3.2.3. Debugging Strategies & Tools
First Principle: Effective debugging relies on systematic problem-solving, leveraging comprehensive data (logs, metrics, traces), and specialized tools to rapidly identify and resolve application issues in the cloud.
For developers, efficient debugging in a cloud environment requires a shift from traditional local debugging to understanding distributed systems.
Key Debugging Strategies & Tools:
- Systematic Problem Solving:
- Reproduce the Issue: Try to recreate the problem in a development or testing environment.
- Isolate Components: Narrow down the problem to a specific service or function.
- Hypothesize & Test: Formulate theories about the cause and test them.
- Leveraging Data Sources:
- CloudWatch Logs: The primary source for application-generated logs (print statements in Lambda, syslog for EC2, container logs for ECS). Use CloudWatch Logs Insights for querying.
- CloudWatch Metrics: Monitor metrics like CPU utilization, error rates, latency to identify abnormal behavior.
- AWS X-Ray Traces: Essential for distributed applications. Trace requests to see latency across services and find where failures occur.
- AWS CloudTrail Logs: For debugging issues related to AWS API calls or IAM permissions.
- Specialized Tools:
- AWS Systems Manager Session Manager: Secure shell access to EC2 instances for direct debugging without opening SSH ports.
- AWS CLI/SDKs: Programmatic inspection of resource states.
Scenario: Your application, deployed across multiple Lambda functions and an API Gateway endpoint, is intermittently returning errors. You've checked basic CloudWatch metrics, but need to pinpoint the exact line of code or service interaction causing the error.
ā ļø Exam Trap: When debugging Lambda, check CloudWatch Logs FIRST (function output and errors), then X-Ray (distributed tracing). Don't jump to code changes before checking logs ā the exam expects a systematic debugging approach.
