DOP-C02 Exam Dumps : AWS Certified DevOps Engineer - Professional

To meet the requirements, the DevOps engineer should do the following:

Turn on the Multi-AZ option on the Aurora cluster.

Update the application to use the Aurora cluster endpoint for write operations.

Update the Aurora cluster's reader endpoint for reads.

Turning on the Multi-AZ option will create a replica of the database in a different Availability Zone. This will ensure that the database remains available even if one of the Availability Zones is unavailable.

Updating the application to use the Aurora cluster endpoint for write operations will ensure that all writes are sent to both the primary and replica databases. This will ensure that the data is always consistent.

Updating the Aurora cluster's reader endpoint for reads will allow the application to read data from the replica database. This will improve the performance of the application during the maintenance window.

The requirement is not just to perform a one-time upgrade, but to ensure that Kubernetes and related components stay continuously within the AWS standard support window, with minimal ongoing effort. EKS Auto Mode is designed to reduce operational burden by managing cluster infrastructure, including control plane and data plane lifecycle, in a more automated fashion. When EKS Auto Mode is enabled and existing managed node groups are removed, EKS can manage compute capacity and associated upgrades in a more integrated, hands-off way, tracking supported versions automatically.

Option A (aws eks update-cluster-version) and Option C (eksctl upgrade) are both manual upgrade mechanisms. They can update clusters to a specific version but do not continuously ensure future upgrades as new supported versions are released; they require the DevOps team to schedule and execute each upgrade. Option D (IaC refactor) is generally a good practice but does not inherently provide automatic version lifecycle management; it also introduces significant upfront effort compared to enabling Auto Mode.

Thus, enabling EKS Auto Mode and deprecating manual managed node groups provides the least operational overhead for staying within the EKS-supported version schedule.

Verified Answer: A, C, and E.

Short Explanation: To improve the performance of the application, the DevOps engineer should use Amazon RDS Proxy, implement the database connection opening outside the Lambda event handler code, and connect to the proxy endpoint from the Lambda function.

Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure1. By using Amazon RDS Proxy, the DevOps engineer can reduce the overhead of opening and closing connections to the database, which can improve latency and throughput2.

The DevOps engineer should connect the proxy to the Aurora cluster reader endpoint, which allows read-only connections to one of the Aurora Replicas in the DB cluster3. This can help balance the load across multiple read replicas and improve performance for read-intensive workloads4.

The DevOps engineer should implement the database connection opening outside the Lambda event handler code, which means using a global variable to store the database connection object5. This can enable connection reuse across multiple invocations of the Lambda function, which can reduce latency and improve performance.

The DevOps engineer should connect to the proxy endpoint from the Lambda function, which is a unique URL that represents the proxy. This can allow the Lambda function to access the database through the proxy, which can provide benefits such as connection pooling, load balancing, failover handling, and enhanced security.

The other options are incorrect because:

Implementing database connection pooling inside the Lambda code is unnecessary and redundant when using Amazon RDS Proxy, which already provides connection pooling as a service.

Implementing the database connection opening and closing inside the Lambda event handler code is inefficient and costly, as it can increase latency and consume more resources for each invocation of the Lambda function.

Connecting to the Aurora cluster endpoint from the Lambda function is not optimal for read-only queries, as it can direct traffic to either the primary instance or one of the Aurora Replicas in the DB cluster. This can result in inconsistent performance and potential conflicts with write operations on the primary instance.