AWS Lambda Test

This skill focuses on configuring and understanding the triggers that invoke Lambda functions. Candidates are evaluated on how Lambda integrates with services like S3, API Gateway, DynamoDB, and EventBridge. Proper configuration ensures that events are reliably captured and routed, which is essential for building responsive and decoupled serverless applications. It also includes understanding sync vs async invocation models and batching behavior.

This skill assesses the ability to track and diagnose Lambda behavior using AWS tools such as CloudWatch Logs, CloudWatch Metrics, and X-Ray. Candidates are tested on understanding cold starts, invocation metrics, error tracing, and setting up alerts. Strong observability is vital for maintaining system reliability, optimizing performance, and responding quickly to failures in production environments.

This skill covers deploying Lambda functions using tools like AWS CLI, SAM, Serverless Framework, and integrating with CI/CD pipelines (e.g., CodePipeline, GitHub Actions). It also includes understanding versioning, aliases, and traffic shifting strategies like blue/green or canary deployments. Automating deployments ensures consistency, reliability, and faster delivery cycles in serverless applications.

This skill tests knowledge of how Lambda scales under load, the role of concurrency limits, provisioned concurrency, and performance tuning via memory and timeout settings. Candidates must understand how to manage cold starts and handle burst workloads efficiently. Optimizing concurrency and resource settings is critical for achieving performance SLAs while controlling costs.

This area evaluates handling of failures in Lambda execution. It includes understanding retry policies for different event sources, using DLQs (Dead Letter Queues), and defining fallback mechanisms. Proper error handling ensures resilience in serverless systems and prevents data loss or repeated failures, especially in asynchronous and stream-based architectures.

This skill emphasizes understanding the cost model of Lambda—charges based on invocations, duration, and memory—and strategies to reduce costs. It includes identifying redundant invocations, tuning function resources, and leveraging architectural patterns that minimize Lambda execution time. Cost-effective Lambda design directly impacts the scalability and economic viability of serverless solutions.

This skill area ensures that candidates understand the programming languages supported by Lambda (e.g., Python, Node.js, Java), handler function syntax, and the differences in cold start behavior and packaging across runtimes. Knowing how runtimes affect performance and deployment is essential for choosing the right language and structuring functions effectively.

This area tests the candidate’s ability to design serverless solutions using Lambda in common use cases like web APIs, data pipelines, real-time processing, and IoT. It includes event-driven architecture patterns and best practices. Understanding when and how to use Lambda enables developers to build scalable, maintainable, and cloud-native applications.

This skill assesses deeper technical knowledge including custom runtimes, Lambda Extensions, sandbox limitations, and diagnosing failed executions. Candidates are tested on identifying issues like permission errors, timeouts, or SDK misconfiguration. Mastery here is key for developers building complex, enterprise-grade serverless solutions that demand deeper customization and reliability.

This skill evaluates knowledge of managing Lambda usage at scale—through tagging, billing visibility, compliance enforcement, and third-party observability tools (like Datadog, New Relic). It also includes access auditability and lifecycle tracking. Governance ensures that Lambda usage aligns with organizational policies, cost controls, and operational maturity standards.

This area evaluates how well a candidate understands IAM roles, policies, and security best practices for Lambda functions. It covers assigning execution roles, applying least-privilege principles, and securing environment variables. Proper permission management ensures that Lambda functions interact securely with other AWS services, reducing risk of unauthorized access, privilege escalation, or data leakage in production environments.

This skill focuses on setting up key Lambda parameters like memory, timeout, environment variables, runtime, and IAM roles. Proper configuration ensures efficient performance, secure access, and seamless integration with other AWS services.