SAP-C02 Continuous Improvement for Existing Solutions Practice Test 13 — 15 Questions

Question 1

A company runs a critical database on Amazon RDS for PostgreSQL. The database is experiencing performance degradation due to high CPU utilization. The operations team wants to analyze the root cause. Which THREE steps should the team take to diagnose the issue?

Accepted Answer

Enable Enhanced Monitoring to view OS-level metrics such as CPU and memory usage.. Options A, B, and D are correct. Enabling Performance Insights helps identify queries causing load. Enabling enhanced monitoring provides OS-level metrics. Using RDS events can indicate maintenance or issues. C is wrong because increasing instance size is a remedy, not a diagnostic step. E is wrong because Multi-AZ is for high availability, not performance diagnosis.

Answer

Increase the instance size to provisioned IOPS to handle the load.

Answer

Enable Multi-AZ deployment for automatic failover.

Question 2

A company uses AWS CloudFormation to deploy infrastructure. The operations team wants to implement a change management process that requires approval before stack updates can proceed. Which TWO approaches can achieve this?

Accepted Answer

Create a service role with specific IAM policies and require that updates be initiated with that role.. Options A and D are correct. Using a change set allows review before execution. Using a service role with IAM policies can enforce approval workflows. B is wrong because stack policies protect resources, not control updates. C is wrong because stack sets are for multi-account deployments. E is wrong because it is a manual process, not automated.

Answer

Use AWS CloudFormation StackSets to deploy updates across multiple accounts.

Answer

Manually review all template changes before uploading to S3.

Answer

Configure a stack policy to prevent updates to critical resources.

Question 3

A company uses AWS Lambda functions behind an Amazon API Gateway REST API. The Lambda functions query an Amazon RDS for PostgreSQL database. Recently, the company has noticed increased latency and occasional timeouts during peak hours. A solutions architect needs to improve the performance and scalability of the database layer. Which solution will meet these requirements with the LEAST operational overhead?

Accepted Answer

Implement Amazon RDS Proxy to manage connection pooling between Lambda and the RDS instance.. Option A is correct because Amazon RDS Proxy handles connection pooling, reducing database load and improving scalability, which directly addresses latency and timeouts. Option B is wrong because Read Replicas help with read-heavy workloads but do not reduce connection overhead. Option C is wrong because DynamoDB Accelerator (DAX) is used for DynamoDB, not RDS. Option D is wrong because increasing instance size is a vertical scaling approach that does not address the connection pooling issue and may still lead to timeouts under high connection counts.

Answer

Enable Amazon DynamoDB Accelerator (DAX) on the RDS instance.

Answer

Add a Multi-AZ RDS Read Replica and modify Lambda to use the Read Replica for queries.

Answer

Increase the instance size of the RDS database to handle more concurrent connections.

Question 4

A company runs a production application on Amazon ECS with Fargate launch type. The application uses an Application Load Balancer (ALB) to distribute traffic to tasks. The company has configured an Auto Scaling target tracking policy based on average CPU utilization. During a marketing campaign, traffic spikes cause the ALB to return 503 errors. The ECS service dashboard shows that the number of tasks scaled out to the maximum allowed but the CPU utilization remained high. What is the MOST likely cause of the 503 errors?

Accepted Answer

The ECS service scaled out to the maximum number of tasks, but the new tasks are not yet registered as healthy with the ALB, or the existing tasks are overwhelmed.. Option B is correct because with target tracking based on CPU, the service scales out until max tasks is reached; if CPU is still high, the ALB may be overloaded or tasks are not accepting traffic fast enough. A surge queue or health check grace period issue could cause 503s. Option A is wrong because an ALB can handle many connections; the issue is task capacity. Option C is wrong because target tracking scaling can take minutes; the issue is max tasks reached. Option D is wrong because Fargate tasks have sufficient ENIs; the error is at the ALB level.

Answer

The target tracking scaling policy takes too long to trigger, and the service cannot scale quickly enough.

Answer

The Fargate tasks have exhausted their elastic network interface (ENI) limits.

Answer

The ALB connection limit has been exceeded due to the traffic spike.

Question 5

A company runs a web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The application stores session data locally on the EC2 instances. The company wants to make the application stateless to improve availability and scalability. Which solution should the solutions architect recommend?

Accepted Answer

Use Amazon ElastiCache for Redis to store session data externally.. Option C is correct because ElastiCache with Redis provides a centralized, fast, and durable session store, making the application stateless. Option A is wrong because storing sessions in S3 would introduce high latency and is not designed for high-frequency read/write. Option B is wrong because session stickiness (sticky sessions) on the ALB prevents true statelessness and can cause uneven load. Option D is wrong because mounting an EFS volume for session files still ties sessions to a filesystem but adds complexity and latency compared to ElastiCache.

Answer

Configure session stickiness on the ALB to route requests from the same user to the same EC2 instance.

Answer

Mount an Amazon EFS file system on the EC2 instances and store session files there.

Answer

Store session data in Amazon S3 and update the application to read and write sessions to S3.

Question 6

A company has an AWS Lambda function that processes files uploaded to an S3 bucket. The Lambda function has been running successfully for months. Recently, the company updated the Lambda function code and started seeing occasional throttling errors (HTTP 429) from the Lambda service. The function's reserved concurrency is set to 100. The company is unsure why throttling is occurring only after the code update. What is the MOST likely cause?

Accepted Answer

The code update increased the execution time of the Lambda function, leading to a higher number of concurrent executions that exceed the account-level concurrency limit.. Option B is correct because if the function invocation rate exceeds the account-level concurrency limit (default 1000), throttling occurs. The code update may have increased execution time, causing more concurrent invocations to pile up. Option A is wrong because increasing S3 events would increase invocations, but the reserved concurrency of 100 might still be within account limits. Option C is wrong because Lambda execution role permissions don't cause throttling errors. Option D is wrong because CloudWatch Logs throttling would cause logs to be dropped, not Lambda throttling.

Answer

The Lambda function is writing logs to CloudWatch Logs at a rate that exceeds the CloudWatch throttling limit.

Answer

The S3 bucket is receiving more uploads than before, causing more Lambda invocations.

Answer

The updated Lambda function no longer has the required IAM permissions to access S3, causing retries that throttle.

Question 7

A company runs a critical application on Amazon EC2 instances in an Auto Scaling group. The application uses a custom health check that reports instance health to Amazon CloudWatch. The Auto Scaling group is configured with an EC2 health check type. Recently, the company noticed that instances failing the custom health check are not being terminated and replaced. What should the solutions architect do to ensure that instances failing the custom health check are automatically replaced?

Accepted Answer

Change the Auto Scaling group health check type to ELB and ensure the custom health check is integrated with the ELB target group.. Option D is correct because Auto Scaling only uses the EC2 status checks (system/reachability) by default. To use a custom health check, you must configure the Auto Scaling group to use ELB health checks and have the custom health check reported via a target group. Alternatively, you can use Amazon EventBridge to listen for custom health check failures and terminate instances. Option A is wrong because changing the health check type to ELB still requires a target group, and the custom health check must be integrated. Option B is wrong because CloudWatch alarms don't directly trigger instance replacement; you would need a lifecycle hook or EventBridge. Option C is wrong because manual termination defeats automation.

Answer

Manually terminate the unhealthy instances from the EC2 console.

Answer

Configure the Auto Scaling group to use instance metadata to report health.

Answer

Create a CloudWatch alarm based on the custom health check metric and configure the alarm to terminate the instance.

Question 8

A company uses AWS CloudFormation to deploy infrastructure. The company wants to ensure that if a stack update fails, the stack automatically rolls back to the last known good state. Which CloudFormation stack option should the company configure?

Accepted Answer

Set the 'Rollback on failure' option to 'Yes' when performing the stack update.. Option A is correct because CloudFormation stack updates have a 'Rollback on failure' option that defaults to 'Yes'. If an update fails, CloudFormation automatically rolls back to the previous state. Option B is wrong because a stack policy prevents updates to specific resources, not rollback behavior. Option C is wrong because change sets allow you to preview changes but do not automate rollback. Option D is wrong because termination protection prevents stack deletion, not rollback on failed updates.

Answer

Enable termination protection on the stack.

Answer

Configure a stack policy to prevent updates to critical resources.

Answer

Use a change set to review changes before updating the stack.

Question 9

A company is running a stateful web application on Amazon EC2 instances in an Auto Scaling group. The instances store session data in an Amazon ElastiCache for Redis cluster. The company wants to improve the application's fault tolerance and ensure that session data is not lost if an Availability Zone fails. What should the solutions architect do?

Accepted Answer

Enable Cluster Mode on the ElastiCache for Redis cluster and configure Multi-AZ.. Option B is correct because ElastiCache for Redis with Cluster Mode enabled automatically shards data across multiple nodes and provides Multi-AZ with automatic failover, ensuring high availability and data durability. Option A is wrong because increasing instance size does not protect against AZ failure. Option C is wrong because a single-node cluster has no replication; if the node fails, data is lost. Option D is wrong because ElastiCache for Memcached does not support persistence or replication; data loss occurs on node failure.

Answer

Configure the ElastiCache for Redis cluster to have multiple read replicas in the same region.

Answer

Increase the instance size of the EC2 instances to handle more load.

Answer

Migrate from ElastiCache for Redis to ElastiCache for Memcached.

Question 10

A company has a monolithic application running on a single Amazon EC2 instance. The application consists of a web server and a backend worker process. The company wants to migrate to a microservices architecture using containers on Amazon ECS with Fargate. The solutions architect needs to design a solution that minimizes downtime during the migration. Which approach should the solutions architect recommend?

Accepted Answer

Use a strangler fig pattern: gradually replace parts of the monolith with microservices, routing traffic via an Application Load Balancer.. Option D is correct because a strangler fig pattern allows incremental migration of functionality from the monolith to microservices, with the ALB routing traffic to either the monolith or new services. This minimizes downtime because the old application remains operational while pieces are moved. Option A is wrong because a lift-and-shift of the entire application into a single container does not decompose it into microservices. Option B is wrong because refactoring the entire application at once introduces significant risk and downtime. Option C is wrong because running both the monolith and new services on the same instance but on different ports does not inherently minimize downtime and complicates routing.

Answer

Create a Docker image of the entire monolithic application and run it on ECS with Fargate.

Answer

Run the monolithic application on the same EC2 instance as the new microservices, using different ports.

Answer

Refactor the entire application into microservices, then deploy all microservices at once on ECS.

Question 11

A company has an S3 bucket that stores sensitive data. The company wants to ensure that all objects uploaded to the bucket are encrypted at rest. Which solution should the solutions architect recommend?

Accepted Answer

Enable default encryption on the S3 bucket using SSE-S3 or SSE-KMS.. Option D is correct because S3 default encryption ensures that all objects are encrypted at rest using SSE-S3 or SSE-KMS, regardless of whether the upload request specifies encryption. Option A is wrong because bucket policies cannot enforce encryption; they can deny uploads without encryption headers but are not the simplest method. Option B is wrong because S3 Access Points are used for managing access, not encryption. Option C is wrong while valid, it's more complex than simply enabling default encryption.

Answer

Use a bucket policy to deny uploads that do not include the x-amz-server-side-encryption header.

Answer

Create an AWS Lambda function that encrypts objects after they are uploaded.

Answer

Configure an S3 Access Point with a policy that requires encryption.

Question 12

A company runs a web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The application experiences high request latency during peak traffic. A solutions architect discovers that the ALB is not distributing traffic evenly across the instances. The instances have different sizes (t3.large and t3.xlarge). Which TWO actions should the solutions architect take to improve load distribution?

Accepted Answer

Enable connection draining on the target group.. Option A and Option D are correct. Changing the routing algorithm to least outstanding requests ensures that instances with fewer pending requests receive new traffic, balancing load based on current capacity. Enabling connection draining ensures that in-flight requests complete before an instance is deregistered, preventing abrupt termination. Option B is wrong because sticky sessions would cause uneven load. Option C is wrong because increasing the deregistration delay helps but doesn't improve distribution. Option E is wrong because using the same instance type does not address the imbalance caused by different sizes; LOR algorithm handles that.

Answer

Replace all instances with the same instance type.

Answer

Enable sticky sessions (session affinity) on the target group.

Answer

Increase the deregistration delay (connection draining) on the target group to 300 seconds.

Question 13

A company is using AWS CodePipeline to automate deployments of a web application. The pipeline includes a build stage using AWS CodeBuild and a deploy stage using AWS CodeDeploy to an Auto Scaling group. Recently, deployments have been failing during the deploy stage with an error indicating that the target instances are not in a healthy state. The CodeDeploy agent logs show that the agent is running but the application validation scripts are failing. Which THREE actions should the solutions architect take to troubleshoot and resolve the issue?

Accepted Answer

Test the validation script manually on a healthy instance to confirm it works as expected.. Options A, C, and D are correct. Checking AppSpec hooks ensures the validation scripts are correctly defined. Reviewing CodeDeploy agent logs helps identify script failures. Testing the validation script manually on a healthy instance verifies its functionality. Option B is wrong because increasing the deployment timeout does not fix the script failure. Option E is wrong because CodeDeploy does not use Auto Scaling lifecycle hooks for instance health; it uses its own deployment lifecycle.

Answer

Increase the deployment timeout in the CodeDeploy deployment group to allow more time for validation.

Answer

Configure an Auto Scaling lifecycle hook to perform health checks before the instance is placed in service.

Question 14

A company uses Amazon RDS for MySQL with Multi-AZ deployment. The database experiences high CPU utilization during peak hours. The company wants to reduce the load on the primary database instance without making changes to the application code. Which TWO solutions should the solutions architect recommend?

Accepted Answer

Create one or more Read Replicas in the same region and direct read traffic to them.. Options B and D are correct. Read Replicas can offload read traffic from the primary, reducing CPU utilization. Amazon ElastiCache caches frequent query results, reducing database queries. Option A is wrong because increasing instance size of the primary helps but is not the only solution and may require downtime. Option C is wrong because converting to Multi-AZ does not reduce read load; Multi-AZ is for failover. Option E is wrong because RDS Proxy helps with connection pooling but not CPU reduction from queries.

Answer

Increase the instance size of the primary RDS instance.

Answer

Enable Amazon RDS Proxy to manage database connections.

Answer

Convert the RDS instance to a Multi-AZ deployment if not already.

Question 15

A media company runs a video processing pipeline on AWS. The pipeline uses AWS Step Functions to orchestrate multiple AWS Lambda functions. The first Lambda function downloads a video file from an S3 bucket, the second transcodes it using AWS Elemental MediaConvert, and the third uploads the transcoded files to a different S3 bucket. Recently, the pipeline has been failing intermittently with 'State machine execution timed out' errors. The Step Functions execution history shows that the first Lambda function takes up to 25 minutes to complete for large video files. The Step Functions state machine has a default execution timeout of 5 minutes. The company wants to fix the timeout issue without redesigning the entire pipeline. Which solution should the solutions architect recommend?

Accepted Answer

Increase the 'timeoutSeconds' value in the Step Functions state machine definition to 1800 (30 minutes) or more.. Option A is correct because the issue is that the first Lambda function exceeds the state machine execution timeout. By increasing the timeout in the state machine definition, the execution can run longer. The Lambda function itself has a maximum timeout of 15 minutes, but the state machine timeout must be higher than the total expected duration. Option B is wrong because the Lambda function timeout is separate; even if increased, the state machine timeout would still cause failure. Option C is wrong because using SQS would require significant changes to the pipeline and does not directly address the long-running Lambda. Option D is wrong because increasing Lambda timeout alone does not fix the state machine timeout.

Answer

Increase the Lambda function timeout to 30 minutes in the Lambda configuration.

Answer

Increase the Lambda function timeout to 15 minutes and increase the state machine execution timeout to 30 minutes.

Answer

Replace the Lambda function with an Amazon SQS queue and have the Step Functions wait for a callback.