# How to Share a ClearML Experiment From a Self-Hosted Server

Canonical: https://commareports.com/share-clearml-report
Published: 2026-09-14

> A self-hosted ClearML server is on your VPN, so nobody outside it can open a task link. Publish the results as a page and share a URL that works anywhere.

# Share a ClearML experiment

ClearML is often chosen precisely because it can be self-hosted: the server
runs in your VPC, the data never leaves, and the compliance conversation is
short.

That same property is why nobody can see your results. `http://clearml.internal:8080/projects/…`
is a perfect link on the VPN and a connection timeout everywhere else.

## Self-hosting is the feature and the problem

The people who need to see a model's results are rarely all on the network:

- A product owner working from a laptop with no VPN client.
- An external reviewer or auditor.
- A collaborator at a partner org.
- Your own team, on a phone, in a meeting room.

Handing them a VPN and a ClearML account to see one metrics table is a
disproportionate ask, and the usual fallback — screenshotting the scalars tab
into Slack — throws away every number's precision. See
[stop screenshotting reports](/stop-screenshotting-reports).

## Pull the results, publish the page

The SDK gives you everything the UI shows:

```python
from clearml import Task

task = Task.get_task(task_id=task_id)
scalars = task.get_last_scalar_metrics()
params  = task.get_parameters()
# render a page from scalars, params and the plots you care about, then publish
```

Publish one document containing the comparison against the incumbent, the two
or three plots that carry the argument, the parameter set, and the task id for
anyone who *is* on the VPN and wants the raw run.

The task id in the footer matters: it keeps the internal system of record
authoritative while letting the conclusion travel.

## You choose what crosses the boundary

The objection to any external publishing in a self-hosted shop is, correctly,
"what leaves?"

The answer here is: exactly the fields you put in the page. A metrics table,
rendered plots, hyperparameters. Not the dataset, not the model weights, not
the artifacts. And the report itself can be access-restricted rather than open
— see [security](/security) and the
[subprocessor list](/subprocessors) if procurement asks.

## Automate it at the end of the task

```python
task = Task.init(project_name="churn", task_name="v31")
...
publish_report(title=f"churn · {task.name}", html=render(task))
```

Every completed run refreshes the same report id, so the link in your tracking
ticket always shows the current state, with the previous round's comments still
attached. If the schedule is the hard part, [routines](/docs/routines) can own
it.

## Worth knowing

- **Static plots, not iframes.** Embedding the internal UI produces a page
  that fails for exactly the audience you built it for.
- **Publish numbers as text, not pictures.** A screenshotted metrics table
  cannot be searched, copied or diffed.
- **Comments anchor to the figure** — see
  [commenting on HTML](/comment-on-html).
- **5 MB per report body.**

## Try it

Free — unlimited reports, commenters and revisions.

**[Read the API reference →](/docs/api)**

### Related

- [Share a Comet ML experiment](/share-comet-report) ·
  [Share an MLflow report](/share-mlflow-report)
- [Share a Weights & Biases report](/share-wandb-report) ·
  [Share a TensorBoard report](/share-tensorboard-report)
- [Security](/security) · [Comma for data scientists](/for/data-scientists)