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llmgw/deploy/examples/server.yaml
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Ilker ManapandClaude Opus 5 a075ff4120 Add approximate prefix routing, and find out it did nothing
Tier 1 of plan §7.5: a radix tree of request prefixes that estimates which
replica has already prefilled one. Bytes, not tokens — needing the engine's
exact tokenizer is what makes tier 2 a separate project.

It went in inert, and the decision metric is what caught it: 144 lookups, zero
hits. The cause was a rule I had written and tested for. A node's label is the
first request that created it, so the second request for the same system
prompt diverges in its last few bytes — a new question after the same
preamble, the single most common shape there is. Requiring the whole label to
match threw away the 700 bytes they shared. What matters is the shared head,
because that is what the engine cached, and a partial label match now counts.
Two unit tests asserted the wrong rule and have been inverted.

With that fixed, measured end to end against engines whose caches are too
small for the working set: 22.5% cache hits without, 81.7% with, and the
breakdown shows the misses are exactly the first round, when the tree is
empty.

The scenario matters as much as the number. With a handful of prompts and a
large cache, scattering is free — every replica ends up holding everything —
and prefix routing can only add constraint. The first version of the test
measured that case and showed a loss, which was a true statement about a
situation the feature is not for.

Two things keep it from being the disaster prefix routing usually is. The
imbalance guard, which needs both an absolute and a relative gap before it
fires, because either alone misfires — absolute on an idle cluster, relative
on a busy one. And it is a scorer rather than a filter: affinity is a vote the
queue and inflight scorers can outvote, not a rule.

The tree records the replica the picker actually chose, not the one the scorer
proposed, and a node prefers the replica it has seen most rather than most
recently — a count is stable under a randomizing picker, where recency just
chases whatever the picker last did.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-16 12:13:19 +02:00

229 lines
9.4 KiB
YAML

# llmgw router configuration (phase 1).
#
# The endpoint list is static here. From phase 3 it comes from the control
# plane instead and this section disappears; everything else stays.
#
# Any field can be overridden from the environment with an LLMGW_ prefix and
# __ for nesting: LLMGW_ROUTER__RETRIES=3
listen: ":8080" # client-facing OpenAI API
admin_listen: ":9090" # metrics, health, pprof — do not expose this publicly
# Where node agents connect. Separate from the client port so the fleet-facing
# surface can be firewalled independently.
agent_listen: ":7443"
# Mutual TLS on the agent port (plan §5.6). With it, a node's identity is taken
# from its certificate's common name and an agent claiming a different node id
# is refused. Without it the port is plaintext HTTP/2 and anyone who can reach
# it can claim to be any node, so it must stay on a trusted network.
#
# These certificates come from llmgw's own authority, not a public one: public
# authorities stopped issuing the clientAuth usage, so no Let's Encrypt
# certificate can authenticate an agent.
#
# llmgw ctl cert init-ca --dir /etc/llmgw/pki
# llmgw ctl cert issue-server llmgw-ctl --host 10.0.0.140 --dir /etc/llmgw/pki
#
# Every address an agent might dial has to appear in --host, bare IP addresses
# included: hostname verification reads subject alternative names and ignores
# the common name entirely.
#
# This covers the fleet-facing port only. The client-facing API above is public
# and belongs behind a publicly trusted certificate.
#
# agent_tls:
# ca: /etc/llmgw/ca.pem
# cert: /etc/llmgw/server.pem
# key: /etc/llmgw/server-key.pem
# The public page at "/". Someone who reaches this address without a key needs a
# route to getting one, and the gateway cannot guess who to send them to.
#
# landing:
# contact: "platform@example.com" # or an https:// URL, or "#platform on Slack"
# notice: "Internal use only."
# API keys on the client-facing port (plan §7.9). Off by default, because a
# gateway on a trusted network with no keys issued still has to serve — but
# nothing else protects that port, so turning it on is what makes it safe to
# expose.
#
# llmgw keys init --store /var/lib/llmgw/llmgw.db
# llmgw keys create --store /var/lib/llmgw/llmgw.db --project default "laptop"
#
# The key is printed once. Only its hash is stored, so there is nothing to
# recover it from.
#
# auth:
# enabled: true
# store: /var/lib/llmgw/llmgw.db
# # How long a resolved key is trusted before being read again. This is the
# # price of keeping the database off the request path: it bounds how long a
# # revoked key keeps working.
# cache_ttl: 30s
# # How long a rejected key is remembered as rejected, so a client looping
# # with a bad key cannot become a database read per request.
# negative_ttl: 5s
#
# # Serve the signup form. What it creates is a pending account that can do
# # nothing until `llmgw users approve` places it in a project, so this is not
# # a way in — it only moves key creation from you to the person who needs one.
# # Off, there is no form and you issue keys with `llmgw keys create --claim`.
# signup_open: true
#
# # What each model costs, in micro-units per thousand tokens. A unit is
# # whatever you decide: self-hosted models have no per-token price, so it can
# # be GPU-seconds, a notional rate, or 1000 everywhere — which turns budgets
# # into plain token quotas.
# #
# # A model priced at zero is exempt from budget checks, which is what lets a
# # key with nothing left still be served a cheap fallback.
# default_price: { prompt_per_1k: 0, completion_per_1k: 0 }
# pricing:
# llama-3.3-70b: { prompt_per_1k: 1000, completion_per_1k: 3000 }
# qwen2.5-32b: { prompt_per_1k: 400, completion_per_1k: 1200 }
#
# # Usage rows are written in batches off the request path. Beyond buffer_size
# # they are dropped rather than blocking a request: losing some accounting is
# # bad, turning a stalled database into an outage is worse.
# flush_interval: 200ms
# batch_size: 500
# buffer_size: 8192
router:
scrape_interval: 2s
scrape_timeout: 1s
# How long an endpoint may go unscraped before it is scored down. It is never
# dropped for staleness alone: if the whole pool went stale there would be
# nowhere left to send anything.
stale_after: 10s
# Additional endpoints to try after a failure, and only while nothing has
# reached the client yet.
retries: 2
# How long a failing endpoint leaves the candidate pool. A long fallback list
# with no cooldown turns one endpoint's rate limit into a cluster-wide retry
# storm.
cooldown: 15s
# Consecutive failures that open the breaker. Set to 1 for pure cooldown
# behaviour.
failure_threshold: 3
default_profile: chat # chat | batch | long-context | debug
# Approximate prefix routing (plan §7.5 tier 1): send a request to the replica
# that has probably already prefilled its prefix.
#
# It earns its keep when the working set does not fit in one replica's cache.
# With a handful of prompts and a large cache, scattering is free — every
# replica ends up holding everything — and this only adds constraint. Measured
# with sim-engines whose caches were too small for the working set: cache hits
# went from 22.5% to 81.7%.
#
# Watch llmgw_prefix_decisions_total to tune it. A high
# load_balance_override count means the guard is doing its job and affinity is
# not getting a chance; a high cache_miss_min_load means match_ratio or
# min_match is too strict for your traffic.
prefix:
enabled: false
# The shortest match worth acting on, in bytes. Below this the overlap is
# coincidence — two English prompts share "The".
min_match: 64
# The share of the prompt that must match. A short shared header on a very
# long prompt saves almost no prefill.
match_ratio: 0.3
# The imbalance guard, and both must trip before affinity is abandoned.
# Absolute alone fires on an idle cluster where one replica has two requests
# and another none; relative alone fires on a busy one where 200 against 180
# is a rounding error. Without the guard the cache hit rate rises while p99
# collapses.
balance_abs: 8
balance_rel: 1.5
# An engine evicts on its own schedule, so an old record may describe a
# cache that is gone.
ttl: 10m
max_nodes: 100000
session_header: x-session-id # affinity key; falls back to the `user` field
# Ask engines for usage even when the client did not, so token accounting
# works regardless of client behaviour. The extra chunk is dropped on the way
# back to a client that did not ask for it.
inject_usage: true
max_body_bytes: 33554432
timeouts:
dial: 5s
response_header: 60s
first_token: 120s
idle: 60s # between streamed tokens; catches a wedged engine
total: 30m
# Flow control: decides *when* a request may proceed, before scheduling
# decides where it goes. Without it a batch workload starves interactive
# traffic, because an engine queue is FIFO and knows nothing about tenants.
admission:
enabled: true
# With auth on, the key decides the band and this header is ignored. With
# auth off the header is trusted, so any client can promote itself into the
# top band — do not expose the port in that configuration.
band_header: x-llmgw-band
default_band: gold
# A band waits once pool saturation passes its ceiling, so the cluster
# degrades from the bottom up. A ceiling of 1.0 means "flow up to the
# healthy limit"; use a value above 1 for a band that must never wait.
bands:
- { name: platinum, priority: 400, saturation_ceiling: 1.00 }
- { name: gold, priority: 300, saturation_ceiling: 0.85 }
- { name: silver, priority: 200, saturation_ceiling: 0.60 }
- { name: bronze, priority: 100, saturation_ceiling: 0.30 }
# Drop a request that has waited this long: the client has usually given up,
# and sending the GPU work nobody is waiting for helps no one.
queue_ttl: 30s
# Reject immediately once a band's queue is this deep, rather than letting
# it accumulate silently.
queue_capacity_per_band: 2000
interval: 10ms
# What the scorers normalize against. Measure these with `ctl bench` rather
# than guessing: target_waiting in particular governs how the whole system
# behaves under load. Too low starves the GPU, too high brings back queueing
# delay.
scoring:
target_waiting: 4
target_inflight: 8
kv_ceiling: 0.9
session_load_factor: 1.25
# How aggressively the control plane reconciles.
control:
interval: 5s
base_backoff: 10s
max_backoff: 10m
# Node expiry is staged deliberately: a network blip must not tear down
# replicas that are still serving, and rebuilding a multi-node replica costs
# tens of minutes of model loading.
unreachable_after: 15s
lost_after: 60s
port_range: [20000, 20999]
mgmt_interface: eth0
models:
- name: llama-3.3-70b
aliases: [llama]
fallbacks: [qwen2.5-32b]
routing_profile: chat
- name: qwen2.5-32b
aliases: [qwen]
routing_profile: batch
# A static replica list, used only when no model declares a profile. That is the
# router-only mode for testing against sim-engines; with the control plane
# running, agents provide the replicas instead.
#
# endpoints:
# - id: sim-1
# url: http://127.0.0.1:8001
# models: [llama-3.3-70b]
# pool: local
# weight: 1