# Upgrade Fabric Workspaces To The Latest GA Runtime

It’s always a good idea to use the latest GA runtime for the Spark pool in Fabric. Unless you change it manually, the workspace will always use the previously set runtime even if a new version is available. To help identify the runtime that workspaces are using and to upgrade multiple workspaces at once, use the code below, powered by Semantic Link.

Here I scrape the [MS Docs](https://learn.microsoft.com/en-us/fabric/data-engineering/runtime) to get the latest GA runtime and use the APIs to check/upgrade the runtimes.

```python
import sempy.fabric as fabric
import requests
import pandas as pd

client = fabric.FabricRestClient()

def get_latest_ga_runtime(url=None):
    """
    Get the latest GA Fabric runtime
    ref : https://learn.microsoft.com/en-us/fabric/data-engineering/runtime

    """
    url = "https://learn.microsoft.com/en-us/fabric/data-engineering/lifecycle" if url is None else url
    df = pd.read_html(url)[0]
    return (df[df['Release stage'] == 'GA']
            .assign(Version=lambda x: x['Runtime name'].str.extract(r'(\d+\.\d+)'))
            ['Version'].max())

latest_rt = get_latest_ga_runtime()


def get_workspace_runtime(workspaceId=None):
    """
    Get current runtime of the default environment of a Fabric workspace

    """
    workspaceId = fabric.get_notebook_workspace_id() if workspaceId is None else workspaceId
    
    try:
        result = client.get(f"v1/workspaces/{workspaceId}/spark/settings")
        return result.json()['environment']['runtimeVersion']
    except (requests.RequestException, KeyError):
        return "na"

workspaces = (fabric.list_workspaces()
      .query('`Is On Dedicated Capacity`==True and `Name`!="Admin monitoring"') #Only P or F
      .assign(runtime=lambda df: df['Id'].apply(get_workspace_runtime))
      .assign(is_latest_rt = lambda rt:rt['runtime'] ==latest_rt ))

workspaces
```

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1733945765502/cc3da49e-acb1-4b9f-8648-d5b8f4561440.png align="center")

### Outdated workspaces

You need to be a workspace admin to change the runtime version

```python
outdated_rt_ws = workspaces[workspaces['is_latest_rt']==False]
display(outdated_rt_ws)

def upgrade_runtime(runtime:str, workspaceId=None):
    workspaceId = fabric.get_notebook_workspace_id() if workspaceId is None else workspaceId
    payload ={"environment": {"runtimeVersion": runtime }}

    return client.patch(f"/v1/workspaces/{workspaceId}/spark/settings", json = payload)

## Either iterate over the above outdated_rt_ws dataframe or upgrade the runtime for one specific workspace
## if workspaceId=None, the workspace of teh notebook is used

upgrade_runtime(runtime = latest_rt, workspaceId=None)
```

**Update :**

You can also use [Semantic Link Labs](https://semantic-link-labs.readthedocs.io/en/stable/sempy_labs.html#sempy_labs.update_spark_settings) to get and update the spark settings. Thanks to Michael Kovalsky for the tip.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1733978650543/740964c7-931b-4185-a28b-fe7ecbbcd28d.png align="center")

Needless to say, before changing the runtime version, ensure your spark jobs can run in the specified runtime.