✨ Workload Optimization

Overview

Workload Optimization will check the Spark jobs you run on IOMETE and recommend settings worth changing. This item covers its first version, built on rule-based checks.

What it will do

• Run checks against your real Spark jobs and flag Spark settings worth changing.
• Point to the settings most likely behind a job that ran slowly.

How it will work

• It will run inside your IOMETE deployment and see only the jobs the asking user can see.
• Recommendations only: it will not change any job or compute cluster settings itself.

Where you will see it

• In the IOMETE console.
• Through MCP, so AI agents can ask for recommendations too.

Where it fits

Its first version uses rule-based checks. Recommendations from an LLM-based agent will follow as their own roadmap item, reaching models through the Model Gateway.

‍