Slurm is not a machine that attaches and stays; it is a queue somebody else
owns. So nothing here submits a node to it. It submits a job whose payload is an
ordinary worker dialling back in, and everything downstream — the protocol, the
artifacts, cancellation, the books — already worked and did not have to learn
what Slurm is.
The alternative, which Covalent takes, is to stage a serialized call and a
runner onto the login node, poll squeue and copy the result back: a second way
of running a node beside the one that exists. The cost of not doing that is one
assumption, that a compute node can open a connection outward. Where that is
false, _payload is the single method a staged variant would replace.
Clusters are configured in provisioners.json beside the alerts, since this is
infrastructure an operator writes rather than anything a flow says. The script
is generated with the system ssh and no new dependency, and prerun owns the
environment — deliberately no pip install, because what is on a cluster is
somebody's decision.
One outstanding request per profile, cancelled if it never attaches and on the
way out. Nothing autoscales.
The run gate needed the same hook: a run held before it starts never reaches the
placer's own wait, so it would have queued forever on a machine nothing had
asked for.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
A worker reported its labels and nothing about the machine behind them, so the
engine could route a node to a GPU box but not tell whether that box had a GPU
free. Inventory — cores, GPUs, memory — now arrives with the hello frame, and
the run frame carries back what the engine allocated for that call.
Which is protocol 2 on both ends. GPUs are never probed: asking a vendor tool
would make the one dependency two, so a GPU is what the batch job says it was
given or what --gpus says. A worker that reports nothing still attaches and is
scheduled by its label alone.
Two things a job scheduler needs: --max-idle stops a worker started for one job
rather than letting it hold its allocation to the walltime, and a refusal is now
fatal instead of a reconnect loop that reads as a hang in a job's log.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
Four things the python SDK turned up, each fixed where every client sees it.
A key no port declares is now an error rather than a silent drop, on the
return, the yield and the emit alike — the contract the docs already stated.
The SDK reads literal yields at sync time, so a typo fails before anything
runs, and an emission of one fails the call rather than being logged where
nobody looks.
NaN and infinity are refused at the port. JSON cannot spell either, so one
that travelled came back as a 500, a socket frame that stopped the canvas, or
a metric batch the database dropped whole.
An artifact input takes `@run:<id>.<output>` or a bare digest, resolved on the
engine — so the CLI, the run dialog and a python caller mean the same thing,
and a sweep can pass one at all.
Node timeouts are off by default. The clock measured silence, which a training
node is full of, and remote workers had already stopped enforcing it — their
heartbeat reset it. Now a heartbeat proves the agent rather than the node,
ninety seconds of nothing fails the call either way, and the engine touches
work it is still running so a long node is not redelivered at sixty seconds.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019V5bsYGNxcgPs4xXmTPx69
A zensical site under docs/, served by a new `docs` compose service behind
Traefik, built with --strict in CI. Same pattern the sibling n3xd workspace
uses.
Getting started splits the way the landing page does — one path is
`pip install fluksio` and a training script, the other is a Docker stack and
an afternoon in the browser — because the two audiences will not spend the same
amount of time. Everything after that is shared: the concepts, the web
interface (app and portal), the CLI and the API, and a reference for node types,
payload types and configuration.
The three flow guides move here from the docs submodule rather than being
copied, so there is one version of them.
Styling mirrors DESIGN-GUIDELINES.md: the app's token palette remapped onto
Material's variables in both schemes, Inter, the 16px panel radius, and the one
terracotta accent spent on the facility lane of the audience split.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01M7Xv3cJEW5c8AXxn2hoojV
stroblmeandClaude Opus 5