My Experience with AWS DevOps Agent – Builders Skill Sprint
A hands-on journey exploring AWS DevOps Agent through real-world troubleshooting scenarios involving AWS Lambda, EC2, CloudWatch, and infrastructure diagnostics.
My Experience with AWS DevOps Agent – Builders Skill Sprint
Introduction
I recently participated in the AWS DevOps Agent Builders Skill Sprint organized by the AWS User Group. This hands-on learning experience introduced me to AWS DevOps Agent, an AI-powered operational assistant that helps investigate infrastructure issues, identify root causes, and recommend solutions.
Throughout the sprint, I worked on multiple real-world troubleshooting scenarios involving AWS Lambda, Amazon EC2, CloudWatch alarms, and infrastructure diagnostics.
Challenge 2 – First Investigation
The first challenge involved a Lambda function that failed every time it was invoked.
Investigation
Using AWS DevOps Agent, I analyzed the failing Lambda function and discovered the root cause.
Root Cause
The function referenced an undefined variable:
1
return {"result": config["value"]}
Since
config was never defined, the function generated a NameError and failed on every invocation.Learning Outcome
This challenge demonstrated how AWS DevOps Agent can quickly identify code-level issues by analyzing logs and runtime behavior.
Challenge 3 – Stress and Diagnose
The third challenge focused on diagnosing performance issues in an EC2 instance.
Scenario
I connected to the EC2 instance using AWS Systems Manager Session Manager and intentionally stressed the CPU using:
1
for i in $(seq $(nproc)); do yes > /dev/null & done
This caused CPU utilization to reach nearly 100%.
Investigation
CloudWatch alarms detected the high CPU utilization and AWS DevOps Agent investigated the issue.
Findings
- CPU utilization reached 100%
- The running
yesprocesses were consuming all available CPU resources - The instance was experiencing resource exhaustion
Recovery
The issue was resolved using:
1
pkill yes
CPU utilization returned to normal and the alarm recovered successfully.
Challenge 4 – Bad Deploy Detective
This challenge focused on application failures after deployment or configuration changes.
Scenario
A Lambda-based application began failing after configuration modifications.
Investigation
AWS DevOps Agent examined the Lambda configuration, environment variables, IAM permissions, and dependencies.
Findings
The investigation identified configuration and permission-related issues affecting application functionality.
Learning Outcome
This challenge showed how AWS DevOps Agent can correlate operational failures with recent infrastructure changes and provide actionable recommendations.
Challenge 5 – Build Your Own Scenario
For the final challenge, I created my own failure scenario.
Scenario
I built a Lambda function designed to exceed its configured execution timeout.
Configuration:
- Lambda timeout: 3 seconds
- Function execution delay: 60 seconds
As expected, every invocation failed.
Investigation
AWS DevOps Agent analyzed the Lambda function and identified the root cause.
Root Cause
The configured timeout was too low for the function's execution duration.
Recommendation
Increase the Lambda timeout value to allow the function sufficient execution time.
Learning Outcome
This challenge highlighted how operational limits such as timeout settings can affect application reliability.
Key Takeaways
During this sprint, I learned:
- How AWS DevOps Agent performs root-cause analysis
- How CloudWatch alarms help monitor system health
- Troubleshooting AWS Lambda failures
- Diagnosing EC2 performance bottlenecks
- Investigating infrastructure issues using natural language queries
- Understanding the value of AI-assisted operations
The most valuable aspect of the sprint was seeing how AWS DevOps Agent reduced the time required to identify and understand operational problems.
Conclusion
The AWS DevOps Agent Builders Skill Sprint provided practical experience in cloud operations, monitoring, and incident investigation. It demonstrated how AI-assisted tools can simplify troubleshooting and improve operational efficiency.
I look forward to applying these skills in future AWS projects and continuing my cloud learning journey.
GitHub Repository
Author
Joshikas B P
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