| title | KV Events for Custom Engines |
|---|
This document explains how to implement KV event publishing for custom inference engines, enabling them to participate in Dynamo's KV cache-aware routing.
The KV Router relies on real-time events from backend workers to track which KV cache blocks are stored on each worker. When your custom engine allocates or evicts KV cache blocks, it should publish these events so the router can make optimal routing decisions.
Events are published over the Dynamo event plane, a transport-agnostic pub/sub layer that supports both NATS and ZMQ backends (see Event Plane for details). The KvEventPublisher binding handles all transport concerns — your engine code does not interact with the event plane directly.
KvEventPublisher supports two publishing modes:
- Direct publishing — Your engine calls
publish_stored()/publish_removed()to push events directly over the event plane. Simplest approach for custom engines. - ZMQ relay — For engines that emit raw KV events over a ZMQ socket (like SGLang and vLLM). The publisher subscribes to the ZMQ endpoint and relays events to the event plane automatically.
The KV cache supports three event types:
| Event Type | Description | When to Publish |
|---|---|---|
BlockStored |
New blocks added to cache | After KV cache allocation succeeds |
BlockRemoved |
Blocks evicted from cache | When blocks are evicted or freed |
AllBlocksCleared |
All blocks removed | On cache reset or worker restart |
Each event contains:
event_id: Monotonically increasing identifier per worker (managed internally by the publisher)dp_rank: Data parallel rank (0 if DP not enabled)data: One ofStored,Removed, orCleared
For BlockStored events:
token_ids: List of token IDs for the stored blocksblock_hashes: List of sequence block hashes from the engine's block manager. These are cumulative hashes that incorporate all tokens from the start of the sequence up to and including the current block (not just the tokens within that block). This enables prefix matching across requests.num_block_tokens: Number of tokens per block (should all equalkv_block_size)parent_hash: Hash of the parent block. Required for all blocks except the first block in a sequence (which has no parent).lora_name: LoRA adapter name string (omit orNonefor base model). When set, the adapter name is incorporated into block hash computation so that blocks for different LoRA adapters (or the base model) are never conflated.
For BlockRemoved events:
block_hashes: List of sequence block hashes being evicted
Call publish_stored() and publish_removed() directly from your engine code. The publisher handles event IDs, serialization, and transport.
flowchart LR
subgraph Engine["Custom Engine"]
cache["KV Cache Manager"]
end
subgraph Worker["Dynamo Worker Process"]
pub["KvEventPublisher"]
end
subgraph EP["Dynamo Event Plane"]
topic["kv-events topic"]
end
subgraph Router["KV Router"]
indexer["KvIndexer"]
end
cache -->|"publish_stored()<br/>publish_removed()"| pub
pub -->|"event plane"| topic
topic --> indexer
When to use:
- Building a custom inference engine from scratch
- Your engine doesn't have a ZMQ-based event system
- You want the simplest integration path
from dynamo.llm import KvEventPublisher
class CustomEnginePublisher:
def __init__(self, component, block_size: int, dp_rank: int = 0):
self.block_size = block_size
self.kv_publisher = KvEventPublisher(
component=component,
kv_block_size=block_size,
dp_rank=dp_rank,
)
def on_blocks_stored(self, token_ids: list[int], block_hashes: list[int],
parent_hash: int | None = None,
lora_name: str | None = None):
"""Call after KV cache blocks are allocated."""
num_block_tokens = [self.block_size] * len(block_hashes)
self.kv_publisher.publish_stored(
token_ids=token_ids,
num_block_tokens=num_block_tokens,
block_hashes=block_hashes,
parent_hash=parent_hash,
lora_name=lora_name,
)
def on_blocks_removed(self, block_hashes: list[int]):
"""Call when KV cache blocks are evicted."""
self.kv_publisher.publish_removed(block_hashes=block_hashes)from dynamo.llm import register_model
async def main():
component, endpoint = await register_model(
model="my-model",
generator=my_generate_fn,
)
publisher = CustomEnginePublisher(
component=component,
block_size=16, # Match your engine's block size
)
def on_prefill_complete(request_id, token_ids, blocks):
block_hashes = [block.hash for block in blocks]
publisher.on_blocks_stored(token_ids=token_ids, block_hashes=block_hashes)
def on_cache_eviction(evicted_blocks):
block_hashes = [block.hash for block in evicted_blocks]
publisher.on_blocks_removed(block_hashes=block_hashes)For engines that already publish raw KV events over a ZMQ socket (like SGLang and vLLM), use the same KvEventPublisher with a zmq_endpoint. The publisher subscribes to the ZMQ socket and relays events to the event plane automatically.
flowchart LR
subgraph Engine["Custom Engine / SGLang / vLLM"]
cache["KV Cache Manager"]
zmq_pub["ZMQ Publisher"]
end
subgraph ZMQ["ZMQ Socket"]
socket["tcp://127.0.0.1:5557"]
end
subgraph Worker["Dynamo Worker Process"]
relay["KvEventPublisher<br/>(relay mode)"]
end
subgraph EP["Dynamo Event Plane"]
topic["kv-events topic"]
end
subgraph Router["KV Router"]
indexer["KvIndexer"]
end
cache --> zmq_pub
zmq_pub -->|"PUB"| socket
socket -->|"SUB"| relay
relay -->|"event plane"| topic
topic --> indexer
When to use:
- Your engine already publishes KV events via ZMQ (like SGLang or vLLM)
- You want to decouple event publishing from your engine's main loop
Pass zmq_endpoint (and optional zmq_topic) to the same KvEventPublisher:
from dynamo.llm import KvEventPublisher
kv_publisher = KvEventPublisher(
component=component,
kv_block_size=block_size,
zmq_endpoint="tcp://127.0.0.1:5557", # Where your engine publishes
zmq_topic="", # Subscribe to all topics
)No further calls to publish_stored() / publish_removed() are needed — the publisher reads events from the ZMQ socket and forwards them automatically.
The ZMQ message format (compatible with SGLang / vLLM):
| Frame | Description |
|---|---|
| 1 | Topic (empty string for all topics) |
| 2 | Sequence number (8 bytes, big-endian) |
| 3 | Msgpack payload: [timestamp, [events], dp_rank] |
Each event in the payload is a dictionary with a type field (BlockStored, BlockRemoved, or AllBlocksCleared).
For BlockStored:
{
"type": "BlockStored",
"block_hashes": [signed_i64, ...], # Sequence block hashes
"parent_block_hash": signed_i64 | None, # Parent hash
"token_ids": [int, ...], # Token IDs
"block_size": int, # Tokens per block
"lora_name": str | None, # LoRA adapter name
}For BlockRemoved:
{
"type": "BlockRemoved",
"block_hashes": [signed_i64, ...],
}For AllBlocksCleared:
{"type": "AllBlocksCleared"}KvEventPublisher(
component: Component,
kv_block_size: int,
dp_rank: int = 0,
enable_local_indexer: bool = False,
zmq_endpoint: str | None = None, # Set for relay mode
zmq_topic: str | None = None, # Defaults to "" when zmq_endpoint is set
)| Parameter | Description |
|---|---|
component |
The Dynamo component this publisher belongs to |
kv_block_size |
Number of tokens per block (must be > 0, must match your engine) |
dp_rank |
Data parallel rank (defaults to 0) |
enable_local_indexer |
Enable a worker-local KV indexer for direct overlap queries |
zmq_endpoint |
ZMQ endpoint to subscribe to for relay mode (e.g. "tcp://127.0.0.1:5557") |
zmq_topic |
ZMQ topic filter (defaults to "" = all topics) |
publish_stored(
token_ids: list[int],
num_block_tokens: list[int],
block_hashes: list[int],
parent_hash: int | None = None,
block_mm_infos: list[dict | None] | None = None,
lora_name: str | None = None,
)Publish a block-stored event. Event IDs are managed internally. When lora_name is provided, the adapter name is mixed into block hash computation so blocks cached under different adapters produce distinct hashes.
publish_removed(block_hashes: list[int])Publish a block-removed event. Event IDs are managed internally.
shutdown()Stop background tasks (ZMQ listener, event forwarding).
-
kv_block_sizemust match your engine's actual block size. -
parent_hashis required for all blocks except the first in a sequence — it links blocks to enable prefix matching. -
Block hashes are signed 64-bit integers in the Python API. The publisher handles conversion internally.
-
Event ordering is automatic — the publisher assigns monotonically increasing event IDs. You do not need to track event IDs yourself.
- Event Plane: Transport options (NATS, ZMQ) and configuration
- Configuration and Tuning: Router flags, tuning, and production setup
- Router Design: Architecture details and event transport modes