Monitor draws CPU, memory, GPUs, requests, tokens, latency, network and disk
as Braille charts over 5m/1h/24h/7d, then per node, card and model
sparklines; node and model pages have their own. History is read from
monitoring.prometheus through POST /api/v1/metrics/range, or without it
from what the console saw. The control plane serves the cluster's machines
for Prometheus http_sd at /prometheus/targets on its metrics port, and node
add installs prometheus-node-exporter.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The console starts a serve or update job over the admin API and stays,
instead of closing to follow the download. Jobs lists them with their
progress and steps; the sidebar counts those running. ctl model serve and
update take --detach; ctl jobs lists jobs and follows one.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The control plane reads the model's shape from one GGUF header or its
config.json and lists, for every file, the best way it runs here: one card,
several of a node's (by layer for llama.cpp, tensor-parallel for vLLM),
several nodes' over one fabric (vLLM, pipeline-parallel between them), or a
CPU node; what each card holds and whether it is free now. ctl model plan
prints it; model serve takes its file and way unless told, gives a GGUF on
GPUs a GPU profile, and with --fallbacks adds the next best ways. The
console shows it per file and asks for the way and the fallback.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The mirror keeps where it fetched a file beside it, and reports that and the
checksum after it restarts. A model whose files the mirror cannot trace is
found on the registry: a repository holding a file of that name that has the
commit the mirror's directory is named after, with every file at the same
size, the most downloaded first. ctl model origin and the console set one by
hand, checked the same way. Commits compare shortened.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model served from the registry records its origin: repository, commit and
each file's checksum; one served before is worked out from the mirror's
record of where it fetched the file. Every mirror.update_check (6h) the
control plane asks whether those files changed there. ctl model updates
lists it, ctl model update fetches beside the old files, checks, swaps and
replaces replicas one at a time, ctl model rollback goes back. The console
shows it on Models and offers the same.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
init --patroni user@host ... installs PostgreSQL, Patroni and etcd on the
given machines over ssh, with this one as the third etcd vote, makes the role
and database, and moves the store in use into the cluster. Each step checks
first, so it changes nothing on a cluster that is up. For a store of several
hosts the control plane publishes each member's role, state and lag from
Patroni, a stopped member as missing, prints it in ctl status, and alerts on
it. Making an administrator on PostgreSQL sent a bool to an integer column;
it sends an integer now.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A node that cannot run the CUDA 13 build installs the same version's
CUDA 12.9 build from vLLM's GitHub release, with PyTorch's cu129 torch;
the install computes on the GPU before it counts. The build can be
chosen per node — auto, cu13, cu129, none — on the cluster page, with
ctl engine-build, or over the admin API; the control plane keeps the
choice and tells the node at once.
Refs #2.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A restart with no room beside it waited the drain grace period before
stopping the old replica, and stopped it even when the replacement
would fit nowhere. It now stops at once when the replica alone blocks
its replacement, gives the restart up (saying why) when nothing would
fit, and ctl restart --in-place stops first on request.
Refs #2 (item 3).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
engine_overrides give nodes picked by GPU class, id or labels their own
engine versions; node add --disable-engine keeps one off a node; what
vLLM cannot do on a node is a warning rather than a refused node; the
CUDA requirement follows the version; a hand-named binary is no longer
replaced by an installed one.
Refs #2 (items 4 and 7).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
llmgw ctl model adapters lists a model's adapters and adds or removes
them through POST /api/v1/models/{name}/adapters, which reads each new
file first and refuses one that is not an adapter for the model's
architecture, as the mirror page's card does.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model's adapters are fetched by each node with its weights and loaded
unapplied at start; a request naming an adapter reaches the model's
replicas with llama.cpp's per-request lora field. Adapter names share the
model namespace, are listed, and follow allowlists on their own. The
router's config seed and pushed catalog now build the name map in one place.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A catalog model with external {url, model, api_key_file} and no profiles
is published as an endpoint by the control plane, the key read from its
file each time; the router rewrites the request's model to the provider's
name and sends its key. It is never scraped nor stale, and nothing is
placed for it. Named in fallbacks, it serves when the cluster has no room.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The quotas page gains a capacity section over the same API methods the CLI
uses; a model's card sets its class, owner, memory and cores, applying only
what changed. Headroom counts the replicas a model could get by preempting
what its class outranks, and the card and ctl model target use it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Every agent samples, at most every ten seconds: nvidia-smi's temperature,
HBM temperature, power draw, enforced limit and throttle reasons per GPU;
hwmon's CPU package and board inlet temperatures; and CPU package power
from RAPL's energy counters. Sent with heartbeats, published as metrics
and shown on the node page; unmeasured sensors are absent, never zero.
Observe-only, step 0 of docs/facility-aware-placement.md, which now
describes the agent source and what these readings can and cannot say.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Stored ctl bench results reach the reconciler: requests per replica past
the measured SLO concurrency scale a model up, a replica is taken back only
if the rest stay under 70% of theirs, and among profiles of equal priority
the most measured tokens per GPU or core is tried first. ctl model target
sizes a model for a throughput against the room there is.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model has an owner (org, team or project). Quotas guarantee a scope
GPUs, cores and memory and may limit it; what a scope holds is summed from
its models' replicas and those beneath it. A replica within its owner's
guarantee is not taken for another scope; what is held beyond a guarantee
is borrowed and taken back for a scope within its own. A limit stops a
model before it starts, and headroom stops there too. ctl quota and ctl
model owner set them; metrics and a CapacityAtLimit alert report them.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model's class (critical, standard, opportunistic; unset follows its
scaling) decides what may be stopped to make room for it: a lower class
for a higher, and within a class only what another grew into under load,
for a model below its minimum. Victims are tried on a copy of the
inventory and stopped only if they make the room. Preempted replicas are
drained with a short grace and their model is held back until the room is
used. ctl model resources and class move under ctl model.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A profile's cpu_cores is reserved out of its node's CPUs by placement, as
memory is, and becomes the engine's thread count. Agents report their CPU
count in registration and heartbeats. New CPU models must declare memory;
model views show reserved against measured memory with warnings, and
ctl model resources sets both for a stored model.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The Held tab's model name opens a card: each replica with its node, state,
age, CPU and memory, the room for more found by dry-running the scheduler
on a copy of the inventory, and a form for the always-running and
under-load replica counts. An always-running count placement cannot meet
is refused with the reason. Headroom is also on the admin API.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
CPU replicas start on half the machine's CPUs, not all of them: two busy
llama.cpp servers each spinning on all 8 vCPUs fell to 0.8 tok/s apiece,
where at 4 threads they keep 5.5. llamacpp.threads sets it per node.
Inference requests can be traced over OTLP/HTTP (tracing.endpoint), with
admission, schedule and upstream spans and traceparent sent to the engine.
Security: onboarding no longer puts the cluster root in the system trust
store and removes it where it was; the mirror's mutual-TLS API can be
limited to named certificates (--api-client); init.log no longer keeps the
administrator's password; a warning when auth is off on a public listen;
the recorded actor is sanitised and sudo-aware; Ray's dashboard is off, and
the remaining engine gaps are documented.
reconciler.go and agent.go are split by topic, the status mapping of each
failure is tested, and the plan's checklist is brought up to date.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Adding a model took four steps and a YAML file — plan it, fetch it into the
mirror, write its catalog entry with a memory figure somebody estimated,
scale it — and whether it would load was found out at the end.
`llmgw ctl model serve OWNER/REPO` does it as one job in the control plane,
where the registry, the mirror, the catalog and the fleet already are:
- the registry: the GGUF file set matching --quant (Q4_K_M by default) or
--file, leaving out vision projectors and importance matrices, and naming
what the repository does have when nothing matches; gated repositories are
refused;
- the mirror: fetched at the repository's revision, with progress, and each
file's sha256 compared with what the registry published — the mirror is
the one place a corrupted download is caught once rather than loaded on
every node;
- the check: whether the nodes' llama.cpp loads the architecture, and the
memory it needs from its own header;
- the catalog, then a wait for a replica that stops early, with the reason,
when the model is parked or fits on no node;
- a smoke test: one short request to the replica, with its engine key, and
the answer and tokens per second.
ctl starts the job and prints each step as it changes; a download of hours
does not depend on the terminal. --on-demand adds the model without starting
a replica. Jobs are kept in memory until the control plane restarts.
The catalog name a repository suggests moved into the registry package, so
the mirror page and this agree on it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Every upgrade so far has been a script of mine copying a binary to each
machine over ssh, restarting it and polling until it came back — which is
the job, but not something the product could do, and which needed ssh into
every node.
`sudo llmgw ctl upgrade VERSION` on the control plane does it. This machine
first: the release for its platform, checked against the release's
checksums, the old binary kept beside it, llmgw-server restarted, and a wait
until every node that was ready has reconnected. Then each node in turn: the
control plane tells its agent the version over the stream it already holds;
the agent fetches and checks the release itself, swaps it in with a rename,
answers, and exits with status 75 so systemd starts the new binary. Engines
keep running, as for any agent restart, and are adopted again.
A node is done when it is back on the new version, ready, with as many ready
replicas as before; one that is not within the timeout stops the run before
the next node, so a bad release reaches one machine. Nodes already on the
version are skipped, so running it again resumes.
The fetch-and-verify is one package now, shared with onboarding's idea of
what a release version looks like.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
"Why was this request slow?" had no answer. Nothing tied a request to the
replica that served it, the time admission held it went out in a response
header and was never kept, and the only per-request log lines were for
disconnects, early stream ends and upstream retries.
Every request now has an id: the client's X-Request-Id when it is a plain
string of reasonable length, otherwise one the gateway makes. It is set on
the response before anything else, so a request refused as malformed can be
named too, and forwarded to the engine. One access log line per request
carries it with the model asked for and served, the replica, status, time in
the queue, time to the first token, total time, tokens, and the key,
project and user.
Usage records gain the id, the replica, queue time and time to first token,
tried against a restored copy of the live store before being shipped: 591
rows kept, columns and index in place. `llmgw ctl request ID` reads one back
through the admin API.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
On the live cluster kev-0.5b — an architecture the nodes' llama.cpp did not
know — was started 155 times in eight hours, failing the same way each time,
and phi-4, which fitted on no node, logged "no placement" 250 times in two
days. Neither showed up anywhere an operator looked: the backoff never gave
up, no metric said a model was failing or unplaceable, and the one alert for
a model with nothing serving could not fire, because its series was published
only while a replica was ready.
After five failures in a row a model is parked: not placed again until its
definition changes — a new source or profile — or `llmgw ctl retry` is run.
Status, the model list and the admin API show it with its last error. The
placement warning is logged when its reason changes or every ten minutes.
A request for a parked or unplaceable model is answered at once with why,
rather than "loading; retry shortly", which a client retries forever. Each
request still clears the previous placement result and triggers a fresh
attempt, so a model that fits once room is made is not refused on a stale
answer; the router waits for that attempt, not for its full activation
window.
Metrics now cover model health (desired, ready at 0 for what should run,
consecutive start failures, parked, unplaceable), engine installs per node,
leadership, and certificate expiry read from disk at each scrape, with alerts
for each. `ctl status` counts a model against what it should have now, so an
on-demand model that was asked for and fitted nowhere no longer reads as
satisfied.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
There was no way to restart a running replica. A running engine picks up an
engine key, an edited profile or a new engine version only when it starts,
so after v0.10.3 the nine replicas already running stayed without a key —
reachable from any node — with nothing to do about it short of draining
nodes, which on a small CPU fleet has nowhere to move a model to.
`llmgw ctl restart REPLICA... | --model M | --all` queues replicas to be
replaced. A replica being replaced keeps serving but stops counting toward
its model, so the reconciler places a replacement beside it; once that is
ready the old one is drained and stopped as a node drain would. Replicas of
one model go one at a time, so a model never needs the memory of every
replica twice. Where no second copy fits anywhere, the old replica is
stopped after the drain grace period and the new one starts in its place,
and the log says so, since that is the one case with an outage.
`ctl replicas` shows "(restart queued)" and "(restart replacing)" while it
happens.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Engines listen on every address their node has, with no key. Checked on the
live cluster: from a neighbouring node, a request straight to an engine's
port was answered — past the gateway's authentication, quotas and
accounting, by anyone who could reach the node.
Each replica's engine is now started with a key and refuses requests without
it. The key is derived from the replica id with an HMAC over a secret kept
in the store, rather than stored per replica: the router has to send the
right key to replicas this process never started — adopted after a restart,
or placed by the other control plane — and a function of a shared secret
gives that without a table to keep in step. A key taken from one node opens
that replica only. The secret is made on first use and copied with the rest
of the store when moving to PostgreSQL; a new one would lock the router out
of every running engine at the moment of the move.
The key reaches llama.cpp and vLLM through their environment
(LLAMA_API_KEY, VLLM_API_KEY) rather than their command line, which every
user on the node can read; SGLang only takes it as an argument. The agent's
readiness check, the router's proxy and its metrics scrape send it, the
client's own Authorization still never reaches the engine, and `ctl bench`
fetches the key of the replica it is pointed at from the admin API.
Engines started before this keep running without a key until their replica
is next started. With no store there is nowhere to keep the secret, and
engines start without one, with a warning.
Also formats two files that went in unformatted.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
doctor checks a node alone, and every check can pass while two nodes still
cannot reach each other. ctl fabric-test A B asks B's agent for an
ib_write_bw server and A's for the client, adapter by adapter as NCCL pairs
them, one rail at a time, and grades each against its link's rate. It goes
through the agents' streams, so there is no SSH between nodes; the agent
installs perftest the first time, and names the RoCE v2 GID itself.
The result is read from perftest's table by its heading, not a column
number. Agents now list the requests they answer beyond the usual
(Register.features), and the control plane refuses a test on one too old to
answer instead of waiting minutes for it. The forwarding dispatcher carries
the new capability, and its test says so: a missing forward would have made
the command quietly unavailable in production.
Not yet run over real InfiniBand or RoCE; this cluster has neither.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Adding a node was deploy/bootstrap/onboard-node.sh, which is not installed
anywhere and wanted the node's name, the control plane's address and a
dozen flags. It is now in the binary, run on the control plane:
sudo llmgw node add ubuntu@10.0.0.21
The node id is the machine's hostname, and the address its agent dials is
this machine's on the route to it, checked against the server certificate.
It installs llmgw there (the release for its architecture, fetched and
checked by the node; uname rather than dpkg, so RHEL works), runs doctor
there and stops on a problem before changing anything, issues and installs
the certificate, writes agent.yaml and the unit, starts the agent, and waits
for it to join and install llama.cpp. The authority is read first, so a
missing one is said before the node is touched.
The steps are events. In a terminal they draw a checklist (bubbletea) that
asks what a script cannot: which fabric each group of active adapters is on,
grouped by the subnet manager or RoCE network they report, and whether to go
on past a problem. Elsewhere, one line per step.
Found by running it on an empty VM: ssh's "Permanently added" warning on
stderr was read as the machine's hostname, so standard error is now kept
apart; and a node added again while cordoned never counted as joined, so
joining now means a heartbeat since the restart.
llmgw node remove forgets a lost node, which otherwise stays listed until
the control plane restarts. ctl nodes no longer lists vLLM as skipped on
every CPU node. The quick install, install and onboarding docs use it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A GB200 NVL72 rack or an NVLink Switch system is a scale-up island: its
GPUs reach each other over NVLink whatever node they are in. Each GPU
now reports its fabric from nvidia-smi -q - state, status, ClusterUUID,
CliqueId, bandwidth - at registration and once a minute after, since a
fabric manager restarting drops every card out at once; and each node
reports nvidia-imex and its channels, without which the domain's GPUs
cannot share memory across nodes. A single machine's NVSwitch, which
reports a cluster of zeros, is no domain.
A replica spanning nodes is placed inside one domain first, on nodes
whose every card is joined and whose IMEX is up, and its shards are
told NCCL_MNNVL_ENABLE=1; InfiniBand is the fallback.
/admin/nvlink draws each domain as a rack - the NVLink Switch band on
top, light running down a backplane, trays of GPU chips that glow when
joined, pulse red when not, turn amber on degraded bandwidth - and
lists what keeps a tray out. A node's page shows its GPU-by-GPU NVLink
matrix, each card's NUMA node and nearest adapter, and its domain and
IMEX. doctor checks joining, bandwidth, IMEX and its channel; metrics
llmgw_gpu_nvlink_joined and llmgw_imex_up; /api/v1/nvlink.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The control plane asks one node on each physical fabric to run
ibnetdiscover every five minutes and parses the text itself, so a
format the parser has not met is a control plane upgrade, not one on
every node. From the map it works out the switch tiers (leaf, spine,
core, by distance from the adapters), which adapter is which node's,
which cables trained below the rate the rest of their kind run at, and
whether the rails line up: every node's Nth adapter on its own leaf.
A page per fabric (/admin/fabrics) draws it: switches in their tiers,
adapters fanned out under their leaves, cables coloured by rate and
bundled, degraded ones marching red with a marker, and the cluster's
own adapters live - down ports glowing red, and particles running each
cable as fast as its adapter is sending and receiving, from the
counters. It zooms, pans, fades what a hovered switch or adapter does
not touch, opens a panel of detail on a click, colours by rail, finds a
node, and refreshes every fifteen seconds. The data is also at
/api/v1/fabrics/{id}/topology.
Placement reads the map: a replica spanning nodes takes nodes of one
leaf together when it can, and nodes whose cable trained short last.
Static assets are named by their content, as the stylesheet already
was.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A fabric's identity was its master subnet manager, which changes on a
failover: for the minute its ports took to agree, one fabric read as
two, and a name covering it as two separate fabrics. Each agent now
also lists every subnet manager on a fabric (saquery SMIR, through one
port per master, once a minute); managers listed together are one
fabric, named by the lowest GUID among them, so the identity survives
the master changing.
The same list says what a fabric can survive. The cluster page's new
subnet manager table, /api/v1/fabrics, doctor and metrics
(llmgw_fabric_master_sm, llmgw_fabric_subnet_managers,
llmgw_fabric_problems) show each fabric's master, priority and
standbys, and say when a fabric has no standby, its ports disagree on
the master, ports are up with no subnet manager (INIT), or the master
changed in the last hour. Every change of master a port reports is
kept, and a fabric's last day of them is listed.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A fabric was what agent.yaml called it. With several independent
InfiniBand fabrics at a site, two given one name would have had a
replica spread across both, starting and then hanging on its first
collective. Each active InfiniBand port now reports the master subnet
manager it sees (sminfo, asked once a minute), which every port on one
fabric shares and ports on separate fabrics cannot; a RoCE port reports
the IP network of its RoCE v2 address. Ports also carry their node and
port GUIDs.
Placement divides a declared fabric by that physical identity and forms
a replica on one part only; a node whose adapters for one name are on
two fabrics is refused, and a node that cannot say is kept apart from
those that can. /api/v1/fabrics and the cluster page list each physical
fabric with its subnet manager, and say when one name covers two
fabrics, two names one fabric, an adapter is up but undeclared, or a
node cannot be checked. doctor reports each port's subnet manager, and
an agent on a node with adapters installs infiniband-diags when sminfo
is missing.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A port's state was read once, at registration: one that went down later
left its node on the fabric, offered multi-node work that would hang on
its first collective, until somebody restarted the agent. The agent now
re-reads every IB and RoCE port on each heartbeat - state, physical
state, rate and the error and data counters - and when the fabrics it
can carry traffic on change, says so once; the control plane replaces
the node's fabrics, which is what placement reads.
The ports are exported as llmgw_ib_port_active (with state and
phys_state, so an unplugged cable reads differently from a missing
subnet manager), llmgw_ib_port_rate_gbps and llmgw_ib_port_counter_total,
and a node's page lists them with the fabric each carries and any error
counter that is not zero.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The nodes are CPU machines, and nothing measured how busy one was: the
heartbeat carried GPU memory and disk, and llmgw_node_memory_bytes is the
total. The agent now reads /proc between heartbeats - CPU across all
cores, load averages, memory used and available, and each engine's
process group's cores and resident memory - and sends it with the
heartbeat. Nothing new runs on the nodes and Prometheus needs no new
target: the control plane exports it with the rest of the fleet, as
llmgw_node_cpu_utilization_percent, llmgw_node_cpus, llmgw_node_load,
llmgw_node_memory_used_bytes, llmgw_node_memory_available_bytes,
llmgw_shard_cpu_cores and llmgw_shard_memory_bytes. A measurement more
than a minute old is left out rather than repeated.
The cluster page's node table shows CPU and RAM as bars, and each node
links to a page of its own: current CPU, RAM, load and disk, the engines
on it with their cores and memory, and an hour of CPU, RAM, load,
per-model cores and memory and queue depth from Prometheus. It refreshes
in place.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Seeing what a node did meant ssh through a jump host, to a machine whose
address nobody remembers, to read a journal only root may open. When an
engine install failed on a new node today, the reason was one line — and it
was four steps away from the page that said the install had failed.
Each node's row on the cluster page now links to its logs: the agent's own,
and every engine running there, chosen from the list the node itself sends.
The page can follow, refreshing every five seconds, and is on both the admin
listener and /admin. `llmgw ctl logs NODE [--source SHARD] [-n N]` reads the
same.
They travel over the stream the agent already holds, so they need nothing
the control plane does not already have: a request goes down, the lines come
back, and a reply that does not come in ten seconds is an agent too old to
answer. The agent keeps its last 2000 lines in memory as well as writing them
wherever it did before; the engines' last few hundred lines were already kept
and sent only when one crashed.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A node ran whatever llama-server somebody had once unpacked on it. Onboarding
checked an engine only when told its path, installed none, and a node with
nothing on it registered as ready. The one time that went wrong it went wrong
invisibly: the binary was there, executable, and could not start for want of
libgomp1, while the node reported healthy.
The control plane now says which engines every node has, at which version —
`engines:` in server.yaml, defaulting to the llama.cpp build this release was
checked against — and each agent converges on it. What only the node can
know, the node works out: the build for its processor and driver (CUDA with
its runtime when an NVIDIA driver is loaded, CPU otherwise), the OS packages
that build needs from its own package sources, and whether the result runs.
Every archive is checked against the sha256 GitHub publishes for it and
unpacked refusing any path or link that leaves the install directory. ldd
names a missing library outright; running `--version` proves the rest. Only
then is a directory marked installed, and it is checked again every ten
minutes, because an unrelated upgrade can remove a library.
An engine is reported only once installed and seen to run, or when the
agent's configuration names it on purpose — never because something happened
to be on PATH. The agent now says when it has probed, so an empty list means
"has none" rather than "too old to say": a node rebuilt from nothing is no
longer a candidate for every model at the moment it can run none of them.
Placement's refusal carries the node's own words, "installing: downloading
llama-b10991-bin-ubuntu-x64.tar.gz (16 MB)", and so do `ctl nodes` and the
cluster page, along with a warning for a CPU without AVX2 — the VM CPU type
that makes everything five times slower and nothing look wrong.
Agents also report their OS, architecture, vector extensions and NVIDIA
driver. Onboarding installs llmgw itself from the CI release for the node's
architecture, checked against the release's checksums, rather than copying
whatever binary the operator's machine had.
vLLM and SGLang are not installed yet: they are Python environments of
several gigabytes, not an archive, and still have to be named in the agent's
configuration.
Also fixes a race on the weights fingerprint, which two heartbeat loops touch
during a failover.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Two defects, both of the same kind: something the CLI knew and the rest of
the system did not.
A profile can be edited while a replica is running against the old one. The
reconciler deliberately leaves it alone — churning a replica that is serving
costs more than the imperfection — but there was no way to see it, so the
cluster could disagree with its own configuration indefinitely and read as
healthy. Profile now carries a fingerprint, a replica records the one it was
placed with, and both the API and `ctl replicas` say "stale profile" when
they differ. An empty fingerprint is not stale: it means a replica adopted
from an older agent, which is unknown rather than wrong.
Adding a model from the admin page skipped the source check `ctl model add`
has done all along, so a typo or a mirror that is down became a replica
failing on a node minutes later, with an error naming the node. The check
moves out of the CLI into a package both use.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
A gateway serving nine models offered nine names and nothing to choose between
them. /v1/models is the only view most clients ever have, and it listed ids.
Models carry a description now: written when the model is added, shown on the
dashboard and sent to clients in /v1/models.
Written rather than derived. A registry offers a pipeline tag and a wall of
README, and neither answers the question somebody picking from a list is
asking — which of these should I send this request to. "General chat, strong
Swedish; slower than the 8B" is not in any metadata field.
It is optional, and absent means absent rather than an empty string in the
response: a model nobody described should read as undescribed, not as described
with nothing.
On the dashboard it sits under its row rather than in a column. A sentence in a
table cell either wraps every other column into a stripe or gets cut off.
Co-Authored-By: Claude Opus 5 (1M context) <moreply@anthropic.com>
A node's registry holds an adapter for every engine whether or not its binary
exists, the agent never said which were installed, and placement carried an
Engine field it had never once read. So a vLLM replica was as happily placed on
a node with no vLLM: the node registered healthy, the shard failed minutes
later with "executable file not found" in the engine's own words, and the
reconciler tried again.
That is how fifteen gigabytes of safetensors reached this cluster's mirror
before anybody noticed it had no card and no vLLM to run them with.
Agents now probe what is installed and report it — the protocol has carried
engine_versions since it was written and nothing ever filled it in. Placement
filters on the key set, `ctl nodes` has a column, and the mirror page's serve
warning is a fact instead of a guess about cards, which would have waved
through a fleet of eight-GPU nodes that never had vLLM.
Probing resolves binaries and runs none of them. The first version asked each
engine for --version, which is fine for an engine and not fine for the wrapper
scripts people put in front of one: a script that shifts past flags it does not
recognise and then execs the server will start an inference server, at agent
startup, on every node. The agent's own test suite installs exactly such a
script and caught it. So presence is a path lookup, and the version is left to
`ctl engine-check`, which is run by somebody who meant to run the engine.
SGLang is the exception and has to execute, because a module has no path to
look up — but the command is llmgw's own one-line import rather than the
engine's launcher. Its exit code is the answer: python3 is on almost every
machine, and treating a failed import as "installed" reported SGLang on every
node in a fleet that had none, which is the failure being fixed, inverted.
Probed once, not per reconnect, and bounded by the context that registration
waits on: an agent that cannot reach the control plane is worse than one
reporting an incomplete list.
A node that reports no engines at all is not excluded anywhere — by placement,
or by the page. That is what every agent older than this reports, and emptying
a fleet on a control plane upgrade is a worse failure than the one being fixed.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Quotas can be written on an organization, a team or a project, and nothing
could show what any of them had used: usage came back per key, per user and per
model only. A quota whose consumption cannot be seen is one nobody reviews
until the day it refuses somebody — and since the previous commit made a group
quota a shared pool, it is now a number several people are spending against
without being able to look at it.
`llmgw ctl usage --by team` sums every key beneath each group, with the budget
that level sets beside it.
Beside it, and only when that level sets one. A team bounded by its
organization's budget has none of its own, and printing the organization's
against each of its teams would read as though each had that much — the exact
misreading this work exists to remove.
Joined through api_keys rather than read from usage.project_id: that column
records where the key was when the request was served, while the quota is
written against the tree. They agree until a key is moved, and a report that
disagrees with the limit shown beside it is the useless one.
Three existing reports were fixed on the way, all failing on PostgreSQL and all
passing in tests, because the tests run on SQLite:
column "k.name" must appear in the GROUP BY clause (UsageSince)
column "us.email" must appear in the GROUP BY clause (UsageByUser)
column "usage.ts" must appear in the GROUP BY clause (UsageBuckets)
SQLite picks an arbitrary row for an ungrouped column and carries on; PostgreSQL
refuses. The first two were selecting names they had not grouped. The third
grouped "ts / ?" while selecting "(ts / ?) * ?", which PostgreSQL matches as
text and so saw a bare ts — it is grouped by ordinal now, the same expression by
construction. The dashboard's usage charts have been empty on the cluster this
whole time, with the reason only in the log.
All four queries were run against the cluster's own PostgreSQL before this was
committed, because passing on SQLite is what they were already doing.
The grouping level picks from a fixed table of levels rather than being
interpolated, so an unknown one is an error and not a fragment of SQL.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
`ctl bench` has always been able to work out what one replica can serve — it
ramps concurrency until the SLO breaks and reports the last level that held.
It printed that and nothing kept it, so the one number saying what a replica is
worth lived in whoever ran it's scrollback. Everything downstream then had to
guess: admission applies a single global default for healthy queue depth, and
sizing a model against real demand had nothing to size against.
`ctl bench --save` records it; `ctl capacity` reads it back.
Keyed by model and profile. Capacity belongs to the hardware and the engine
arguments as much as to the weights, so the same model on CPU and on an H100
are two numbers, and one key would overwrite the other on every run.
The profile is looked up from the replica rather than asked for, because the
control plane already knows which profile answers on which endpoint and a
measurement filed under the wrong one is worse than none. A target that is not
a replica — the gateway, usually — is refused with that said: benchmarking the
whole path is worth doing and says nothing about the hardware.
The conclusion is stored, not the ramp. Every level and its latencies are worth
reading once while judging whether the run was sound; keeping them would grow
without bound as a model is re-benchmarked.
Re-measuring replaces. A second run is a better answer to the same question,
not another data point, and keeping both would leave a reader choosing between
numbers with no basis for the choice.
The SLO and the date are stored with it. Capacity means nothing without the
target it was measured against, and hardware and engine builds change — a
measurement is an observation with a date on it, not a fact about the model.
A failed save is reported and not fatal: the run has already cost the GPU time.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The count is scaling.min, and until now the only way to change it was to edit
server.yaml on the host and restart — or, for a model added at runtime, to
remove it and add it back, which means having its whole definition to hand.
`llmgw ctl scale <model> --min N` instead. Only the scaling block moves:
everything else is read back from what was stored and written out untouched, so
changing a number cannot quietly become a redefinition.
The catalog is rebuilt and validated before anything is written, as in Add. A
max below a min is refused with the stored definition untouched — persisting a
rejected change would come back on the next restart as a catalog that does not
build.
The answer reports the scaling in force rather than the request. The catalog
fills in a max that was left out, and a caller echoing its own request would
print a number the cluster is not using.
A model declared in configuration is refused, for the reason Remove already
refuses one: the YAML is read on every start, so the new count would hold until
the next restart and then silently revert. A cluster disagreeing with its own
config file is worse than an error saying where to edit.
The help says what --max does, because it is not what it looks like: a model
with a minimum runs exactly that many and nothing scales it up under load, and
an on-demand model loads one replica however high its max.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The agent has always logged a percentage as it fetches weights, with a comment
saying a replica pulling a hundred gigabytes and one that is wedged look
identical from the control plane. They still did: the log is on the node, and
the node is not where anyone is looking when a replica has been starting for
ten minutes.
Progress now rides on the shard status and appears under the replica in `ctl
replicas` — a line rather than a column, because most replicas are not
downloading anything and a column would be empty for all of them.
It is deliberately not a state transition. Treating each chunk as one would
re-mark the shard as starting on every report and reset the timer that decides
when a slow start has become a failed one, so an hour-long download would keep
a doomed replica alive indefinitely. It arrives on its own method for that
reason, and a real transition clears it — otherwise a finished download sits in
the listing at ninety-nine percent under a shard that has been serving for an
hour.
Watchers are keyed by source rather than by shard, because a fetch is
single-flight: eight shards starting together produce one download and all
eight are waiting on it.
No percentage is invented when the server sent no length. One that stops moving
is worse than a byte count that keeps rising, so the field is absent and the
listing says "so far".
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
