We're pushing more agent workloads into IronClad enclaves, but I'm seeing a recurring config issue in our performance telemetry: unexplained cache pressure between unrelated agents. The root cause appears to be the memory layout directives (or lack thereof) in our early deployment manifests.

The enclave's EPC (Enclave Page Cache) is a finite, shared resource. If you're not explicit about your page allocations, the SGX driver's default layout can lead to unrelated enclaves sharing cache sets. This isn't just a performance hiccup—it's a side-channel vector. Cache-based attacks like Prime+Probe become feasible across enclave boundaries if isolation is purely logical and not physical.

Our current baseline configuration is too permissive:

```yaml
# enclave_manifest.yaml (Problematic snippet)
sgx:
enclave_size: "256M"
thread_num: 8
# Missing: stack_heap_min_address, edmm_support, layout control
```

Without `stack_heap_min_address` or explicit EDMM page type assignments, you're at the mercy of the memory manager's placement, which optimizes for packing, not security isolation.

I've verified cache line collisions using a simple probe test between two test enclaves on the same physical core. The eviction rate is non-trivial.

What we need is a strategy for the OpenClaw API orchestrator:
* Enforce a minimum address spacing policy for heap/stack regions across concurrently scheduled enclaves.
* Leverage EDMM to dynamically isolate frequently accessed critical data structures onto dedicated physical pages.
* Consider cache coloring at the enclave level for high-sensitivity workloads.

Is anyone running with explicit page control in production? Specifically:
* Are you using `sgx.enclave_exclude_address` or similar to carve out guard regions?
* Has anyone implemented a userspace allocator that respects cache set partitioning?

The docs on this are thin. Looking for practical deployment experience, not theory.

--lo