DOP-C02 Monitoring and Logging Practice Question
A media company runs a video transcoding pipeline on AWS. The pipeline uses AWS Step Functions to orchestrate multiple Lambda functions that transcode video files stored in Amazon S3. The company wants to implement a monitoring solution to track the progress of each workflow execution, including which step is currently running, the duration of each step, and any errors. The solution should provide near real-time visibility and allow the team to troubleshoot failed executions quickly. Which solution meets these requirements?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Amazon EventBridge to capture Step Functions execution status changes and build a custom dashboard in CloudWatch.
Amazon EventBridge (formerly CloudWatch Events) can capture Step Functions execution state changes (e.g., step started, succeeded, failed). These events can be used to build a custom dashboard in CloudWatch, providing near real-time visibility into workflow progress, step durations, and errors. Option A is incorrect because creating custom metrics from Lambda functions requires additional instrumentation and does not provide workflow-level context easily. Option C is incorrect because CloudWatch Logs Insights queries are not near real-time; they require searching through logs, and the solution needs real-time visibility. Option D is incorrect because AWS X-Ray provides distributed tracing for individual requests, but it does not offer high-level workflow step tracking with durations and errors aggregated across executions in near real-time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create custom CloudWatch metrics from Lambda functions for each step, and build a CloudWatch dashboard.
Why it's wrong here
Custom CloudWatch metrics emitted from Lambda functions track aggregate performance but lack the workflow-level state machine context, such as which Step Functions step is currently executing or the transition timing between steps. This approach cannot correlate individual metric datapoints to a specific execution’s step progression, failing the requirement for near real-time visibility of each workflow’s current step. It is tempting because CloudWatch dashboards effectively visualise aggregated operational metrics, and would be correct for monitoring overall pipeline health or Lambda invocation rates across all executions.
- ✓
Use Amazon EventBridge to capture Step Functions execution status changes and build a custom dashboard in CloudWatch.
Why this is correct
Correct. Amazon EventBridge captures Step Functions execution state changes (e.g., 'ExecutionStarted', 'TaskStateEntered', 'ExecutionFailed') in near real-time. These events can be used to build a CloudWatch dashboard that shows the current step, duration per step, and errors, meeting all requirements without custom instrumentation.
- ✗
Configure each Lambda function to write logs to CloudWatch Logs with the execution ID, and use CloudWatch Logs Insights to query and visualize.
Why it's wrong here
Incorrect. While Lambda logs to CloudWatch Logs, querying with Logs Insights is not near real-time and requires manual querying. It does not provide a continuous dashboard for monitoring workflow progress. Also, correlating logs across steps requires complex parsing of execution IDs.
- ✗
Enable AWS X-Ray tracing on the Step Functions and Lambda functions to get a service map and trace details.
Why it's wrong here
Incorrect. AWS X-Ray provides detailed tracing of service calls and latencies, but it is designed for distributed tracing of individual requests, not for aggregating workflow-level metrics like step durations and execution progress. It also adds additional overhead and cost, and does not inherently provide a dashboard for near real-time visibility.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DOP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DOP-C02 exam.