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chore: introduce write queue for inference_store

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# What does this PR do?
Adds a write worker queue for writes to inference store. This avoids overwhelming request processing with slow inference writes.

## Test Plan

Benchmark:
```
cd /docs/source/distributions/k8s-benchmark
# start mock server
python openai-mock-server.py --port 8000
# start stack server
uv run --with llama-stack python -m llama_stack.core.server.server docs/source/distributions/k8s-benchmark/stack_run_config.yaml
# run benchmark script
uv run python3 benchmark.py --duration 120 --concurrent 50 --base-url=http://localhost:8321/v1/openai/v1 --model=vllm-inference/meta-llama/Llama-3.2-3B-Instruct
```


Before:

============================================================
BENCHMARK RESULTS

Response Time Statistics:
  Mean: 1.111s
  Median: 0.982s
  Min: 0.466s
  Max: 15.190s
  Std Dev: 1.091s

Percentiles:
  P50: 0.982s
  P90: 1.281s
  P95: 1.439s
  P99: 5.476s

Time to First Token (TTFT) Statistics:
  Mean: 0.474s
  Median: 0.347s
  Min: 0.175s
  Max: 15.129s
  Std Dev: 0.819s

TTFT Percentiles:
  P50: 0.347s
  P90: 0.661s
  P95: 0.762s
  P99: 2.788s

Streaming Statistics:
  Mean chunks per response: 67.2
  Total chunks received: 122154
============================================================
Total time: 120.00s
Concurrent users: 50
Total requests: 1919
Successful requests: 1819
Failed requests: 100
Success rate: 94.8%
Requests per second: 15.16

Errors (showing first 5):
  Request error:
  Request error:
  Request error:
  Request error:
  Request error:
Benchmark completed.
Stopping server (PID: 679)...
Server stopped.


After:

============================================================
BENCHMARK RESULTS

Response Time Statistics:
  Mean: 1.085s
  Median: 1.089s
  Min: 0.451s
  Max: 2.002s
  Std Dev: 0.212s

Percentiles:
  P50: 1.089s
  P90: 1.343s
  P95: 1.409s
  P99: 1.617s

Time to First Token (TTFT) Statistics:
  Mean: 0.407s
  Median: 0.361s
  Min: 0.182s
  Max: 1.178s
  Std Dev: 0.175s

TTFT Percentiles:
  P50: 0.361s
  P90: 0.644s
  P95: 0.744s
  P99: 0.932s

Streaming Statistics:
  Mean chunks per response: 66.8
  Total chunks received: 367240
============================================================
Total time: 120.00s
Concurrent users: 50
Total requests: 5495
Successful requests: 5495
Failed requests: 0
Success rate: 100.0%
Requests per second: 45.79
Benchmark completed.
Stopping server (PID: 97169)...
Server stopped.
This commit is contained in:
Eric Huang 2025-09-10 11:43:26 -07:00
parent 935b8e28de
commit e721ca9730
7 changed files with 139 additions and 22 deletions
Download patch file Download diff file Expand all files Collapse all files

12
tests/unit/utils/inference/test_inference_store.py
View file

@ -65,6 +65,9 @@ async def test_inference_store_pagination_basic():
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Test 1: First page with limit=2, descending order (default)
result = await store.list_chat_completions(limit=2, order=Order.desc)
assert len(result.data) == 2
@ -108,6 +111,9 @@ async def test_inference_store_pagination_ascending():
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Test ascending order pagination
result = await store.list_chat_completions(limit=1, order=Order.asc)
assert len(result.data) == 1
@ -143,6 +149,9 @@ async def test_inference_store_pagination_with_model_filter():
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Test pagination with model filter
result = await store.list_chat_completions(limit=1, model="model-a", order=Order.desc)
assert len(result.data) == 1
@ -190,6 +199,9 @@ async def test_inference_store_pagination_no_limit():
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Test without limit
result = await store.list_chat_completions(order=Order.desc)
assert len(result.data) == 2