Kafka Streams automatically creates internal topics —such as changelog and repartition topics— based on the structure of a topology. 

While convenient, this mechanism can be fragile : small topology changes like reordering processors or inserting a new step may alter internal topic names, breaking state reuse and causing unexpected reprocessing in production.

KIP‑1111 introduces a solution : it allows Kafka Streams applications to enforce explicit naming for internal resources and fail fast at startup when auto-generated names are still present.

In a short, demo-driven session 🎬, I will:

• 🔍 Show how topology-derived internal topic naming can unintentionally break stateful applications
• ⚙️ Demonstrate how to enable and use KIP‑1111 in a real Kafka Streams application
• 📈 Explain how explicit internal topic names simplify upgrades and monitoring

Attendees will leave with a clear understanding of why explicit internal naming matters, how KIP‑1111 catches problems early, and when to adopt this approach in production Kafka Streams applications.