DOP-C02 Resilient Cloud Solutions Practice Test 13 — 15 Questions

Question 1

A company runs a stateful application on EC2 instances. They want to distribute traffic evenly and maintain session stickiness. Which AWS service should they use?

Accepted Answer

Application Load Balancer with sticky sessions. An Application Load Balancer with sticky sessions (session affinity) distributes HTTP/HTTPS traffic across targets while binding a client to the same target for the duration of a session via a cookie. This satisfies both even distribution and session persistence for a stateful application.

Answer

Network Load Balancer

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Amazon Route 53 weighted routing policy

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Amazon CloudFront with origin failover

Question 2

A company uses AWS CodeDeploy to deploy a new version of an application to EC2 instances. They want to minimize downtime and roll back quickly if the deployment fails. Which deployment type should they use?

Accepted Answer

Blue/green deployment. Blue/green deployment creates two separate environments (blue and green) and shifts traffic from the old to the new after testing. This minimizes downtime because traffic is switched instantly, and rollback is achieved by reverting traffic to the original environment. Option A (Canary) is a traffic shifting pattern used within blue/green deployments, not a standalone deployment type that offers immediate rollback. Option B (Linear) is also a traffic shifting pattern for blue/green. Option D (In-place) updates existing instances, causing downtime during deployment and requiring a manual rollback process.

Answer

Canary deployment

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Linear deployment

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In-place deployment

Question 3

A company runs a critical microservices architecture on Amazon ECS with Fargate. They want to ensure that if a task fails, it is automatically restarted, and the service remains available across multiple Availability Zones. How should they configure the ECS service?

Accepted Answer

Define an ECS service with a task definition, set desired count across multiple Availability Zones, and use Service Auto Scaling. An ECS service configured with a task definition, desired count across multiple Availability Zones, and Service Auto Scaling ensures resilience. The ECS service scheduler automatically restarts failed tasks, and distributing tasks across AZs provides high availability. Option A is wrong because placing all tasks in a single AZ creates a single point of failure. Option B is wrong because a standalone Fargate task does not have automatic restart; a CloudWatch alarm can restart it but lacks the built-in resilience of an ECS service. Option C is wrong because using a single EC2 instance is a single point of failure and does not provide multi-AZ resilience.

Answer

Place all tasks in the same Availability Zone to reduce latency

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Run a standalone Fargate task and use a CloudWatch alarm to restart it

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Use an EC2 launch type with a single instance to reduce complexity

Question 4

A company uses Amazon DynamoDB with global tables for a multi-region active-active application. They notice that occasionally, concurrent updates to the same item in different regions cause data inconsistency. How can they resolve this?

Accepted Answer

Use conditional writes and design the application to handle conflicts. DynamoDB global tables use an eventually consistent model for multi-region replication, meaning concurrent updates to the same item in different regions can lead to conflicts. Conditional writes allow the application to enforce a last-writer-wins (LWW) strategy or custom conflict resolution logic, ensuring data consistency by only applying updates that meet specified conditions (e.g., a version number or timestamp check). This approach aligns with the recommended practice for handling concurrent writes in an active-active global table setup.

Answer

Disable global tables and use a single region

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Use DynamoDB read replicas instead of global tables

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Use DynamoDB Accelerator (DAX) to cache writes

Question 5

A company experiences intermittent high latency for a web application running on EC2 behind an ALB. They want to monitor and automatically replace instances that have high CPU. Which solution meets this requirement?

Accepted Answer

Create a CloudWatch alarm on CPU utilization that triggers an Auto Scaling policy to replace the instance. You can configure a CloudWatch alarm on the EC2 instance's CPU utilization metric, and then use that alarm to trigger an Auto Scaling lifecycle hook or a scaling policy that terminates the unhealthy instance and launches a replacement. This directly ties performance monitoring to automated instance replacement, meeting the requirement to replace instances with high CPU.

Answer

Use Auto Scaling scheduled scaling actions to replace instances at peak times

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Use AWS Lambda to periodically check CPU and terminate high-CPU instances

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Configure the ALB health check to mark instances unhealthy when CPU is high

Question 6

Which TWO AWS services can be used to distribute incoming traffic across multiple AWS resources in different Availability Zones within a single region?

Accepted Answer

AWS Global Accelerator. AWS Global Accelerator uses the AWS global network and Anycast static IP addresses to route incoming traffic to the optimal endpoint, such as an Application Load Balancer or EC2 instance, across multiple Availability Zones within a single region. It improves performance and reliability by directing traffic to the healthiest endpoint and automatically rerouting in case of failure, making it a valid service for distributing traffic across AZs.

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Amazon Route 53

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Amazon CloudFront

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AWS Direct Connect

Question 7

Which TWO actions can help ensure that an application running on EC2 instances can survive the loss of an entire Availability Zone?

Accepted Answer

Use an Auto Scaling group with multiple Availability Zones. Deploying instances in multiple Availability Zones (AZs) ensures that if one AZ fails, instances in other AZs continue to run. Using an Auto Scaling group with multiple AZs automatically distributes instances across AZs and replaces failed instances, further enhancing resilience. Options B and C are both correct because they achieve multi-AZ deployment. Option A is incorrect because a single AZ is a single point of failure. Option D is incorrect because instance type does not provide AZ resilience. Option E is incorrect because CloudWatch alarms can detect issues but do not distribute instances across AZs.

Answer

Deploy all instances in a single Availability Zone for consistency

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Use a larger instance type to handle more load

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Use CloudWatch alarms to monitor instance health

Question 8

A company runs a critical web application on EC2 instances behind an Application Load Balancer. The application stores session state in an in-memory cache on each instance. During deployment of a new version, users experience session timeouts and errors. Which design change will MOST effectively improve resilience and avoid session loss during deployments?

Accepted Answer

Migrate session state to ElastiCache for Redis.. Migrating session state from in-memory EC2 instance storage to ElastiCache for Redis decouples session data from individual instances. This ensures that when a new deployment replaces instances, sessions persist independently, preventing timeouts and errors. ElastiCache provides a centralized, highly available session store that survives instance termination and scaling events.

Answer

Enable sticky sessions (session affinity) on the ALB.

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Increase the ALB idle timeout to 600 seconds.

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Increase the EC2 instance size to handle higher memory.

Question 9

A company is designing a multi-Region disaster recovery strategy for a stateless web application. The application runs on EC2 instances in an Auto Scaling group behind an ALB in us-east-1. The recovery point objective (RPO) is 15 minutes and recovery time objective (RTO) is 30 minutes. The application data is stored in Amazon RDS for PostgreSQL. Which combination of actions should the company take to meet the RPO and RTO?

Accepted Answer

Use RDS cross-Region replication to a standby DB instance in another Region. Maintain a warm standby environment (Auto Scaling group, ALB) in the disaster Region. Configure Route 53 health checks to fail over automatically.. It meets both the 15-minute RPO and 30-minute RTO. RDS cross-Region replication provides continuous asynchronous replication with minimal lag, typically well under 15 minutes, ensuring data is nearly up-to-date. The warm standby environment (pre-provisioned Auto Scaling group and ALB) in the disaster Region allows automatic failover via Route 53 health checks, enabling recovery within the 30-minute RTO without manual intervention.

Answer

Use RDS cross-Region snapshot copy every 15 minutes. In the disaster Region, manually launch a new environment and restore the latest snapshot.

Answer

Use RDS Multi-AZ in us-east-1. In the disaster Region, keep a standby Auto Scaling group and ALB. On failure, promote the Multi-AZ standby to primary and update DNS.

Answer

Use RDS read replicas in another Region. On failure, promote the read replica to a standalone instance and update the application.

Question 10

A DevOps engineer is designing a resilient architecture for a serverless application using AWS Lambda, Amazon API Gateway, and Amazon DynamoDB. The application experiences occasional spikes in traffic that cause Lambda function throttling and increased error rates. What is the MOST effective way to improve resilience and reduce throttling?

Accepted Answer

Reserve concurrency for the Lambda function to ensure it always has available capacity.. The stem specifies that traffic spikes cause Lambda function throttling. Reserving concurrency for the Lambda function (Option D) guarantees a dedicated portion of the account-level concurrency limit, preventing other functions from exhausting capacity and directly mitigating throttling. Option B (DynamoDB auto scaling) would only help if the throttling were caused by DynamoDB capacity issues, but the stem makes no mention of database errors. Option A (increasing memory) does not address concurrency limits, and Option C (API Gateway throttling) can limit incoming requests but does not guarantee that Lambda has capacity to process them.

Answer

Increase the Lambda function memory to the maximum allowed.

Answer

Enable DynamoDB auto scaling for the table to handle traffic spikes.

Answer

Set API Gateway throttling limits to match the expected peak traffic.

Question 11

A company runs a microservices architecture on Amazon ECS with Fargate. Services communicate via an internal Application Load Balancer. Recently, one service became unavailable due to a memory leak, causing cascading failures in downstream services. What design change would MOST effectively improve resilience and limit the blast radius?

Accepted Answer

Implement circuit breaker patterns in the service discovery and client libraries to stop calling unhealthy services.. Implementing a circuit breaker pattern in service discovery and client libraries stops requests to unhealthy services, preventing cascading failures and limiting blast radius. Option A is wrong because increasing memory limits only delays the inevitable failure and does not prevent downstream services from being affected. Option C (connection draining) only affects in-flight requests during deregistration, not active health issues. Option D (auto scaling) helps but does not stop requests from being sent to a failing service; scaling cannot fix a memory leak.

Answer

Increase the memory limit for each ECS task to accommodate memory leaks.

Answer

Enable connection draining on the ALB to allow in-flight requests to complete.

Answer

Implement automatic scaling policies for ECS services based on memory utilization.

Question 12

A company runs a critical batch processing workload on Amazon EMR that must complete within a 2-hour window each night. The workload is fault-tolerant but must be resilient to instance failures. Currently, the EMR cluster uses instance fleets with Spot Instances. Recently, Spot Instance interruptions caused the cluster to take over 3 hours to complete. Which change will MOST effectively ensure the workload completes within the 2-hour window despite Spot interruptions?

Accepted Answer

Use a mixed instances policy that includes multiple instance types across different Availability Zones.. A mixed instances policy across multiple Availability Zones increases the diversity of Spot capacity pools. When one instance type or zone experiences interruptions, the cluster can fall back to other pools, reducing the likelihood of prolonged delays. This approach directly addresses Spot interruption risk without sacrificing cost efficiency, as On-Demand instances would.

Answer

Increase the number of core nodes to 20 to improve parallelism.

Answer

Switch to using On-Demand instances for all nodes.

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Configure the cluster to terminate idle nodes after 5 minutes to reduce costs.

Question 13

A company uses Amazon Route 53 for DNS and wants to ensure high availability for a web application hosted on two EC2 instances in different Availability Zones. The application uses an Application Load Balancer. What is the simplest way to achieve resilience if one Availability Zone becomes unavailable?

Accepted Answer

Place the instances in different Availability Zones behind the ALB.. Placing EC2 instances in different Availability Zones behind an Application Load Balancer (ALB) is the simplest and most effective way to achieve high availability. The ALB automatically distributes traffic across healthy targets in multiple AZs, and if one AZ becomes unavailable, the ALB stops routing requests to instances in that AZ, ensuring continued service from the remaining AZ.

Answer

Launch both instances in the same Availability Zone.

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Configure Route 53 latency-based routing to each instance.

Answer

Configure Route 53 failover routing with health checks pointing to each instance.

Question 14

A company is deploying a stateful application on Amazon EKS. The application requires persistent storage that can be reattached to a new pod if the original pod fails. The cluster spans multiple Availability Zones. Which storage solution provides the BEST resilience and meets these requirements?

Accepted Answer

Amazon EFS file system.. Amazon EFS provides a fully managed, regional NFS file system that can be mounted concurrently by multiple pods across different Availability Zones. It is designed for high availability and durability, automatically replicating data across multiple AZs, and supports automatic reattachment to a new pod if the original pod fails, making it the best choice for stateful applications requiring resilient, shared persistent storage on Amazon EKS.

Answer

Amazon S3 bucket with a mountpoint.

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Amazon EBS with gp3 volume type.

Answer

EC2 instance store volumes.

Question 15

A company runs a critical application on AWS Lambda that processes messages from an Amazon SQS queue. The application must be resilient to downstream service failures. The team notices that when the downstream service is unhealthy, messages are repeatedly retried and eventually sent to the dead-letter queue (DLQ) before the service recovers. What design change would improve resilience by allowing automatic retries after the downstream service recovers?

Accepted Answer

Configure the SQS queue with a large visibility timeout (e.g., 6 hours) and use a redrive policy only after a high number of receives. Keep the messages in the queue and retry when the downstream service becomes healthy.. Increasing the visibility timeout to a long duration (e.g., 6 hours) prevents messages from being repeatedly retried and sent to the DLQ while the downstream service is unhealthy. Instead, messages remain in the SQS queue and become visible again only after the visibility timeout expires, allowing automatic retries once the downstream service recovers. This approach avoids premature DLQ delivery and leverages SQS's built-in redrive policy based on maxReceiveCount.

Answer

Reduce the maxReceiveCount to 1 so that messages are sent to DLQ immediately, then reprocess them from DLQ later.

Answer

Increase the message retention period to 14 days and use a DLQ with high retention.

Answer

Use Amazon SNS to fan out messages to multiple SQS queues, each with different retry policies.