Introducing Apache Spark upgrade agent for Amazon EMR

This article introduces an AI-powered Apache Spark upgrade agent for Amazon EMR that automates version upgrades, reducing manual effort from months to hours.

• Conversational AI agent handles code analysis, API deprecation fixes, and dependency updates
• Six-phase automated workflow: planning, environment setup, code transformation, local validation, EMR validation, data quality checks
• Operates as managed MCP server with IAM-governed access and CloudTrail auditability
• Assessment dashboard helps identify which Spark applications should be prioritized for migration
• Integrates with IDEs like Kiro and supports CI/CD pipeline integration via Git branches
• Sample upgrade from Spark 3.0 to 3.5 reduced manual work from 8 hours to 30 minutes
• Available through Amazon Q Developer CLI, Kiro IDE, or custom agent frameworks

The Spark upgrade agent transforms complex version upgrades into manageable workflows, enabling organizations to maintain current Spark environments without significant resource constraints.