4.3.4. Sample Questions - Domain 4: Monitoring & Logging
Question 1:
A DevOps team needs to collect custom metrics from their application running on Amazon EC2 instances, such as the number of active user sessions and specific business transaction counts. These metrics are not available by default in CloudWatch. Which is the most efficient way to collect and send these custom metrics to CloudWatch?
A) Use AWS CloudTrail to log application events and create metrics from them. B) Configure Amazon Kinesis Data Firehose to stream application logs to CloudWatch. C) Install and configure the CloudWatch Agent on the EC2 instances. D) Develop a Lambda function to periodically poll the application and push metrics.
Correct Answer: C
Explanation:
- C) Install and configure the CloudWatch Agent on the EC2 instances: The CloudWatch Agent is specifically designed to collect system-level metrics (e.g., memory, disk, CPU, network) and logs from EC2 instances and on-premises servers. Crucially, it also supports collecting custom metrics from applications running on these instances. This is the most direct and efficient way to collect the required custom metrics, aligning with the First Principle of Centralized Observability and Data Collection.
Question 2:
A company wants to analyze their application logs in real-time to identify errors and performance bottlenecks. The logs are currently being streamed to CloudWatch Logs. They need a solution that allows them to perform ad-hoc queries and visualize log data without exporting it to another service. Which CloudWatch Logs feature should they use?
A) CloudWatch Alarms B) CloudWatch Dashboards C) CloudWatch Logs Insights D) CloudWatch Metric Filters
Correct Answer: C
Explanation:
- C) CloudWatch Logs Insights: CloudWatch Logs Insights is a fully integrated, interactive query service that enables you to search and analyze your log data in CloudWatch Logs. It allows you to perform powerful ad-hoc queries, discover fields, and visualize log data directly within the CloudWatch console, aligning with the First Principle of Actionable Insights from log data.
