AWS DVA-C02 Drill: Collecting Custom Metrics - CloudWatch Agent vs X-Ray Agent

Jeff’s Note

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Unlike generic exam dumps, ADH analyzes this scenario through the lens of a Real-World Lead Developer.

For DVA-C02 candidates, the confusion often lies in knowing which AWS service or agent is designed specifically for collecting detailed infrastructure and custom metrics versus tracing application requests. In production, this is about knowing exactly how to instrument your EC2 instances to collect both system-level and custom app-level metrics with minimal code changes and maximum efficiency. Let’s drill down.

The Certification Drill (Simulated Question)

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Scenario

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TechTrendz, a software company, runs a high-traffic web application on Amazon EC2 instances behind an Auto Scaling group. The application workload fluctuates significantly throughout the day. The engineering team needs to gather detailed operating system and EC2 instance metrics like CPU, memory, and disk usage to optimally size their instances. Additionally, they want to monitor custom application-level metrics such as request latency and processed transaction counts to ensure smooth performance and identify bottlenecks early.

The Requirement:

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Select the best solution to collect comprehensive EC2 instance operating metrics and custom application metrics efficiently and with minimal development overhead.

The Options

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• A) Install the AWS X-Ray agent on the EC2 instances. Configure it to collect both EC2 instance metrics and custom application metrics.
• B) Install the Amazon CloudWatch agent on the EC2 instances. Configure it to gather EC2 instance metrics and custom application metrics.
• C) Embed the AWS SDK within the application code. Modify the application to push both EC2 instance metrics and custom application metrics directly to CloudWatch.
• D) Enable AWS CloudTrail to track and analyze EC2 instance metrics alongside custom application metrics.

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Correct Answer

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B

Quick Insight: The Developer’s Instrumentation Imperative

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The Amazon CloudWatch agent is purpose-built for collecting detailed system-level metrics and supports custom metrics collection through configuration files, allowing quick turn-up without recoding the app. In contrast, AWS X-Ray is designed primarily for distributed tracing, not collecting OS-level metrics. Embedding the AWS SDK for metrics collection increases development complexity unnecessarily. CloudTrail focuses on API call auditing, not metrics.

Content Locked: The Expert Analysis

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You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?

The Expert’s Analysis

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Correct Answer

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Option B

The Winning Logic

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The Amazon CloudWatch agent is designed for exactly this use case: collecting detailed OS-level metrics from EC2 instances such as CPU, memory, disk, and network metrics. It also supports custom metrics collection through JSON or TOML configuration files, enabling aggregation of application-specific metrics without modifying the app code. This agent runs as a process on the instance and pushes metrics seamlessly to CloudWatch.

• Why CloudWatch Agent? It offers out-of-box integration, support for common OS metrics (Linux and Windows), and flexible custom metric collection formats.
• Why not X-Ray? AWS X-Ray primarily provides distributed request tracing for applications and services. It does not gather host-level performance metrics like CPU or memory usage.
• Why not AWS SDK in-app? While technically feasible, embedding metric publishing logic in your app requires additional dev time, risks affecting app performance, and complicates maintenance.
• Why not CloudTrail? CloudTrail focuses on auditing AWS API operations and changes. It does not capture performance or health metrics of EC2 instances or applications.

The Trap (Distractor Analysis):

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• Why not A? Confusing tracing with metrics. X-Ray traces requests but does not provide granular instance CPU/memory metrics or custom metric ingestion.
• Why not C? Overengineering the solution by complicating the application code for metrics already provided by an agent.
• Why not D? CloudTrail logs management API calls but does not provide monitoring of system or app performance metrics.

The Technical Blueprint

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B) For Developer (Code/CLI Snippet)

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Here’s an example command to install and configure the CloudWatch agent on an EC2 instance using SSM:

# Download and install CloudWatch Agent
sudo yum install -y amazon-cloudwatch-agent

# Create CloudWatch agent config JSON (example snippet)
cat << 'EOF' > /opt/aws/amazon-cloudwatch-agent/bin/config.json
{
  "metrics": {
    "append_dimensions": {
      "AutoScalingGroupName": "${aws:AutoScalingGroupName}",
      "InstanceId": "${aws:InstanceId}"
    },
    "metrics_collected": {
      "cpu": {
        "measurement": [
          "cpu_usage_idle",
          "cpu_usage_iowait"
        ],
        "metrics_collection_interval": 60
      },
      "mem": {
        "measurement": [
          "mem_used_percent"
        ],
        "metrics_collection_interval": 60
      },
      "statsd": {
        "service_address": ":8125"
      }
    }
  }
}
EOF

# Start agent with config
sudo /opt/aws/amazon-cloudwatch-agent/bin/amazon-cloudwatch-agent-ctl \
  -a fetch-config -m ec2 -c file:/opt/aws/amazon-cloudwatch-agent/bin/config.json -s

The Comparative Analysis

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Real-World Application (Practitioner Insight)

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Exam Rule

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For the exam, always pick CloudWatch Agent when you need to collect detailed OS-level and custom metrics from EC2 instances without modifying application code.

Real World

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In production, developers often combine CloudWatch Agent with application logging libraries (e.g., StatsD or Prometheus exporters) that feed metrics to CloudWatch or other observability platforms via agents, avoiding tight coupling metric publishing logic in apps.

(CTA) Stop Guessing, Start Mastering

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Disclaimer

This is a study note based on simulated scenarios for the AWS DVA-C02 exam.