Serverless data processing using AWS Lambda for event-driven data pipelines, transformations, and integrations.
Learners will master serverless computing concepts with AWS Lambda, develop event-driven data processing functions, implement Lambda-based ETL workflows, and integrate Lambda with other AWS services for scalable data engineering solutions.
Serverless architecture principles, benefits and limitations, use cases for data engineering, and cost considerations.
Function creation, deployment, runtime environments, dependencies management, and development best practices.
Data format conversion, validation, enrichment, aggregation, and transformation patterns using Lambda.
Memory and timeout configuration, cold start optimization, concurrency management, and performance monitoring.
Error handling patterns, retry mechanisms, dead letter queues, CloudWatch integration, and troubleshooting techniques.
API Gateway integration, Step Functions orchestration, database connections, and microservices patterns for data engineering.
S3 events, Kinesis streams, DynamoDB streams, SQS, SNS, and custom event sources for Lambda triggers.