A data engineer must orchestrate a pipeline that includes a single AWS Lambda function followed by one AWS Glue job and must use AWS-managed services. Which approach delivers this with the least operational overhead?

AWS Step Functions is the most suitable choice for orchestrating this pipeline with the least operational overhead because it is a fully managed service designed for coordinating distributed applications and microservices using visual workflows. It natively integrates with AWS Lambda and AWS Glue, allowing you to define the sequence of execution directly within the state machine. This eliminates the need for managing underlying infrastructure. Deploying Apache Airflow on Amazon EC2 or Amazon EKS introduces significant operational overhead. You would be responsible for provisioning, managing, patching, and scaling the EC2 instances or the EKS cluster, as well as maintaining the Airflow installation itself. While AWS Glue workflows can orchestrate Glue jobs, they have more limited native integration with Lambda functions compared to Step Functions, often requiring custom Glue job types or external triggers for Lambda.