Content Domain 4: Troubleshooting and Optimization
Tasks
Task 4.1: Assist in a root cause analysis.
Skill 4.1.1: Debug application code and service integration issues to identify defects.
Skill 4.1.2: Interpret application metrics, logs, and traces.
Skill 4.1.3: Query logs to find relevant data.
Skill 4.1.4: Troubleshoot deployment failures by using output logs.
Skill 4.1.5: Use AWS AI tools to analyze errors and to generate troubleshooting suggestions.
Task 4.2: Apply logging, monitoring, and observability best practices.
Skill 4.2.1: Implement effective logging strategies to record application behavior and state (for example, by using structured logging for application events and user actions).
Skill 4.2.2: Implement code that emits custom metrics.
Skill 4.2.3: Implement notification alerts for specific actions (for example, quota limits, deployment completions).
Skill 4.2.4: Implement tracing by using AWS services and tools.
Skill 4.2.5: Monitor workload health (for example, by using application health checks, liveness and readiness probes).
Task 4.3: Optimize applications by using AWS services and features.
Skill 4.3.1: Apply concurrency concepts (for example, AWS Lambda provisioned concurrency, Amazon EC2 Auto Scaling, thread pool management, connection pooling).
Skill 4.3.2: Optimize memory and compute power for an application.
Skill 4.3.3: Optimize application messaging (for example, by using Amazon SQS queues, Amazon SNS fan-out patterns).
Skill 4.3.4: Implement caching by using AWS services (for example, Amazon ElastiCache, Amazon DynamoDB Accelerator [DAX], Amazon CloudFront).
Skill 4.3.5: Detect performance bottlenecks by using AWS services (for example, Amazon CloudWatch).
Skill 4.3.6: Use AWS AI tools to identify optimization opportunities (for example, performance bottleneck detection, resource usage optimization, code efficiency improvement).