Free Amazon Web Services SAP-C02 Practice Exam with Questions & Answers | Set: 6

The best solution is to upload files from the mobile software directly to Amazon S3, use S3 event notifications to create a message in an Amazon Simple Queue Service (Amazon SQS) standard queue, and invoke an AWS Lambda function to perform image processing when a message is available in the queue. This solution will ensure that image processing can scale to handle the load, as Amazon S3 can store any amount of data and handle concurrent uploads, Amazon SQS can buffer the messages and deliver them reliably, and AWS Lambda can run code without provisioning or managing servers and scale automatically based on the demand. This solution will also notify the user when processing is complete by sending a push notification to the mobile app using Amazon Simple Notification Service (Amazon SNS), which is a web service that enables applications to send and receive notifications from the cloud. This solution is more cost-effective than using Amazon MQ, which is a managed message broker service for Apache ActiveMQ that requires a dedicated broker instance, or S3 Batch Operations, which is a feature that allows users to perform bulk actions on S3 objects, such as copying or tagging, but does not support custom code execution. This solution is also more suitable than using Amazon Simple Email Service (Amazon SES), which is a web service that enables applications to send and receive email messages, but does not support push notifications for mobile devices. References: Amazon S3 Documentation, Amazon SQS Documentation, AWS Lambda Documentation, Amazon SNS Documentation

The best option is to use an Auto Scaling group, a Network Load Balancer, Amazon Route 53, and Amazon DynamoDB to create a scalable, highly available, and low-latency online game application. An Auto Scaling group can automatically adjust the number of EC2 instances based on the demand and traffic in each Region. A Network Load Balancer can distribute the incoming traffic across the EC2 instances and handle millions of requests per second. Amazon Route 53 can use latency-based routing to direct the users to the Region that provides the best performance. Amazon DynamoDB global tables can replicate the game metadata across multiple Regions, ensuring consistency and availability of thedata. This approach minimizes the operational overhead and cost, as it leverages fully managed services and avoids custom logic or replication.

Option A is not optimal because using an EC2 Spot Fleet can introduce the risk of losing the EC2 instances if the Spot price exceeds the bid price, which can affect the availability and performance of the game. Using AWS Global Accelerator can improve the network performance, but it is not necessary if Amazon Route 53 can already route the users to the closest Region. Using Amazon RDS for MySQL can store the game metadata, but it requires setting up read replicas and managing the replication lag across Regions, which can increase the complexity and cost.

Option B is not optimal because using geoproximity routing can direct the users to the Region that is geographically closer, but it does not account for the network latency or performance. Using MySQL databases on EC2 instances can store the game metadata, but it requires managing the EC2 instances, the database software, the backups, the patches, and the replication across Regions, which can increase the operational overhead and cost.

Option D is not optimal because using EC2 Global View is not a valid service. Using a custom DNS server on an EC2 instance can redirect the user to the Region that provides the lowest latency, but it requires developing and maintaining the custom logic, as well as managing the EC2 instance, which can increase the operational overhead and cost. Using Amazon Aurora global database can store the game metadata, but it is more expensive and complex than using Amazon DynamoDB global tables.

Auto Scaling groups

Network Load Balancer

Amazon Route 53

Amazon DynamoDB global tables

This option uses the S3 Storage Lens default dashboard to track bucket and encryption metrics across two AWS Regions. S3 Storage Lens is a feature that provides organization-wide visibility into object storage usage and activity trends, and delivers actionable recommendations to improve cost-efficiency and apply data protection best practices. S3 Storage Lens delivers more than 30 storage metrics, including metrics on encryption, replication, and data protection. The default dashboard provides a summary of the entire S3 usage and activity across all Regions and accounts in an organization. The company can give the compliance teams access to the dashboard directly in the S3 console, which requires the least operational overhead.

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The best option is to use Amazon SQS and AWS Lambda to create a serverless order processing application. Amazon SQS is a fully managed message queue service that can decouple the order receiving and processing components, making the application more scalable and fault-tolerant. AWS Lambda is a serverless compute service that can automatically scale to handle the incoming messages from the SQS queue and process them according to the business logic. AWS Lambda can also integrate with Amazon DynamoDB to store the processed orders in a fast and flexible NoSQL database. This approach eliminates the need to provision, manage, or scale any servers or containers, and reduces the operational overhead and cost.

Option A is not reliable because using an EC2-hosted database to receive the orders introduces a single point of failure and a scalability bottleneck. EC2 instances also require more management and configuration than serverless services.

Option C is not reliable because using AWS Step Functions to receive the orders adds unnecessary complexity and cost to the application. AWS Step Functions is a service that coordinates multiple AWS services into a serverless workflow, but it is not designed to handle high-volume, sporadic, or unpredictable traffic patterns. AWS Step Functions also charges per state transition, which can be expensive for a large number of orders. Launching an ECS container to process each order also requires more resources and management than invoking a Lambda function.

Option D is not reliable because using Amazon Kinesis Data Streams to receive the orders is not suitable for this use case. Amazon Kinesis Data Streams is a service that enables real-time processing of streaming data at scale, but it is not meant for asynchronous message queuing. Amazon Kinesis Data Streams requires consumers to poll the data from the stream, which can introduce latency and complexity. Amazon Kinesis Data Streams also charges per shard hour, which can be expensive for a sporadic traffic pattern.

Amazon SQS

AWS Lambda

Amazon DynamoDB

AWS Step Functions

Amazon ECS

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 use of provisioned concurrency ensures the web application’s Lambda functions have pre-initialized execution environments, removing cold start latency and maintaining performance during high-traffic periods.

Route 53 health checks and failover records automate DNS failover to the secondary Region, improving application availability and reliability.

The CloudWatch alarm is configured to monitor the Lambda ConcurrentExecutions metric and send an SNS notification if concurrency usage nears the limit, enabling quick operational response.

This approach minimizes manual management, ensuring reliability and performance during peak traffic while meeting best practices for AWS Lambda and Route 53 failover.

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Option A is correct because placing the EC2 instances behind an Application Load Balancer (ALB) and associating an SSL certificate from AWS Certificate Manager (ACM) with the ALB enables encryption in transit between the client and the ALB. Exporting the SSL certificate and installing it on each EC2 instance enables encryption in transit between the ALB and the web server. Configuring the ALB to listen on port 443 and to forward traffic to port 443 on the instances ensures that HTTPS is used for both connections. This solution achieves end-to-end encryption in transit for the web application12

Using AWS Backup to create a scheduled daily backup plan for the EC2 instances will enable taking snapshots of the EC2 instances and their attached EBS volumes1. Configuring the backup task to copy the backups to a vault in the secondary Region will enable maintaining backups in a separate Region1. In the event of a failure, launching the CloudFormation template will enable deploying the network configuration in the secondary Region2. Restoring the instance volumes and configurations from the backup vault will enable recovering the EC2 instances and their data1. Transferring usage to the secondary Region will enable resuming operations2.

The company has many S3 buckets and many identities across multiple AWS accounts. It currently uses S3 bucket policies for granular authorization. As requirements grow, the bucket policies have become very large and have hit the maximum size limits. The company needs a way to express granular, identity-based access to S3 resources without relying on increasingly complex bucket policies.

AWS provides S3 Access Grants to centrally manage S3 data access based on identities. S3 Access Grants integrate with IAM Identity Center and external identity providers such as Microsoft Entra ID (formerly Azure AD). With S3 Access Grants, you define grants that associate specific identities or groups (from IAM Identity Center) with permissions on specific S3 buckets, prefixes, or objects. Access Grants maintain a mapping between identities and S3 resources without requiring large, per-bucket policies.

Option A describes exactly this approach. You create an S3 Access Grant configuration associated with the IAM Identity Center instance that is already integrated with the company’s IdP. You then define S3 Access Grants for the various user groups according to business requirements, specifying the appropriate S3 buckets and prefixes. When users access S3 through AWS tools that support S3 Access Grants, temporary credentials are issued that reflect the grants. This centralizes authorization management, reduces the size and complexity of S3 bucket policies, and minimizes operational overhead because you manage permissions per identity group rather than constantly editing long bucket policies.

Option B uses S3 access points and Object Lambda Access Points with a Lambda function for data filtering. This is more suitable for content transformation or redaction rather than primary authorization management. It adds operational complexity by requiring custom Lambda code and Object Lambda configuration, and it does not directly solve the problem of large bucket policies for fine-grained permissions.

Option C uses per-bucket S3 access points with attached policies. While access points can simplify some aspects of access control and allow per-application policies, using many access points with detailed policies can still lead to significant policy complexity. It also does not take advantage of the existing IAM Identity Center integration and does not centrally align permissions with identity groups.

Option D uses AWS Organizations service control policies (SCPs). SCPs are intended to define high-level guardrails and maximum permissions at the account or organizational unit level, not detailed, per-bucket or per-prefix access control for individual users or groups. Using SCPs to express granular S3 bucket permissions would be complex, hard to maintain, and not aligned with the purpose of SCPs.

Therefore, using S3 Access Grants integrated with IAM Identity Center (option A) provides a centralized, identity-aware, low-overhead way to manage granular S3 access without hitting S3 bucket policy size limits.

D is correct because thehealth check grace perioddefines how long Auto Scaling waits after launching an instance before checking its health status. With the larger content added to the S3 bucket, the instance initialization (via user data) is taking longer. Increasing the grace period allows the instance time to complete startup tasks before it’s marked as unhealthy.

Option A would not necessarily reduce startup time — the issue is likely network latency or the size of the content.

Option B only affects the timeout for health check responses, not the delay before they begin.

Option C is not applicable unless the health check path itself is invalid (which isn't mentioned).