docs: add SGLang HiCache L3 observability note

docs/source/performance/sglang-hicache-l3-aistudio-observability.md

@@ -0,0 +1,71 @@
+# SGLang HiCache + Mooncake L3 Observability on AI Studio A800
+
+This note records a small, reproducible SGLang HiCache + Mooncake Store L3
+experiment on a single AI Studio A800 runtime. It is intended as an
+observability and reproduction note, not as a performance-win benchmark.
+
+## Scope
+
+- Platform: Baidu AI Studio A800 runtime.
+- Model: Qwen3-0.6B.
+- Runtime layout: single-node TCP-oriented setup.
+- Workload: repeated-prefix requests with short output to emphasize TTFT.
+- Goal: verify whether SGLang's Mooncake backend emits L3 write/read metrics and
+  whether Store reload beats a no-store baseline in this constrained setup.
+
+## Result Summary
+
+| case | no-store p50 TTFT | store reload p50 TTFT | exists hit pages | get success pages | conclusion |
+|---|---:|---:|---:|---:|---|
+| p4096_c1_n32 | 44.815 ms | 45.955 ms | 3095 | 3095 | L3 read-back observed; reload was 2.544% slower |
+| p8192_c1_n16 | 69.110 ms | 73.600 ms | 0 | 0 | no read-back hit; reload was 6.497% slower |
+
+A previous gapfill run also showed successful Store write-back metrics:
+
+```text
+set_requested_pages = 13268
+set_success_pages = 13268
+```
+
+## Interpretation
+
+The `p4096_c1_n32` case demonstrates that backend-level L3 read-back can be
+observed through `exists` and `get` counters. It does not demonstrate a latency
+improvement. In this small-model, single-node setup, Store reload added enough
+overhead that no-store remained faster.
+
+This result is useful as a lower-bound diagnostic case:
+
+- L3 write-back is observable.
+- One L3 read-back case is observable.
+- Positive TTFT or throughput gains require a stronger workload or topology,
+  such as larger models, longer shared prefixes, higher concurrency, multi-turn
+  histories, RAG-style repeated documents, or an independent storage process
+  that remains alive across SGLang restarts.
+
+## Follow-Up Work
+
+1. Rebuild or install a same-runtime `mooncake_client` for AI Studio Ubuntu
+   20.04 to validate an independent persistent Store topology.
+2. Extend the matrix to larger models, longer prefixes, multi-turn workloads,
+   RAG workloads, and higher concurrency.
+3. Add first-class counters for L3 exists/get/set pages and success ratios in
+   SGLang/Mooncake integration logs so negative and positive results can be
+   interpreted without screenshots or ad hoc parsing.
+4. Validate prefix-aware eviction/orphan suffix cleanup under real Store
+   pressure before presenting it as an optimization.
+
+## Claim Boundary
+
+Safe claim:
+
+```text
+SGLang HiCache + Mooncake Store can produce observable L3 write-back and one
+controlled read-back case on AI Studio A800.
+```
+
+Unsafe claim:
+
+```text
+Mooncake Store improves TTFT or throughput in this setup.
+```

docs/source/performance/sglang/index.md

@@ -6,11 +6,13 @@ Benchmarks evaluating Mooncake's integration with SGLang across PD disaggregatio
 |----------|----------|---------------|
 | [PD Disaggregation Performance](../sglang-benchmark-results-v1) | SGLang PD disaggregation with Mooncake Transfer Engine | 1P1D PD disaggregation achieves approximately **30% lower ITL** while maintaining comparable throughput against two regular instances. |
 | [HiCache with Mooncake Backend Benchmark](../sglang-hicache-benchmark-results-v1) | SGLang HiCache using Mooncake Store as L3 storage | Mooncake-backed HiCache improves prefill performance in multi-turn workloads by maintaining higher KV cache hit rates as conversation rounds grow. |
+| [AI Studio A800 L3 Observability](../sglang-hicache-l3-aistudio-observability) | SGLang HiCache with Mooncake Store on a single AI Studio A800 runtime | L3 write-back and one read-back case were observed, but Store reload did not beat no-store in this constrained setup. |
 
 :::{toctree}
 :maxdepth: 1
 :hidden:
 
 ../sglang-benchmark-results-v1
 ../sglang-hicache-benchmark-results-v1
+../sglang-hicache-l3-aistudio-observability
 :::