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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q104-Q109):
NEW QUESTION # 104
A company is migrating a legacy application to AWS. The application runs on EC2 instances across multiple Availability Zones behind an Application Load Balancer (ALB). The target group routing algorithm is set to weighted random, and the application requires session affinity (sticky sessions).
After deployment, users report random application errors that were not present before migration, even though target health checks are passing.
Which solution will meet this requirement?
- A. Turn off the cross-zone load balancing attribute of the target group.
- B. Turn on anomaly mitigation for the target group.
- C. Increase the deregistration delay attribute of the target group.
- D. Set the routing algorithm of the target group to least outstanding requests.
Answer: D
Explanation:
According to the AWS Cloud Operations and Elastic Load Balancing documentation, Application Load Balancer (ALB) supports multiple routing algorithms to distribute requests among targets:
Round robin (default)
Least outstanding requests (LOR)
Weighted random
When applications require session affinity, AWS recommends using "least outstanding requests" as the load balancing algorithm because it reduces latency, distributes load evenly, and ensures consistent target responsiveness during high traffic.
Using weighted random routing with sticky sessions can cause sessions to be routed inconsistently if one target's capacity fluctuates, leading to session mismatches and application errors - especially when user sessions rely on instance-specific state.
Disabling cross-zone balancing (Option C) or adjusting deregistration delay (Option D) does not address routing inconsistency. Anomaly mitigation (Option B) protects against target performance degradation, not sticky-session misrouting.
Therefore, the correct solution is Option A - changing the target group's routing algorithm to least outstanding requests ensures smoother, predictable session handling and resolves random application errors.
NEW QUESTION # 105
A CloudOps engineer wants to share a copy of a production database with a migration account.
The production database is hosted on an Amazon RDS DB instance and is encrypted at rest with an AWS Key Management Service (AWS KMS) key that has an alias of production-rds-key.
What must the CloudOps engineer do to meet these requirements with the LEAST administrative overhead?
- A. Create an RDS read replica in the migration account. Configure the KMS key policy to replicate the production-rds-key KMS key to the migration account.
- B. Use native database toolsets to export the RDS DB instance to Amazon S3. Create an S3 bucket and an S3 bucket policy for cross-account access between the production account and the migration account. Use native database toolsets to import the database from Amazon S3 to a new RDS DB instance.
- C. Take a snapshot of the RDS DB instance in the production account. Share the snapshot with the migration account. In the migration account, create a new KMS key that has an identical alias.
- D. Take a snapshot of the RDS DB instance in the production account. Amend the KMS key policy of the production-rds-key KMS key to give access to the migration account's root user. Share the snapshot with the migration account.
Answer: D
Explanation:
Encrypted RDS snapshots can be shared across accounts only if the KMS key that encrypts them allows the target account to use the key. The CloudOps engineer should (1) take a snapshot of the encrypted RDS instance, (2) update the production-rds-key KMS key policy to grant the migration account access, and then (3) share the snapshot with the migration account. This is the simplest, fully managed approach with the least administrative overhead.
NEW QUESTION # 106
A company is migrating a legacy application to AWS. The application runs on EC2 instances across multiple Availability Zones behind an Application Load Balancer (ALB). The target group routing algorithm is set to weighted random, and the application requires session affinity (sticky sessions).
After deployment, users report random application errors that were not present before migration, even though target health checks are passing.
Which solution will meet this requirement?
- A. Turn off the cross-zone load balancing attribute of the target group.
- B. Turn on anomaly mitigation for the target group.
- C. Increase the deregistration delay attribute of the target group.
- D. Set the routing algorithm of the target group to least outstanding requests.
Answer: D
Explanation:
According to the AWS Cloud Operations and Elastic Load Balancing documentation, Application Load Balancer (ALB) supports multiple routing algorithms to distribute requests among targets:
* Round robin (default)
* Least outstanding requests (LOR)
* Weighted random
When applications require session affinity, AWS recommends using "least outstanding requests" as the load balancing algorithm because it reduces latency, distributes load evenly, and ensures consistent target responsiveness during high traffic.
Using weighted random routing with sticky sessions can cause sessions to be routed inconsistently if one target's capacity fluctuates, leading to session mismatches and application errors - especially when user sessions rely on instance-specific state.
Disabling cross-zone balancing (Option C) or adjusting deregistration delay (Option D) does not address routing inconsistency. Anomaly mitigation (Option B) protects against target performance degradation, not sticky-session misrouting.
Therefore, the correct solution is Option A - changing the target group's routing algorithm to least outstanding requests ensures smoother, predictable session handling and resolves random application errors.
Reference: AWS Cloud Operations & Load Balancing Guide - Optimizing Application Load Balancer Routing Algorithms for Stateful Applications
NEW QUESTION # 107
A company is storing backups in an Amazon S3 bucket. The backups must not be deleted for at least 3 months after the backups are created.
What should a CloudOps engineer do to meet this requirement?
- A. Enable S3 Object Lock on a new S3 bucket in governance mode. Place all backups in the new S3 bucket with a retention period of 3 months.
- B. Enable S3 Object Lock on a new S3 bucket in compliance mode. Place all backups in the new S3 bucket with a retention period of 3 months.
- C. Configure an IAM policy that denies the s3:DeleteObject action for all users. Remove the policy after three months.
- D. Enable S3 Versioning on the existing S3 bucket. Configure S3 Lifecycle rules to protect the backups.
Answer: B
Explanation:
Comprehensive Explanation (250-350 words):
Amazon S3 Object Lock in compliance mode provides immutable storage that prevents objects from being deleted or overwritten for a defined retention period. In compliance mode, even the root user cannot remove the retention or delete the object before the retention period expires. This makes it suitable for regulatory and strict data-protection requirements.
Because Object Lock must be enabled at bucket creation time, a new bucket is required. Setting a retention period of 3 months ensures that backups cannot be deleted before that time under any circumstances.
Option D (governance mode) allows privileged users to bypass retention, which violates the strict "must not be deleted" requirement. Option A relies on IAM policy changes, which are reversible and error-prone.
Option C does not prevent deletion; versioning only retains previous versions if objects are deleted, but users can still delete versions unless additional controls are applied.
Therefore, S3 Object Lock in compliance mode is the correct and most secure solution.
NEW QUESTION # 108
A company runs an application on Amazon EC2 that connects to an Amazon Aurora PostgreSQL database. A developer accidentally drops a table from the database, causing application errors.
Two hours later, a CloudOps engineer needs to recover the data and make the application functional again.
Which solution will meet this requirement?
- A. Perform a point-in-time recovery on the existing database to restore the database to a specified point in time, 2 hours in the past.
- B. Create a new Aurora cluster. Choose the Restore data from S3 bucket option. Choose log files up to the failure time 2 hours in the past.
- C. Use the Aurora Backtrack feature to rewind the database to a specified time, 2 hours in the past.
- D. Perform a point-in-time recovery and create a new database to restore the database to a specified point in time, 2 hours in the past. Reconfigure the application to use a new database endpoint.
Answer: D
Explanation:
In the AWS Cloud Operations and Aurora documentation, when data loss occurs due to human error such as dropped tables, Point-in-Time Recovery (PITR) is the recommended method for restoration. PITR creates a new Aurora cluster restored to a specific time before the failure.
The restored cluster has a new endpoint that must be reconfigured in the application to resume normal operations. AWS does not support performing PITR directly on an existing production database because that would overwrite current data.
Aurora Backtrack (Option A) applies only to Aurora MySQL, not PostgreSQL. Option B is incorrect because PITR cannot be executed in place. Option D refers to an import process from S3, which is unrelated to time-based recovery.
Hence, Option C is correct and follows the AWS CloudOps standard recovery pattern for PostgreSQL workloads.
NEW QUESTION # 109
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