Amazon Web Services SAP-C02 Exam Questions Free Practice Test

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Questions # 46:

A company has an organization in AWS Organizations that includes a separate AWS account for each of the company ' s departments. Application teams from different

departments develop and deploy solutions independently.

The company wants to reduce compute costs and manage costs appropriately across departments. The company also wants to improve visibility into billing for individual departments. The company does not want to lose operational flexibility when the company selects compute resources.

Which solution will meet these requirements?

Options:

Use AWS Budgets for each department. Use Tag Editor to apply tags to appropriate resources. Purchase EC2 Instance Savings Plans.

Configure AWS Organizations to use consolidated billing. Implement a tagging strategy that identifies departments. Use SCPs to apply tags to appropriateresources. Purchase EC2 Instance Savings Plans.

Configure AWS Organizations to use consolidated billing. Implement a tagging strategy that identifies departments. Use Tag Editor to apply tags to appropriate resources. Purchase Compute Savings Plans.

Use AWS Budgets for each department. Use SCPs to apply tags to appropriate resources. Purchase Compute Savings Plans.

Expert Solution

Questions # 47:

Question:

An application uses CloudFront, App Runner, and two S3 buckets — one for static assets and one for user-uploaded content. User content is infrequently accessed after 30 days. Users are located only in Europe.

How can the companyoptimize cost?

Options:

Expire S3 objects after 30 days.

Transition S3 content toGlacier Deep Archiveafter 30 days.

Use Spot Instances with App Runner.

Add auto scaling to Aurora read replica.

UseCloudFront Price Class 200(Europe and U.S. only).

Expert Solution

Questions # 48:

A company hosts an application on AWS. The application reads and writes objects that are stored in a single Amazon S3 bucket. The company must modify the application to deploy the application in two AWS Regions.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Set up an Amazon CloudFront distribution with the S3 bucket as an origin. Deploy the application to a second Region Modify the application to use the CloudFront distribution. Use AWS Global Accelerator to access the data in the S3 bucket.

Create a new S3 bucket in a second Region. Set up bidirectional S3 Cross-Region Replication (CRR) between the original S3 bucket and the new S3 bucket. Configure an S3 Multi-Region Access Point that uses both S3 buckets. Deploy a modified application to both Regions.

Create a new S3 bucket in a second Region Deploy the application in the second Region. Configure the application to use the new S3 bucket. Set up S3 Cross-Region Replication (CRR) from the original S3 bucket to the new S3 bucket.

Set up an S3 gateway endpoint with the S3 bucket as an origin. Deploy the application to a second Region. Modify the application to use the new S3 gateway endpoint. Use S3 Intelligent-Tiering on the S3 bucket.

Expert Solution

Questions # 49:

Question:

A company runs production workloads on EC2 On-Demand Instances and RDS for PostgreSQL. They want to reduce costs without compromising availability or capacity.

Options:

Use CUR and Lambda to terminate underutilized instances. Buy Savings Plans.

Use Budgets and Trusted Advisor, then manually terminate and buy RIs.

UseCompute OptimizerandTrusted Advisorfor recommendations. Apply rightsizing, auto scaling, and purchase a Compute Savings Plan.

Use Cost Explorer, alerts, and replace with Spot Instances.

Expert Solution

Questions # 50:

A large company runs workloads in VPCs that are deployed across hundreds of AWS accounts. Each VPC consists to public subnets and private subnets that span across multiple Availability Zones. NAT gateways are deployed in the public subnets and allow outbound connectivity to the internet from the private subnets.

A solutions architect is working on a hub-and-spoke design. All private subnets in the spoke VPCs must route traffic to the internet through an egress VPC. The solutions architect already has deployed a NAT gateway in an egress VPC in a central AWS account.

Which set of additional steps should the solutions architect take to meet these requirements?

Options:

Create peering connections between the egress VPC and the spoke VPCs. Configure the required routing to allow access to the internet.

Create a transit gateway, and share it with the existing AWS accounts. Attach existing VPCs to the transit gateway Configure the required routing to allow access to the internet.

Create a transit gateway in every account. Attach the NAT gateway to the transit gateways. Configure the required routing to allow access to the internet.

Create an AWS PrivateLink connection between the egress VPC and the spoke VPCs. Configure the required routing to allow access to the internet

Expert Solution

Questions # 51:

A company needs to monitor a growing number of Amazon S3 buckets across two AWS Regions. The company also needs to track the percentage of objects that are

encrypted in Amazon S3. The company needs a dashboard to display this information for internal compliance teams.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Create a new S3 Storage Lens dashboard in each Region to track bucket and encryption metrics. Aggregate data from both Region dashboards into a singledashboard in Amazon QuickSight for the compliance teams.

Deploy an AWS Lambda function in each Region to list the number of buckets and the encryption status of objects. Store this data in Amazon S3. Use AmazonAthena queries to display the data on a custom dashboard in Amazon QuickSight for the compliance teams.

Use the S3 Storage Lens default dashboard to track bucket and encryption metrics. Give the compliance teams access to the dashboard directly in the S3console.

Create an Amazon EventBridge rule to detect AWS Cloud Trail events for S3 object creation. Configure the rule to invoke an AWS Lambda function to recordencryption metrics in Amazon DynamoDB. Use Amazon QuickSight to display the metrics in a dashboard for the compliance teams.

Expert Solution

Questions # 52:

A solutions architect needs to advise a company on how to migrate its on-premises data processing application to the AWS Cloud. Currently, users upload input files through a web portal. The web server then stores the uploaded files on NAS and messages the processing server over a message queue. Each media file can take up to 1 hour to process. The company has determined that the number of media files awaiting processing is significantly higher during business hours, with the number of files rapidly declining after business hours.

What is the MOST cost-effective migration recommendation?

Options:

Create a queue using Amazon SQS. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in an Amazon S3 bucket.

Create a queue using Amazon M. Configure the existing web server to publish to the new queue. When there are messages in the queue, create a new Amazon EC2 instance to pull requests from the queue and process the files. Store the processed files in Amazon EFS. Shut down the EC2 instance after the task is complete.

Create a queue using Amazon MO. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in Amazon EFS.

Create a queue using Amazon SOS. Configure the existing web server to publish to the new queue. Use Amazon EC2 instances in an EC2 Auto Scaling group to pull requests from the queue and process the files. Scale the EC2 instances based on the SOS queue length. Store the processed files in an Amazon S3 bucket.

Expert Solution

Questions # 53:

A company plans to migrate a three-tiered web application from an on-premises data center to AWS The company developed the Ui by using server-side JavaScript libraries The business logic and API tier uses a Python-based web framework The data tier runs on a MySQL database

The company custom built the application to meet business requirements The company does not want to re-architect the application The company needs a solution to replatform the application to AWS with the least possible amount of development The solution needs to be highly available and must reduce operational overhead

Which solution will meet these requirements?

Options:

Deploy the UI to a static website on Amazon S3 Use Amazon CloudFront to deliver the website Build the business logic in a Docker image Store the image in AmazonElastic Container Registry (Amazon ECR) Use Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to host the website with an Application Load Balancer in front Deploy the data layer to an Amazon Aurora MySQL DB cluster

Build the UI and business logic in Docker images Store the images in Amazon Elastic Container Registry (Amazon ECR) Use Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to host the UI and business logic applications with an Application LoadBalancer in front Migrate the database to an Amazon RDS for MySQL Multi-AZ DB instance

Deploy the UI to a static website on Amazon S3 Use Amazon CloudFront to deliver the website Convert the business logic to AWS Lambda functions Integrate the functions with Amazon API Gateway Deploy the data layer to an Amazon Aurora MySQL DB cluster

Build the UI and business logic in Docker images Store the images in Amazon Elastic Container Registry (Amazon ECR) Use Amazon Elastic Kubernetes Service(Amazon EKS) with Fargate profiles to host the UI and business logic Use AWS Database Migration Service (AWS DMS) to migrate the data layer to Amazon DynamoDB

Expert Solution

Questions # 54:

A company processes environment data. The has a set up sensors to provide a continuous stream of data from different areas in a city. The data is available in JSON format.

The company wants to use an AWS solution to send the data to a database that does not require fixed schemas for storage. The data must be send in real time.

Which solution will meet these requirements?

Options:

Use Amazon Kinesis Data Firehouse to send the data to Amazon Redshift.

Use Amazon Kinesis Data streams to send the data to Amazon DynamoDB.

Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to send the data to Amazon Aurora.

Use Amazon Kinesis Data firehouse to send the data to Amazon Keyspaces (for Apache Cassandra).

Expert Solution

Questions # 55:

A global ecommerce company has many data centers around the world. With the growth of its stored data, the company needs to set up a solution to provide scalable storage for legacy on-premises file applications. The company must be able to take point-in-time copies of volumes by using AWS Backup and must retain low-latency access to frequently accessed data. The company also needs to have storage volumes that can be mounted as Internet Small Computer System Interface (iSCSI) devices from the company ' s on-premises application servers.

Which solution will meet these requirements?

Options:

Provision an AWS Storage Gateway tape gateway. Configure the tape gateway to store data in anAmazon S3 bucket. Deploy AWS Backup to take point-in-time copies of the volumes.

Provision an Amazon FSx File Gateway and an Amazon S3 File Gateway. Deploy AWS Backup to take point-in-time copies of the data.

Provision an AWS Storage Gateway volume gateway in cache mode. Back up the on-premises Storage Gateway volumes with AWS Backup.

Provision an AWS Storage Gateway file gateway in cache mode. Deploy AWS Backup to take point-in-time copies of the volumes.

Expert Solution

Questions # 56:

A delivery company needs to migrate its third-party route planning application to AWS. The third party supplies a supported Docker image from a public registry. The image can run in as many containers as required to generate the route map.

The company has divided the delivery area into sections with supply hubs so that delivery drivers travel the shortest distance possible from the hubs to the customers. To reduce the time necessary to generate route maps, each section uses its own set of Docker containers with a custom configuration that processes orders only in the section ' s area.

The company needs the ability to allocate resources cost-effectively based on the number of running containers.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster on Amazon EC2. Use the Amazon EKS CLI to launch the planning application in pods by using the -tags option to assign a custom tag to the pod.

Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster on AWS Fargate. Use the Amazon EKS CLI to launch the planning application. Use the AWS CLI tag-resource API call to assign a custom tag to the pod.

Create an Amazon Elastic Container Service (Amazon ECS) cluster on Amazon EC2. Use the AWS CLI with run-tasks set to true to launch the planning application by using the -tags option to assign a custom tag to the task.

Create an Amazon Elastic Container Service (Amazon ECS) cluster on AWS Fargate. Use the AWS CLI run-task command and set enableECSManagedTags to true to launch the planning application. Use the --tags option to assign a custom tag to the task.

Expert Solution

Questions # 57:

A company has developed an application that is running Windows Server on VMware vSphere VMs that the company hosts on premises The application data is stored in a proprietary format that must be read through the application The company manually provisioned the servers and the application

As part of its disaster recovery plan, the company wants the ability to host its application on AWS temporarily if the company ' s on-premises environment becomes unavailable The company wants the application to return to on-premises hosting after a disaster recovery event is complete The RPO is 5 minutes.

Which solution meets these requirements with the LEAST amount of operational overhead?

Options:

Configure AWS DataSync Replicate the data to Amazon Elastic Block Store (Amazon EBS) volumes When the on-premises environment is unavailable, use AWS Cloud Format ion templates to provision Amazon EC2 instances and attach the EBS volumes

Configure AWS Elastic Disaster Recovery Replicate the data to replication Amazon EC2 instances that are attached to Amazon Elastic Block Store (Amazon EBS) volumes When the on-premises environment is unavailable use Elastic Disaster Recovery to launch EC2 instances that use the replicated volumes

Provision an AWS Storage Gateway file gateway. Replicate the data to an Amazon S3 bucket When the on-premises environment is unavailable, use AWS Backup to restore the data to Amazon Elastic Block Store (Amazon EBS) volumes and launch Amazon EC2 instances from these EBS volumes

Provision an Amazon FSx for Windows File Server file system on AWS Replicate the data to the file system When the on-premises environment is unavailable, use AWS Cloud Format ion templates to provision Amazon EC2 instances and use AWS CloudFormation Init commands to mount the Amazon FSx file shares

Expert Solution

Questions # 58:

A company is using Amazon SageMaker A1 Notebook Instances and SageMaker APIs to train machine learning (ML) models. The SageMaker A1 Notebook Instances are deployed in a VPC that does not have access to or from the internet. Datasets for ML model training are stored in an Amazon S3 bucket. Interface VPC endpoints provide access to Amazon S3 and the SageMaker APIs.

Occasionally, data scientists require access to a private Git repository to update application packages that they use as part of their workflow. The company must provide access to the Git repository while ensuring that the SageMaker A1 Notebook Instances remain isolated from the internet.

Which solution meets these requirements with the LEAST operational overhead?

Options:

Add the Git repository as a resource for SageMaker by referencing the remote URL. Configure AWS Secrets Manager to use Git credentials to access the repository.

Add the Git repository as a resource for SageMaker by referencing the remote URL. Add the username to the URL that is required to access the repository.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet. Configure network ACL rules that allow the SageMaker A1 Notebook Instances access to only the Git repository URL.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet with a network ACL that allows access to only the Git repository URL.

Expert Solution

Answer

Explanation

The key requirement is to provide access to a private Git repository while keeping the SageMaker notebook instances isolated from the internet. The environment is intentionally configured without internet access, and connectivity to AWS services is provided through VPC endpoints. Introducing a NAT gateway and routing to the internet would violate the requirement to keep the notebook instances isolated from the internet, and network ACLs cannot reliably restrict outbound access by URL or domain name because NACLs operate at the IP and port level and do not provide DNS-aware URL filtering.

SageMaker supports integrating Git repositories so that notebooks can pull code directly as part of the workflow. When using a private repository, credentials must be handled securely. Using AWS Secrets Manager to store and reference Git credentials allows authentication without embedding usernames and passwords in code or URLs and without granting broad network access. This approach meets the requirement with low operational overhead because it relies on managed SageMaker Git integration and managed secret storage rather than custom networking controls.

Option A uses SageMaker’s Git repository integration with the remote URL and stores credentials in AWS Secrets Manager. This allows notebooks to access the private repository in a controlled, auditable way while preserving the “no internet access” posture of the VPC design (because it does not require adding a NAT gateway or public routes).

Option B is not appropriate because embedding credentials (even just usernames) in URLs is not a secure or robust credential management practice. It also does not solve private authentication in a secure manner and can lead to credential leakage through logs or configuration.

Options C and D are not correct because they require adding a NAT gateway and routing to the internet. That directly conflicts with the requirement that SageMaker notebook instances remain isolated from the internet. Additionally, the proposed restriction mechanism is invalid: network ACLs cannot restrict traffic to a specific URL. They only allow/deny traffic based on IP addresses, ports, and protocols. A Git repository can resolve to multiple IPs, can change IPs, and can use CDNs, making NACL-based IP allowlisting brittle and operationally heavy.

Therefore, integrating the Git repository with SageMaker and using Secrets Manager for credentials is the best solution with the least operational overhead while maintaining internet isolation.

[References:AWS documentation on SageMaker notebook Git repository integration for pulling code from remote repositories.AWS documentation on AWS Secrets Manager for secure storage and retrieval of credentials used by applications and workflows.AWS networking documentation describing that network ACLs operate on IP/port rules and do not support URL-based filtering, and that adding NAT gateway enables internet egress from private subnets., , , , , ]

Questions # 59:

A software as a service (SaaS) company has developed a multi-tenant environment. The company uses Amazon DynamoDB tables that the tenants share tor the storage layer. The company uses AWS Lambda functions for the application services.

The company wants to offer a tiered subscription model that is based on resource consumption by each tenant Each tenant is identified by a unique tenant ID that is sent as part of each request to the Lambda functions The company has created an AWS Cost and Usage Report (AWS CUR) in an AWS account The company wants to allocate the DynamoDB costs to each tenant to match that tenant " s resource consumption

Which solution will provide a granular view of the DynamoDB cost for each tenant with the LEAST operational effort?

Options:

Associate a new lag that is named tenant ID with each table in DynamoDB Activate the tag as a cost allocation tag m the AWS Billing and Cost Management console Deploy new Lambda function code to log the tenant ID in Amazon CloudWatch Logs Use the AWS CUR to separate DynamoDB consumption cost for each tenant ID

Configure the Lambda functions to log the tenant ID and the number of RCUs and WCUs consumed from DynamoDB for each transaction to Amazon CloudWatch Logs Deploy another Lambda function to calculate the tenant costs by using the logged capacity units and the overall DynamoDB cost from the AWS Cost Explorer API Create an Amazon EventBridge rule to invoke the calculation Lambda function on a schedule.

Create a new partition key that associates DynamoDB items with individual tenants Deploy a Lambda function to populate the new column as part of each transaction Deploy another Lambda function to calculate the tenant costs by using Amazon Athena to calculate the number of tenant items from DynamoDB and the overall DynamoDB cost from the AWS CUR Create an Amazon EventBridge rule to invoke the calculation Lambda function on a schedule

Deploy a Lambda function to log the tenant ID the size of each response, and the duration of the transaction call as custom metrics to Amazon CloudWatch Logs Use CloudWatch Logs Insights to query the custom metrics for each tenant. Use AWS Pricing Calculator to obtain the overall DynamoDB costs and to calculate the tenant costs

Expert Solution

Questions # 60:

A company runs a website on Amazon ECS containers that use the AWS Fargate launch type. The company configures AWS Application Auto Scaling by using a target tracking scaling policy. The company sets the request count as the scaling metric. An Application Load Balancer (ALB) serves traffic to the ECS containers. The website serves images on request and resizes the images to a predefined size to match the viewers ' screens. After the website resizes an image, the website caches the image locally in a container and serves subsequent requests from the cache.

During periods of high traffic, the company observed that images load slowly and with high latency. The company wants to minimize the latency to serve images.

Which solution will meet this requirement with the LEAST operational overhead?

Options:

Create a new Amazon CloudFront distribution and an Amazon S3 bucket. Set the ALB as one origin for the distribution and the S3 bucket as a second origin. Configure a cache behavior that routes image requests to the S3 origin, and configure a default cache behavior for the ALB origin. Pre-scale all images and upload the images to the S3 bucket.

Create an Amazon ElastiCache (Memcached) cluster. Update the application to read and write the resized images to the ElastiCache (Memcached) cluster by using the image name and size as the key.

Create an Amazon Aurora cluster and an Amazon S3 bucket. Update the application to store resized images in the S3 bucket and to store a cache key in the Aurora cluster. Configure the application to load the cache key from the Aurora cluster and to serve images from the S3 bucket.

Create an Amazon API Gateway HTTP API and enable API request caching. Replace the ALB with the HTTP API and remove the local caching in the application code.

Expert Solution

Answer

Explanation

The core issue is high latency when serving images during traffic spikes. The current design resizes images dynamically and caches them locally inside ECS containers. With AWS Fargate, containers are ephemeral and scale in and out based on load. Local container caches are not shared across tasks, so cache hit rates drop during scaling events, forcing repeated image resizing. This increases CPU usage, startup latency, and response times under load.

The lowest operational overhead and most effective solution is to offload image delivery entirely from the application layer and use edge caching. Amazon CloudFront is designed to cache static content at edge locations close to end users, dramatically reducing latency and backend load. Amazon S3 is a durable, highly scalable object store that is well suited for serving static assets such as images.

Option A moves image delivery to a CloudFront + S3 architecture. By pre-scaling images and storing them in S3, the application no longer performs on-demand image resizing during requests. CloudFront caches the images at edge locations, so subsequent requests are served directly from the edge with minimal latency. The ALB remains the origin for dynamic content, while image requests are routed to the S3 origin using cache behaviors. This approach is fully managed, highly scalable, and requires minimal changes to the application logic once images are pre-generated.

Option B introduces ElastiCache, which adds operational overhead and complexity. The application must manage cache keys, eviction, and failure scenarios. ElastiCache is better suited for low-latency data access patterns rather than large static objects like images, and it does not provide global edge caching.

Option C adds unnecessary complexity by introducing an Aurora database as part of the caching layer. Databases are not designed to manage cache metadata for static assets at scale, and this design increases operational overhead without improving latency compared to CloudFront.

Option D is not appropriate because API Gateway caching is intended for API responses, not for efficient delivery of large static binary objects such as images. Replacing the ALB with API Gateway also introduces request size, payload, and cost considerations and does not provide global edge caching comparable to CloudFront for image delivery.

Therefore, using Amazon CloudFront with Amazon S3 for pre-scaled images provides the lowest latency, highest scalability, and least operational overhead.

[References:AWS documentation on Amazon CloudFront for low-latency delivery of static content through global edge caching.AWS documentation on Amazon S3 as a scalable origin for static assets and integration with CloudFront.AWS best practices for separating static content delivery from dynamic application workloads to reduce backend load and improve performance., , , , , ]

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