Tasks and logs

Remote function calls, endpoint requests, and scheduled runs each create a task. The task keeps the call’s status, result or error, and logs after the container stops, so you can inspect a failure or collect the result of background work later. .local() calls do not create tasks.

Live progress

lazycloud run and .remote() called from your machine show the same live display: image build, source upload, task status, and the cloud container’s stdout and stderr, followed by a summary. A failed step keeps its recent logs on screen. When output is redirected, build logs print without live redraws. Progress and logs go to stderr. The CLI prints the result to stdout, and Python returns it to the caller. output(enabled=False) silences the display in Python:

from lazycloud import output

with output(enabled=False):
    result = summarize_sales.remote([1200, 3500, 800])

Calls made inside LazyCloud containers are quiet unless wrapped in with output():. Silencing output leaves exceptions and stored logs intact.

Lifecycle

A task is pending until a container picks it up, then running. If an attempt fails and retries remain, the same task moves to retry. It ends as complete, failed, timeout, cancelled, or expired.

Why a task is pending

After five seconds pending, the CLI and dashboard show the reason: compute is starting, the container is starting, every container is busy, the workspace is at its compute limit, an input call has not finished, or a retry delay is running. If “every container is busy” lasts longer than a container start, the workload is at its max_containers. See Scaling. Your own code receives the same reason through lazycloud.progress():

import lazycloud


def report(task_id: str, pending: lazycloud.TaskPendingProgress | None) -> None:
    if pending is not None:
        print(task_id, pending.reason, pending.message)


with lazycloud.progress(report):
    result = summarize_sales.remote([1200, 3500, 800])

The callback receives None when the reason clears. For a call submitted with .spawn(), read call.task.pending_progress.

Look up a task from Python

handle = summarize_sales.spawn([1200, 3500, 800])
print(handle.task_id)

outcome = handle.result(wait=True, timeout_seconds=120)
print(outcome.ok, outcome.status, outcome.value, outcome.error)

handle.get(timeout_seconds=120) returns the value or raises on failure, and handle.logs() reads stored logs. From another process, reconnect by ID:

from lazycloud import Task

task = Task.from_id("<task-id>")
outcome = task.wait(timeout_seconds=120)

task.cancel() cancels pending work.

Look up a task from the CLI

uv run lazycloud task show <task-id>
uv run lazycloud logs --task-id <task-id> --follow

LazyCloud captures everything your code prints. flush=True makes lines appear as they happen. The task and logs reference lists every command, and the dashboard’s Tasks page shows the same history.

Callbacks

Functions, endpoints, ASGI apps, and realtime handlers accept callback_url. LazyCloud calls that webhook with execution events as the task changes state, so another system can react without polling.

Getting started

Core concepts

CLI reference

Examples

Account

Live progress

Lifecycle

Why a task is pending

Look up a task from Python

Look up a task from the CLI

Callbacks

​Live progress

​Lifecycle

​Why a task is pending

​Look up a task from Python

​Look up a task from the CLI

​Callbacks

Live progress

Lifecycle

Why a task is pending

Look up a task from Python

Look up a task from the CLI

Callbacks