Free Practice Questions for Amazon Web Services SAP-C02 Exam

Using an Amazon Kinesis data stream as a target for the IoT Core rule ensures durable and scalable buffering of data during traffic spikes.

An ECS Fargate application reads data from Kinesis, processes it, and stores it in Aurora, meeting the requirement for flexible, serverless data handling.

This solution guarantees no data loss while providing real-time or near-real-time data processing capabilities.

https://aws.amazon.com/solutions/implementations/disaster-recovery-for-aws-iot/

Option A is incorrect because creating an SCP to set a fixed monthly account usage limit is not possible. SCPs are policies that specify the services and actions that users and roles can use in the member accounts of an AWS Organization. SCPscannot enforce budget limits or prevent users from launching costly services or running services unnecessarily1

Option B is correct because using AWS Budgets to create a fixed monthly budget for each developer’s account as part of the account creation process meets the requirement of giving developers a fixed monthly budget to limit their AWS costs. AWS Budgets allows you to plan your service usage, service costs, and instance reservations. You can create budgets that alert you when your costs or usage exceed (or are forecasted to exceed) your budgeted amount2

Option C is correct because creating an SCP to deny access to costly services and components meets the requirement of ensuring that developers are not launching costly services or running services unnecessarily. SCPs can restrict access to certain AWS services or actions based on conditions such as region, resource tags, or request time. For example, an SCP can deny access to Amazon Redshift clusters or Amazon EC2 instances with certain instance types1

Option D is incorrect because creating an IAM policy to deny access to costly services and components is not sufficient to meet the requirement of ensuring that developers are not launching costly services or running services unnecessarily. IAM policies can only control access to resources within a single AWS account. If developers have multiple accounts or can create new accounts, they can bypass the IAMpolicy restrictions. SCPs can apply across multiple accounts within an AWS Organization and prevent users from creating new accounts that do not comply with the SCP rules3

Option E is incorrect because creating an AWS Budgets alert action to terminate services when the budgeted amount is reached is not possible. AWS Budgets alert actions can only perform one of the following actions: apply an IAM policy, apply an SCP, or send a notification through Amazon SNS.AWS Budgets alert actions cannot terminate services directly.

Option F is correct because creating an AWS Budgets alert action to send an Amazon SNS notification when the budgeted amount is reached and invoking an AWS Lambda function to terminate all services meets the requirement of giving developers a fixed monthly budget to limit their AWS costs. AWS Budgets alert actions can send notifications through Amazon SNS when a budget threshold is breached. Amazon SNS can trigger an AWS Lambda function that can perform custom logic such as terminating all services in the developer’s account. This way, developers cannot exceed their budget limit and incur additional costs.

The company needs centralized traffic inspection and centralized internet access for multiple workload VPCs connected by a transit gateway. The standard AWS hub-and-spoke pattern for centralized inspection is to use an inspection VPC that hosts network virtual appliances behind a Gateway Load Balancer, and to steer traffic from spoke VPCs through the transit gateway to the inspection VPC. Gateway Load Balancer endpoints are used to privately connect VPCs to the GWLB, allowing traffic to be transparently redirected to the appliances for inspection without changing application configurations.

To ensure symmetric routing for stateful inspection (so that return traffic traverses the same appliance path), appliance mode is enabled on the transit gateway attachment that connects to the inspection VPC. Appliance mode is specifically used with transit gateways and third-party appliances to preserve flow symmetry and avoid asymmetric routing issues.

Option D matches the centralized model: it creates a dedicated inspection VPC that contains the GWLB, endpoints, and the inspection appliance. It updates workload VPC routes to send traffic to the transit gateway and configures the transit gateway route tables to forward relevant traffic to the GWLB endpoints in the inspection VPC. Enabling appliance mode on the transit gateway is the key operational setting to maintain symmetric routing through the appliance fleet for inspected traffic.

Option A is incorrect because it places the inspection components inside an existing workload VPC rather than using a centralized inspection VPC. This increases coupling, makes the architecture harder to manage, and does not match the typical centralized inspection pattern. It also references enabling appliance mode on the GWLB, whereas appliance mode is a transit gateway attachment feature used for routing symmetry with appliances, not a setting “on the GWLB” itself.

Option B is incorrect because it splits the GWLB and endpoints/appliances across different workload VPCs, which complicates the design and is not the intended GWLB pattern. GWLB endpoints are created in VPCs that need to send traffic to the GWLB service; the appliances sit behind the GWLB in the provider/inspection VPC. The option also refers to enabling appliance mode on endpoints, but the appliance mode setting is associated with the transit gateway attachment.

Option C is incorrect because VPC flow logs are for logging and visibility; flow logs do not route traffic. Also, separating “inspection VPC” and “internet access VPC” with the appliances in the internet VPC does not align with the standard GWLB centralized inspection architecture and introduces unnecessary complexity.

Therefore, creating a dedicated inspection VPC with GWLB and endpoints and enabling appliance mode on the transit gateway attachment is the correct centralized approach.

This solution allows for deploying the Lambda function and API Gateway endpoint to another region, providing a failover option in case of any issues in the primary region. Using Route 53 ' s failover routing policy allows for automatic routing of traffic to the healthy endpoint, ensuring that the application is available even in case of issues in one region. This solution provides a cost-effective and simple way to implement failover while minimizing operational overhead.

The combination of changes that will meet the requirement with the least operational overhead are:

A. Deploy the API to multiple Regions. Configure Amazon Route 53 with custom domain names that route traffic to each Regional API endpoint.Implement a Route 53 multivalue answer routing policy.

B. Create a new KMS multi-Region customer managed key. Create a new KMS customer managed replica key in each in-scope Region.

C. Replicate the existing Secrets Manager secret to other Regions. For each in-scope Region’s replicated secret, select the appropriate KMS key.

These changes will enable the company to have an active-active configuration for its API across multiple Regions, while minimizing the complexity and cost of managing the secrets and keys.

A. This change will allow the company to use Route 53 to distribute traffic across multiple Regional API endpoints, based on the availability and latency of each endpoint.This will improve the performance and availability of the API for global customers12

B. This change will allow the company to use KMS multi-Region keys, which are KMS keys in different Regions that can be used interchangeably.This will simplify the encryption and decryption of secrets across Regions, as the same key material and key ID can be used in any Region34

C. This change will allow the company to use Secrets Manager replication, which replicates the encrypted secret data and metadata across the specified Regions.This will ensure that the secrets are consistent and accessible in any Region, andthat any update made to the primary secret will be propagated to the replica secrets automatically56

The company should configure Amazon FSx for Lustre with an import and export policy. The company should link the new file system to an S3 bucket. The company should install the Lustre client and mount the document store to an Amazon EC2 instance by using NFS. This solution will meet the requirements with the least amount of effort because Amazon FSx for Lustre is a fully managed service that provides a high-performance filesystem optimized for fast processing of workloads such as machine learning, highperformance computing, video processing, financial modeling, and electronic design automation1. Amazon FSx for Lustre can be linked to an S3 bucket and can import data from and export data to the bucket2. The import and export policy can be configured to automatically import new or changed objects from S3 and export new or changed files to S33. This will ensure that the files are available to the public for download within 30 minutes. Amazon FSx for Lustre supports NFS version 3.0 protocol for Linux clients.

The other options are not correct because:

Migrating the application to an AWS Lambda function would require a lot of effort and may not be feasible for the existing server that generates many documents. Lambda functions have limitations on execution time, memory, disk space, and network bandwidth.

Setting up an Amazon S3 File Gateway would not work because S3 File Gateway does not support write-back caching, which means that files written to the file share are uploaded to S3 immediately and are not available locally until they are downloaded again. This would not provide fast local access to the files that the server generates and modifies.

Configuring AWS DataSync to connect to an Amazon EC2 instance would not meet the requirement of making the files available to the public for download within 30 minutes. DataSync is a service that transfers data between on-premises storage systems and AWS storage services over the internet or AWS Direct Connect. DataSync tasks can be scheduled to run at specific times or intervals, but they are not triggered by file changes.

For collecting data from remote sensors without internet connectivity, using an AWS Snowcone device with an Amazon EC2 instance running an FTP server presents a practical solution. This setup allows the sensors to upload data to the EC2 instance via FTP, and after the experiment, the Snowcone device can be returned to AWS for data ingestion into Amazon S3. This approach minimizes operational complexity and ensures efficient data transfer to AWS for further processing or storage.

AWS Documentation on AWS Snowcone and Amazon EC2 provides detailed guidance on deploying compute and storage capabilities in edge locations. This solutionleverages AWS ' s edge computing devices to address challenges associated with data collection in remote or disconnected environments.

AWS Global Accelerator is a service that directs traffic to optimal endpoints (in this case, the Application Load Balancer) based on the health of the endpoints and network routing. It allows you to create an accelerator that directs traffic to multiple endpoint groups, one for each Region where the application is deployed. The accelerator uses the AWS global network to optimize the traffic routing to the healthy endpoint.

By using Global Accelerator, the company can use a single static IP address for the apex domain, and traffic will be directed to the optimal endpoint based on the user ' s location, without the need for additional load balancers or routing policies.

Amazon Simple Notification Service (Amazon SNS) is a fully managed pub/sub messaging service that enables users to send messages to multiple subscribers1. Users can sendevent details to an Amazon SNS topic and configure an AWS Lambda function as a subscriber to the SNS topic to process the events. Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources2. Users can add an on-failure destination to the function and set an Amazon Simple Queue Service (Amazon SQS) queue as the target. Amazon SQS is a fully managed message queuing service that enables users to decouple and scale microservices, distributed systems, and serverless applications3. This way, if a processing error occurs, the event will move into the separate queue for review.

Option B is incorrect because publishing events to an Amazon SQS queue and creating an Amazon EC2 Auto Scaling group will not have the ability to scale in and out based on the number of events that the solution receives. Amazon EC2 is a web service that provides secure, resizable compute capacity in the cloud. Auto Scaling is a feature that helps users maintain application availability and allows them to scale their EC2 capacity up or down automatically according to conditions they define. However, for this use case, using SQS and EC2 will not take advantage of the serverless capabilities of Lambda and SNS.

Option C is incorrect because writing events to an Amazon DynamoDB table and configuring a DynamoDB stream for the table will not have the ability to move events into a separate queue for review if a processing error occurs. Amazon DynamoDB is a fully managed key-value and document database that delivers single-digit millisecond performance at any scale. DynamoDB Streams is a feature that captures data modification events in DynamoDB tables. Users can configure the stream to invoke a Lambda function, but they cannot configure an on-failure destination for the function.

Option D is incorrect because publishing events to an Amazon EventBridge event bus and setting an Application Load Balancer (ALB) as the event bus target will not have the ability to move events into a separate queue for review if a processing error occurs. Amazon EventBridge is a serverless event bus service that makes it easy to connect applications with data from a variety of sources. An ALB is a load balancer that distributes incoming application traffic across multiple targets, such as EC2 instances, containers, IP addresses, Lambda functions, and virtual appliances. Users can configure EventBridge to retry events, but they cannot configure an on-failure destination for the ALB.

The company should create a Network Load Balancer (NLB) and associate it with one static IP address in multiple Availability Zones. The company should also create an ALB-type target group for the NLB and add the existing ALB. The company should add the NLB IP addresses to the firewall appliance and update the clients to connect to the NLB. This solution will allow traffic flow to AWS from the on-premises network by using static IP addresses that can be added to the firewall appliance’s allow list. The NLB will forward requests to the ALB, which will use path-based routing to forward requests to the target groups.

According to the AWS documentation1, AWS App2Container (A2C) is a command line tool for migrating and modernizing Java and .NET web applications into container format. AWS A2C analyzes and builds an inventory of applications running in bare metal, virtual machines, Amazon Elastic Compute Cloud (EC2) instances, or in the cloud. You can use AWS A2C to generate container images for your applications and deploy them on Amazon ECS or Amazon EKS.

Option A meets the requirements of the scenario because it allows you to migrate your existing Java application to AWS and minimize the administrative overhead to maintain the servers. You can use AWS A2C to analyze your application dependencies, extract application artifacts, and generate a Dockerfile. You can then store your container images in Amazon ECR, which is a fully managed container registry service. You can use AWS Fargate as the launch type for your Amazon ECS cluster, which is a serverless compute engine that eliminates the need to provision and manage servers for your containers. You can grant the ECS task execution role permission to access the ECR image repository, which allows your tasks to pull images from ECR. You can configure Amazon ECS to use an ALB, whichis a load balancer that distributes traffic across multiple targets in multiple Availability Zones using HTTP or HTTPS protocols. You can use the ALB to interact with your application.

They all mention using spot instances and EKS based on EC2. A spot instance is not appropriate for a production server and the company is developing new application designed for AWS Fargate, which means we must plan the future cost improvement including AWS Fargate. https://aws.amazon.com/savingsplans/compute-pricing/