A company is developing an application that runs across a combination of Amazon EC2 On-Demand...

Option A satisfies all requirements with the most direct, purpose-built AWS logging workflow. By using the CloudWatch Agent (or fluent-bit / unified logging configuration) on each EC2 instance—regardless of whether it is On-Demand or Spot—the application logs can be centralized into asingle Amazon CloudWatch Logs log group. Centralization ensures the logs remain available even as Spot Instances are interrupted and replaced. Access control is handled withIAM policies(and optionally resource policies/KMS encryption) so that only a specific set of users can read/query the log group.

For analysis,CloudWatch Logs Insightsprovides an interactive query language that is SQL-like and commonly treated as “SQL queries” for troubleshooting. It enables fast filtering, aggregation, and pattern detection across large log volumes without building a separate data lake pipeline. This supports event-pattern analysis and root cause investigation directly from the centralized log group.

Option B is incorrect because Logs Insights queries CloudWatch Logs data, not arbitrary log files sitting in S3. Option C is inefficient (many log groups) and Athena cannot directly query CloudWatch log groups as a native data source. Option D is incorrect because Amazon Detective is for security investigations across supported data sources and is not the primary service for ad-hoc SQL-style querying of application logs.