> ## Documentation Index
> Fetch the complete documentation index at: https://docs.conduktor.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Advanced pattern support Interceptors

> Advanced patterns in Conduktor Gateway Interceptors: cache data, handle large messages, filter topics with CEL or SQL, and concentrate topic partitions.

Conduktor Gateway advanced pattern Interceptors let you do things standard Kafka can't: cache repeated fetches, send oversized messages, filter topic content server-side, and collapse many virtual topics onto fewer physical ones. Producers and consumers keep using standard Kafka clients — Gateway handles it at the proxy layer.

## Available patterns

| Pattern                                                                                | Description                                                                                                  |
| -------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| [Data caching](/guide/use-cases/cache-kafka-data)                                      | Cache fetch responses at the proxy layer to reduce broker load and repeated consumer reads                   |
| [Large messages](/guide/use-cases/manage-large-messages#large-messages)                | Split oversized messages at produce time and reassemble them transparently at consume time                   |
| [Large batches](/guide/use-cases/manage-large-messages#large-batches)                  | Break produce requests that exceed broker limits into smaller batches automatically                          |
| [CEL topic filtering](/guide/conduktor-concepts/logical-topics#filter-topics-with-cel) | Define logical topics that filter records server-side using Common Expression Language expressions           |
| [SQL topics](/guide/conduktor-concepts/logical-topics#sql-topics)                      | Query Kafka topics using SQL semantics — filter, project and transform records at the proxy                  |
| [Topic concentration](/guide/conduktor-concepts/logical-topics#concentrated-topics)    | Map multiple virtual topics onto a single physical Kafka topic to reduce partition count and broker overhead |

## When to use advanced patterns

* **Reduce broker load** — use caching to serve repeated fetch requests without hitting the broker every time
* **Work around Kafka limits** — large message and batch handling let you produce and consume data that exceeds `message.max.bytes` without reconfiguring brokers
* **Control data exposure** — CEL and SQL topic filters let you expose a subset of a topic's records to specific consumers without duplicating the underlying data
* **Optimize partition usage** — topic concentration consolidates logical namespaces onto fewer physical partitions, reducing overhead in multi-tenant environments

## Related resources

* [Logical topics overview](/guide/conduktor-concepts/logical-topics)
* [Large message and batch use case](/guide/use-cases/manage-large-messages)
* [Cache data use case](/guide/use-cases/cache-kafka-data)
* [Data quality Interceptors](/guide/reference/data-quality)