazon CloudWatch for monitoring and logging, allowing integration with existing tools. C. "Incorrect. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Fargate for serverless compute, and use Amazon CloudWatch for monitoring and logging." Explanation: While this option meets most of the requirements, it does not address the requirement of securing the Kubernetes cluster with industry-standard best practices. D. "Incorrect. Deploy a multi-node EKS cluster across multiple Availability Zones, configure Auto Scaling for worker nodes, enable AWS Managed Microsoft AD for RBAC, and integrate with third-party monitoring and logging tools." Explanation: This option meets the requirements of high availability, auto-scaling, and integrating with existing monitoring and logging tools. However, it does not address the requirement of securing the Kubernetes cluster with industry-standard best practices.

A company is planning to migrate their on-premises applications to a containerized environment on AWS using Kubernetes. They have the following requirements: 1. High availability and fault tolerance for the Kubernetes control plane. 2. Automatic scaling of worker nodes based on resource utilization. 3. Secure communication between the control plane and worker nodes. 4. Integration with AWS services for logging, monitoring, and load balancing. Which of the following AWS services would you recommend for deploying and managing the Kubernetes cluster?

• A. Amazon Elastic Kubernetes Service (EKS)
• B. Amazon Elastic Container Service (ECS)
• C. AWS Fargate
• D. Amazon Elastic Compute Cloud (EC2) with self-managed Kubernetes

Answer explanation

A. Correct. Amazon Elastic Kubernetes Service (EKS) is a fully managed Kubernetes service provided by AWS. It meets all the requirements mentioned in the question: 1. EKS provides high availability and fault tolerance for the Kubernetes control plane by running it across multiple Availability Zones. 2. EKS supports automatic scaling of worker nodes based on resource utilization using the Cluster Autoscaler. 3. EKS ensures secure communication between the control plane and worker nodes using mutual TLS authentication. 4. EKS integrates with other AWS services like CloudWatch for monitoring, AWS Load Balancer for load balancing, and CloudTrail for logging. B. Incorrect. Amazon Elastic Container Service (ECS) is a container orchestration service provided by AWS, but it does not use Kubernetes. The question specifically mentions the requirement of using Kubernetes. C. Incorrect. AWS Fargate is a serverless compute engine for running containers, but it does not provide a managed Kubernetes service. Fargate can be used as a worker node for an EKS cluster, but it does not meet the requirement of deploying and managing the Kubernetes control plane. D. Incorrect. While it is possible to deploy and manage a self-hosted Kubernetes cluster on Amazon Elastic Compute Cloud (EC2) instances, it requires significant effort in setting up and maintaining the control plane and worker nodes. The question specifically asks for a managed Kubernetes service, which is not the case with a self-managed Kubernetes cluster on EC2.

You are working as a Solutions Architect for a company that is migrating its application workloads to AWS. One of the applications is a containerized microservices-based application that needs to be deployed on a serverless container orchestration service. The application has varying traffic patterns, and you want to ensure that the infrastructure scales automatically based on the demand. Which AWS service would you recommend for deploying this application?

• A. AWS Fargate
• B. Amazon Elastic Container Service (Amazon ECS) with EC2 instances
• C. Amazon Elastic Kubernetes Service (Amazon EKS)
• D. AWS Lambda

Answer explanation

A. Correct. AWS Fargate is a serverless container orchestration service that allows you to run containerized applications without managing the underlying infrastructure. It automatically scales the infrastructure based on the demand, making it a suitable choice for deploying a containerized microservices-based application with varying traffic patterns. B. Incorrect. Amazon Elastic Container Service (Amazon ECS) with EC2 instances requires you to manage the underlying EC2 instances, which goes against the requirement of a serverless container orchestration service that scales automatically based on demand. C. Incorrect. Amazon Elastic Kubernetes Service (Amazon EKS) is a managed Kubernetes service, but it still requires you to manage the underlying worker nodes (EC2 instances or Fargate). While it can scale automatically, it is not a serverless container orchestration service like AWS Fargate. D. Incorrect. AWS Lambda is a serverless compute service for running functions, not for deploying containerized applications. It is not suitable for deploying a microservices-based application.

You are working as a Solutions Architect for a company that is migrating its application workloads to AWS. One of the applications is a containerized microservices architecture that needs to be deployed on a serverless compute platform. The application requires high availability and scalability, and you want to minimize the operational overhead of managing the underlying infrastructure. Which AWS service would you recommend for deploying the containerized microservices application?

• A. AWS Fargate
• B. AWS Lambda
• C. Amazon EC2 Container Service (ECS)
• D. Amazon Elastic Kubernetes Service (EKS)

Answer explanation

A. Correct. AWS Fargate is a serverless compute engine for containers that allows you to run containerized applications without having to manage the underlying infrastructure. It works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS), providing a serverless option for running containers in a highly available and scalable manner. Fargate eliminates the need to provision and manage servers, allowing you to focus on building and deploying your applications. B. Incorrect. AWS Lambda is a serverless compute service for running code without provisioning or managing servers. While Lambda is suitable for event-driven, short-lived functions, it is not designed for running containerized microservices applications that require long-running processes or complex architectures. C. Incorrect. Amazon Elastic Container Service (ECS) is a fully managed container orchestration service that allows you to run and manage containerized applications on AWS. However, ECS requires you to provision and manage the underlying EC2 instances or use AWS Fargate for a serverless experience. While ECS can be used to deploy containerized microservices, it does not provide a fully serverless compute platform as described in the question. D. Incorrect. Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service that allows you to run and manage Kubernetes clusters on AWS. While EKS can be used to deploy containerized microservices applications, it requires you to provision and manage the underlying EC2 instances or use AWS Fargate for a serverless experience. EKS itself does not provide a fully serverless compute platform as described in the question.

A company is planning to migrate its monolithic application to a microservices architecture using containers. They want to ensure that the containers are highly available, scalable, and can be easily managed. Which AWS service would you recommend for deploying and managing the containerized microservices?

• A. AWS Elastic Beanstalk
• B. AWS Elastic Container Service (ECS)
• C. AWS Elastic Kubernetes Service (EKS)
• D. AWS Lambda

Answer explanation

A. AWS Elastic Beanstalk Incorrect. AWS Elastic Beanstalk is a service for deploying and scaling web applications and services developed with various programming languages and platforms. While it can be used to deploy containerized applications, it is not specifically designed for managing and orchestrating containerized microservices at scale. B. AWS Elastic Container Service (ECS) Correct. AWS Elastic Container Service (ECS) is a highly scalable and high-performance container orchestration service that supports Docker containers. It allows you to run and manage containerized applications across a cluster of Amazon EC2 instances. ECS provides features like load balancing, service discovery, and automatic scaling, making it a suitable choice for deploying and managing containerized microservices with high availability and scalability requirements. C. AWS Elastic Kubernetes Service (EKS) Correct. AWS Elastic Kubernetes Service (EKS) is a managed Kubernetes service that makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS. Kubernetes is a popular open-source container orchestration platform that provides advanced features for managing containerized microservices, including automatic scaling, load balancing, self-healing, and rolling updates. EKS simplifies the process of setting up and managing Kubernetes clusters on AWS, making it a suitable choice for deploying and managing containerized microservices. D. AWS Lambda Incorrect. AWS Lambda is a serverless computing service that allows you to run code without provisioning or managing servers. While Lambda can be used in conjunction with containerized microservices for certain use cases, such as event-driven functions or API gateways, it is not a container orchestration service designed for deploying and managing containerized microservices at scale.