Jeff’s Note #
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 how to efficiently collect and alarm on performance data with minimal code and operational overhead. In production, this is about knowing exactly how to push custom metrics to CloudWatch and trigger alerts without managing extra infrastructure or polling logic. Let’s drill down.
The Certification Drill (Simulated Question) #
Scenario #
A digital media startup deploys an image recognition application on a single Amazon EC2 instance. Each image must be processed within 5 seconds to meet SLAs. If processing takes longer than 5 seconds for any image, the engineering team must be immediately notified via email or push alert. The team wants to implement this monitoring and notification system with minimal operational complexity and maintenance effort.
The Requirement: #
Design a solution to measure processing time for each image, detect when it exceeds 5 seconds, and notify the team automatically while minimizing the development and operational overhead.
The Options #
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A) Create an Amazon CloudWatch custom metric. Each time an image is processed, publish the processing time as a metric value. Configure a CloudWatch alarm based on a static threshold of 5 seconds. Notify the team using an Amazon Simple Notification Service (Amazon SNS) topic.
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B) Create an Amazon Simple Queue Service (Amazon SQS) queue. Publish each processing time to the queue. Develop an external application that consumes the queue, checks if any processing time exceeds 5 seconds, then sends an SNS notification.
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C) Create an Amazon CloudWatch custom metric. Publish each processing time. Set a CloudWatch alarm that triggers when the average processing time exceeds 5 seconds. Notify the team by sending an Amazon Simple Email Service (Amazon SES) message.
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D) Create an Amazon Kinesis data stream. Send each processing time to the stream. Configure a CloudWatch alarm that enters ALARM state if any records exceed 5 seconds. Use SNS to notify the team.
Google adsense #
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Correct Answer #
A
Quick Insight: The Developer Imperative #
- Effective application monitoring with the least operational overhead involves pushing custom metrics directly from the application to Amazon CloudWatch.
- Leveraging CloudWatch alarms based on static thresholds enables immediate detection of slow processing events.
- Combining CloudWatch alarms with SNS simplifies notifications without additional polling or custom consumers.
- Choices involving queues or Kinesis add unnecessary complexity and operational burden for this use case.
Content Locked: The Expert Analysis #
You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?
The Expert’s Analysis #
Correct Answer #
Option A
The Winning Logic #
Publishing the processing time as a custom CloudWatch metric directly from the application allows immediate, per-event metric granularity. Setting a CloudWatch alarm on a static threshold of 5 seconds ensures the alarm triggers precisely when any processing time crosses the SLA boundary.
The alarm can then notify the development team using SNS, which is a fully managed pub-sub notification service requiring minimal setup.
Key developer advantages here:
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No additional infrastructure (queues, consumers, streams) to build or maintain.
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CloudWatch custom metrics can be pushed via AWS SDK APIs (
PutMetricData), straightforward for developers. -
CloudWatch alarms support threshold-based triggers with flexible evaluation periods.
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SNS integration is direct, reliable, and supported natively by CloudWatch alarms.
The Trap (Distractor Analysis): #
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Option B: Using SQS adds complexity. You must build and run an extra consumer application to process the queue and identify slow events, increasing operational overhead and failure points.
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Option C: Triggering on average processing time is inappropriate for SLA breaches on any single image. Averages can mask individual slow events, causing delayed or missed alerts. Also, SES requires extra setup for email compared to SNS notifications.
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Option D: Kinesis streams are designed for high-throughput event streaming; deploying and operating a Kinesis stream here is overkill and adds complexity unrelated to simple monitoring.
The Technical Blueprint #
# Example AWS CLI to publish a single custom metric
aws cloudwatch put-metric-data --namespace "ImageProcessingApp" \
--metric-name "ProcessingTime" --value 6.1 \
--unit Seconds --timestamp "$(date -Is)"
# Example CLI to create a CloudWatch alarm on threshold 5 seconds
aws cloudwatch put-metric-alarm --alarm-name "HighProcessingTime" \
--metric-name "ProcessingTime" --namespace "ImageProcessingApp" \
--statistic Maximum --period 60 --evaluation-periods 1 \
--threshold 5 --comparison-operator GreaterThanThreshold \
--alarm-actions arn:aws:sns:region:account-id:DevTeamNotificationTopic
The Comparative Analysis (DVA-C02) #
| Option | API Complexity | Performance | Use Case |
|---|---|---|---|
| A | Low — direct put-metric | Immediate alert | Simple per-event time tracking + alerting |
| B | High — build queue consumer | Moderate | Complex, operationally heavy notification |
| C | Moderate | May miss spikes | Average-based alerting, poor for SLA breaches |
| D | High | Overkill | Heavy infrastructure for minimal benefit |
Real-World Application (Practitioner Insight) #
Exam Rule #
For the exam, always pick CloudWatch custom metrics + CloudWatch alarms + SNS when you see per-event SLA thresholds and notification requirements.
Real World #
In production, you might add additional layers like AWS X-Ray or Lambda for deeper tracing or distributed processing; but for a monolithic EC2 app requiring simple timing alerts, this remains the lowest overhead and most maintainable approach.
(CTA) Stop Guessing, Start Mastering #
Disclaimer
This is a study note based on simulated scenarios for the AWS DVA-C02 exam.