Amazon Web Services DVA-C02 Exam With Confidence Using Practice Dumps

This solution will solve the deployment issue by deploying the new version of the application to one new EC2 instance at a time, while keeping the old version running on the existing instances. This way, there will always be at least four instances serving traffic during the deployment, and no downtime or performance degradation will occur. Option A is not optimal because it will increase the cost of running the Elastic Beanstalk environment without solving the deployment issue. Option B is not optimal because it will split the traffic between two versions of the application, which may cause inconsistency and confusion for the customers. Option D is not optimal because it will deploy the new version of the application to two existing instances at a time, which may reduce the capacity below four instances during the deployment.

Centralized logging for microservices means collecting application logs from many services into a single managed logging backend where logs can be searched, retained, and monitored. For containerized microservices on AWS, the standard approach is to send each service’s stdout/stderr logs to Amazon CloudWatch Logs.

Option A is the appropriate solution: create separate CloudWatch Logs streams (and typically log groups) per microservice. This scales naturally as microservices increase, supports retention policies, metric filters, alarms, and integrations with tools like CloudWatch Logs Insights for querying across services. Container orchestrators (ECS/EKS) can be configured to use the CloudWatch Logs log driver so logs are shipped automatically without custom log shipping agents.

Option B (CloudTrail) logs AWS API activity, not application logs.

Option C (VPC Flow Logs) captures network flow metadata, not application-level logs.

Option D (Cloud Map) is service discovery, not logging.

Therefore, using CloudWatch Logs streams per microservice is the correct central logging approach.