SAP-C02 Design for New Solutions Practice Test 19 — 15 Questions

Question 1

A solutions architect is designing a disaster recovery plan for a critical application. The application runs on EC2 instances behind an Application Load Balancer (ALB) in us-east-1. The recovery time objective (RTO) is 15 minutes, and the recovery point objective (RPO) is 1 hour. Which approach meets these requirements?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use a warm standby: maintain a scaled-down copy of the environment in us-west-2 that can be scaled up within 15 minutes.. A warm standby strategy meets the RTO of 15 minutes and RPO of 1 hour by maintaining a scaled-down copy of the environment in us-west-2 that can be rapidly scaled up to full production capacity. This approach ensures data replication (e.g., using Amazon RDS cross-Region replication or EBS snapshots) meets the 1-hour RPO, while the pre-provisioned but smaller infrastructure allows scaling within the 15-minute RTO, unlike a pilot light which requires more time to provision resources.

Answer

Use backup and restore: take hourly snapshots of EBS volumes and copy to us-west-2, then restore EC2 instances from snapshots.

Answer

Implement a pilot light strategy: replicate data to us-west-2 and keep a minimal stack running.

Answer

Deploy a multi-site active-active configuration with full capacity in both regions.

Question 2

A company is deploying a serverless application using AWS Lambda. The application processes high-resolution images and stores them in Amazon S3. The processing time for each image is variable, but some images require more than 15 minutes to process. Lambda has a maximum execution time of 15 minutes. How can the company process these long-running image transformations?

Accepted Answer

Use AWS Batch to run the image processing as a job on EC2 or Fargate.. AWS Lambda has a hard limit of 15 minutes per invocation, so images requiring more than 15 minutes cannot be processed within a single Lambda function. AWS Batch is designed for long-running, batch-oriented compute jobs and can run on EC2 or Fargate without any time limit, making it the correct choice for processing high-resolution images that exceed Lambda's timeout.

Answer

Use AWS Step Functions to chain multiple Lambda functions, each processing a part of the image.

Answer

Use Amazon SQS to queue the images and have Lambda poll the queue; the Lambda function can process one image per invocation.

Answer

Increase the Lambda timeout to 20 minutes.

Question 3

A company is designing a new web application that will be accessed by users worldwide. The application should have low latency and high availability. The application uses a stateless web tier and a relational database. Which architecture minimizes latency for global users?

Accepted Answer

Deploy the application in multiple regions with Route 53 latency-based routing, and use Amazon Aurora Global Database for the database tier.. Deploying in multiple regions with Route 53 latency-based routing directs users to the region with the lowest network latency, minimizing response times. Amazon Aurora Global Database provides a fully managed cross-region replication solution with typical latency of under one second, ensuring the relational database tier is available close to each application deployment for low-latency reads and fast failover.

Answer

Deploy the application in a single region and use Route 53 geolocation routing.

Answer

Deploy the application in multiple regions, use CloudFront to cache static content, and route dynamic requests to the nearest region via Route 53 latency-based routing.

Answer

Deploy the application in a single region and use Amazon CloudFront to cache content globally.

Question 4

A company is deploying a containerized application on Amazon ECS. The application must be highly available and scale automatically based on CPU utilization. The application also needs to be accessible from the internet via a single endpoint. Which combination of services should the solutions architect use?

Accepted Answer

Amazon ECS with an Application Load Balancer and ECS Service Auto Scaling with a target tracking policy based on average CPU utilization.. An Application Load Balancer (ALB) provides a single internet-facing endpoint and supports HTTP/HTTPS traffic, which is typical for containerized applications. ECS Service Auto Scaling with a target tracking policy based on average CPU utilization allows the service to automatically adjust the desired count of tasks to maintain a specified CPU utilization target, ensuring high availability and elasticity.

Answer

Amazon ECS with a Network Load Balancer and step scaling policies.

Answer

Amazon ECS with an Application Load Balancer and step scaling policies based on CPU utilization.

Answer

Amazon ECS with an Application Load Balancer and manual scaling.

Question 5

A company is designing a new system to ingest and process real-time streaming data from thousands of IoT devices. The system must be able to handle variable throughput and provide durable storage for the data. The data will be processed by a Lambda function and then stored in Amazon S3. Which two services should be used together to build this ingestion pipeline?

Accepted Answer

AWS Lambda. Amazon Kinesis Data Streams (Option D) is the correct ingestion service because it provides durable, real-time data streaming with shard-level persistence for up to 365 days, enabling Lambda to process records in near real-time with at-least-once delivery semantics. AWS Lambda (Option A) is the correct processing service because it can be configured as a consumer of the Kinesis stream via event source mapping, scaling automatically with the number of shards to handle variable throughput without managing servers.

Answer

Amazon Kinesis Data Firehose

Answer

Amazon Simple Queue Service (SQS)

Answer

Amazon Simple Notification Service (SNS)

Question 6

A company is designing a new solution to host a static website with global low latency. The website content is stored in an S3 bucket and must be secured with HTTPS. Which three services or features should be used together to meet these requirements?

Accepted Answer

S3 bucket configured as an origin with Origin Access Control (OAC). Origin Access Control (OAC) allows CloudFront to securely access the S3 bucket without making the bucket public, enforcing that all requests come through CloudFront. This is the modern replacement for Origin Access Identity (OAI) and supports HTTPS between CloudFront and S3.

Answer

Application Load Balancer

Answer

Amazon Route 53

Question 7

A company is building a new application that requires a relational database with high availability across multiple Availability Zones. The database must automatically failover with minimal downtime. Which two AWS services or features meet these requirements?

Accepted Answer

Amazon Aurora DB cluster with multiple Availability Zones. Amazon Aurora DB cluster with multiple Availability Zones meets the requirements because Aurora automatically replicates data across three Availability Zones by default, providing high availability and automatic failover with minimal downtime (typically under 30 seconds). Aurora's distributed storage layer allows the primary instance to fail over to a read replica in another AZ without data loss, making it ideal for applications requiring a relational database with multi-AZ high availability.

Answer

Amazon RDS Single-AZ deployment with automated backups

Answer

Amazon DynamoDB with global tables

Answer

Amazon RDS Read Replica

Question 8

A company is designing a new data lake on AWS. The data lake will store raw data from various sources in Amazon S3. The data will be processed using AWS Glue ETL jobs and queried using Amazon Athena. To optimize costs and performance, which three practices should the solutions architect implement?

Accepted Answer

Compress data using Snappy or Gzip compression.. Compressing data with Snappy or Gzip reduces storage costs in Amazon S3 and decreases the amount of data scanned by Athena, which charges per TB scanned. Snappy offers faster decompression for ETL workloads, while Gzip provides higher compression ratios. Both are natively supported by AWS Glue and Athena, making them optimal for cost and performance.

Answer

Store data in JSON format for flexibility.

Answer

Store data in many small files to improve parallel processing.

Question 9

A company runs a critical e-commerce platform on AWS. The application is deployed across multiple Availability Zones in a single region (us-east-1). The architecture includes an Application Load Balancer (ALB), an EC2 Auto Scaling group, and an Amazon RDS for MySQL Multi-AZ database. The application experiences periodic spikes in traffic, and the Auto Scaling group scales out successfully. However, during a recent traffic spike, the database CPU utilization reached 90%, causing increased latency and some database connection timeouts. The company needs to improve the database performance to handle the spikes without over-provisioning. The solutions architect must design a solution that reduces the load on the primary database instance and improves read scalability. The application is read-heavy, with a read-to-write ratio of 80:20. Which solution should the architect implement?

Accepted Answer

Create one or more Amazon RDS Read Replicas in the same region and configure the application to route read queries to the read replica endpoint.. Amazon RDS Read Replicas can offload read traffic from the primary instance, reducing CPU utilization. For a read-heavy workload (80:20), creating Read Replicas in the same region and routing read queries to them is the most effective solution to improve read scalability without over-provisioning the primary. Option D is correct. Option A (ElastiCache) is more suited for caching but does not offload database reads directly; it requires significant application changes and may not handle all query patterns. Option B (scaling up instance class) has scaling limits and is less cost-effective; Multi-AZ is for high availability, not read scaling. Option C (DynamoDB) is a different database; migrating would be complex and unnecessary.

Answer

Implement an Amazon ElastiCache Redis cluster to cache frequent database queries.

Answer

Increase the DB instance class to a larger size and enable Multi-AZ with synchronous replication.

Answer

Migrate the database to Amazon DynamoDB and use DynamoDB Accelerator (DAX) for read performance.

Question 10

A healthcare startup is building a HIPAA-compliant application on AWS. The application uses Amazon RDS for MySQL to store patient data. The compliance team requires that all database changes be audited, including SELECT statements. The current solution enables general query logs on the RDS instance, but the logs are stored locally and are lost when the instance is rebooted. Additionally, the logs are consuming significant storage on the instance. The startup needs a durable, scalable, and cost-effective solution for storing and querying database audit logs. Which solution meets these requirements?

Accepted Answer

Configure RDS to publish audit logs to Amazon CloudWatch Logs, then export logs to Amazon S3 using a subscription filter and Lambda. Use Athena to query the logs in S3.. The most suitable solution. RDS for MySQL supports publishing audit logs to CloudWatch Logs. From there, you can set up a subscription filter to a Lambda function that exports logs to Amazon S3 for durable storage. Athena can then be used to query the logs cost-effectively. This approach is durable, scalable, and cost-effective, meeting the compliance requirement for auditing changes including SELECT statements.

Option A: While Kinesis Data Firehose can stream to S3, enabling audit logs on RDS for MySQL does not directly integrate with Kinesis; this option is more complex and unnecessary. Option C: Storing logs in a table on RDS consumes instance storage and does not provide durable, scalable storage; logs are still lost on reboot. Option D: CloudWatch Logs Insights is not cost-effective for long-term querying of large volumes and does not offer the same query flexibility as Athena on S3.

Answer

Enable audit logs on RDS and use Amazon Kinesis Data Firehose to stream logs to Amazon S3. Use Amazon Athena to query the logs.

Answer

Enable the general query log on RDS and set the log_output to TABLE. Write a scheduled script to copy the log table to Amazon S3.

Answer

Enable audit logs on RDS and stream them to Amazon CloudWatch Logs. Use CloudWatch Logs Insights to query logs.

Question 11

A company is deploying a new microservices application on Amazon ECS using Fargate. The application consists of several services that need to communicate with each other. The company wants to use service discovery so that services can find each other by name. Additionally, the company needs to ensure that traffic between services is encrypted in transit. The security team requires that all inter-service traffic uses TLS. Which combination of services should be used to meet these requirements?

Accepted Answer

Use AWS Cloud Map for service discovery and AWS App Mesh with TLS enforcement for inter-service communication.. AWS Cloud Map provides service discovery, allowing ECS services to find each other by name. AWS App Mesh can enforce TLS encryption for inter-service traffic, meeting the security requirement. Option A is incorrect because an Application Load Balancer is used for external traffic and does not provide service discovery for internal service-to-service communication. Option B is incorrect because ECS built-in service discovery (which relies on Cloud Map) does not automatically encrypt traffic; ACM certificates alone do not enforce TLS for all inter-service traffic. Option C is incorrect because an ALB is designed for load balancing external traffic, not for internal service discovery and mTLS.

Answer

Use AWS Cloud Map for service discovery and an Application Load Balancer for inter-service communication with TLS termination.

Answer

Use the built-in service discovery in Amazon ECS and encrypt traffic using AWS Certificate Manager (ACM) certificates.

Answer

Use an Application Load Balancer with target groups for each service and enable TLS on the load balancer.

Question 12

A financial services company is designing a new application that processes sensitive transactions. The application runs on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer. The application writes transaction logs to an Amazon EFS file system. The company needs to ensure that the logs are encrypted at rest using a customer-managed AWS KMS key. Additionally, the logs must be retained for 7 years and should not be accessible after that period. Which solution meets the encryption and retention requirements?

Accepted Answer

Enable encryption at rest on the EFS file system using a customer-managed KMS key. Use a Lambda function to copy logs to Amazon S3 and apply an S3 Lifecycle policy to expire objects after 7 years.. EFS supports encryption at rest using a customer-managed KMS key, and by copying logs to S3 and applying a lifecycle policy with expiration after 7 years, both encryption and retention requirements are met. Option A is incorrect because storing logs directly in S3 with default encryption uses S3-managed keys, not a customer-managed KMS key. Option C is incorrect because CloudWatch Logs is for real-time monitoring and not designed for long-term archival with the specified encryption and retention requirements. Option D is incorrect because enabling encryption on EFS with an AWS managed key does not meet the customer-managed KMS key requirement, and deleting logs via a cron job on EC2 instances is not reliable and may not ensure complete deletion after exactly 7 years.

Answer

Store logs directly in Amazon S3 with default encryption. Use an S3 Lifecycle policy to delete objects older than 7 years.

Answer

Use Amazon CloudWatch Logs to stream logs from the application and set a retention policy of 7 years. Enable encryption using a customer-managed KMS key.

Answer

Enable encryption at rest on the EFS file system using an AWS managed key. Use a cron job on the EC2 instances to delete logs older than 7 years.

Question 13

A company is building a new serverless application using AWS Lambda functions. The application processes images uploaded to an Amazon S3 bucket. Each image triggers a Lambda function that resizes the image and stores the result in another S3 bucket. The company expects a high volume of uploads, up to 10,000 images per minute. The current Lambda function is configured with a timeout of 5 minutes and 1024 MB of memory. During testing, the Lambda function times out for large images. What should the company do to ensure the function can process large images without timing out?

Accepted Answer

Increase the Lambda function memory to 3008 MB to get more CPU and network throughput.. Increasing Lambda memory proportionally increases CPU and network throughput, which can significantly speed up image processing, especially for large images, thereby reducing the likelihood of timeout. Option A: Increasing timeout does not address the root cause of slow processing; it only allows the function to run longer, but the function may still time out if processing is too slow. Option B: Using SQS decouples invocation but does not speed up individual function execution; it mainly helps with throttling and retries. Option C: Migrating to ECS on Fargate is not necessary; Lambda can handle this workload with sufficient memory allocation.

Answer

Increase the Lambda function timeout to 15 minutes.

Answer

Use Amazon SQS to decouple the S3 event and Lambda invocation, allowing Lambda to pull messages in batches.

Answer

Migrate the image processing to Amazon ECS on Fargate with a long-running task.

Question 14

A company is designing a new application that will run on AWS. The application needs to store and retrieve user session data with low latency. The session data is small (less than 1 KB per user) and must be highly available. The company expects up to 10 million active users per day. Which AWS service should be used as the session store?

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is an in-memory data store designed for low-latency access, making it ideal for session storage for millions of users. Option A: DynamoDB has higher latency compared to in-memory stores. Option B: S3 is object storage and not suitable for low-latency session data. Option C: RDS for MySQL is relational and slower for session access.

Answer

Amazon DynamoDB

Answer

Amazon S3

Answer

Amazon RDS for MySQL

Question 15

A company is deploying a new web application on AWS that requires a highly available and scalable architecture. The application consists of a stateless web tier and a stateful database tier. The web tier runs on Amazon EC2 instances behind an Application Load Balancer. The database tier uses Amazon Aurora MySQL. The company expects variable traffic patterns and wants to automatically scale the web tier based on CPU utilization. Additionally, the company wants to ensure that the database can handle increased read traffic without manual intervention. Which combination of actions should the company take?

Accepted Answer

Use an Auto Scaling group with a target tracking scaling policy based on CPU utilization. Enable Aurora Auto Scaling to add read replicas based on CPU or connections.. It uses an Auto Scaling group with a target tracking scaling policy based on CPU utilization to automatically scale the web tier, and enables Aurora Auto Scaling to add read replicas based on CPU or connections, which meets the requirements for both web and database scaling. Option B is incorrect because Amazon SQS is a message queue service and does not scale the database or handle read traffic for Aurora. Option C is incorrect because DynamoDB is a NoSQL database, not the specified Aurora MySQL database, and its auto scaling does not apply. Option D is incorrect because ElastiCache is a caching service, not the database tier, and its auto scaling does not address read scaling for Aurora.

Answer

Use an Auto Scaling group with a target tracking scaling policy based on CPU utilization. Use Amazon SQS to queue read requests during peak traffic.

Answer

Use an Auto Scaling group with a simple scaling policy based on CPU utilization. Use DynamoDB Auto Scaling for the database.

Answer

Use an Auto Scaling group with a step scaling policy based on CPU utilization. Use ElastiCache Auto Scaling to add cache nodes for read traffic.