Something strange is happening in the Spark clusters.Memory thresholds are breached. Jobs mutate. Performance vanishes. And in the middle of it all, a single question lingers: Did we configure the pool… or awaken something else?In this episode, Frank and Kevin dig deep into the mysterious world of executor memory management in Microsoft Fabric. What happens when your jobs outgrow the starter pool? Is it really just a configuration issue — or is there something more sinister lurking in your autoscaling?

They’ll unpack:

- The limits of the starter Spark pool
- Why some jobs demand more memory than expected
- How to fix performance using custom pools and dynamic allocation
- When to say: "This job needs more than Fabric wants to give"

🧠 The Memory Mutation is real — and it starts with your next workload.

👾 Stream the episode now before your cluster crashes first.