> ## Documentation Index
> Fetch the complete documentation index at: https://mage-staging.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Logging

## Server Logging

The server logger can be configured to adjust the amount of detail that is included in the server logs. This can be helpful for debugging or troubleshooting server issues. You can change the verbosity level of the logger by setting the `SERVER_VERBOSITY` environment variable.

The `SERVER_VERBOSITY` variable accepts the following values: `DEBUG`, `INFO`, `WARNING`, `ERROR` and `CRITICAL`.

## Pipelines logging

By default, logs for each pipeline run will be stored in the
`<path_to_project>/pipelines/<pipeline_name>/.logs` folder.

Learn more about logs [here](/design/core-abstractions#log).

### Set logging level

The default logging level is `INFO`. To customize the logging level for logs of block runs and pipeline runs,
you can set the `level` of `logging_config` in your project's `metadata.yaml` file.

Example logging config to only log errors:

```yaml theme={null}
logging_config:
  level: ERROR
```

### Set log retention period

To delete old logs in your peristent volume, you can specify the `retention_period` in the `logging_config`. Valid period units
are 'h', 'd', and 'w'.

Example logging config:

```yaml theme={null}
logging_config:
  retention_period: '15d'
```

Then you can run command `mage clean-old-logs [project_uuid]` to clean up old logs

### Block logging

A logger is available in the block's context. You can use it to log messages to the block's log file. The logger is passed into
each block as a keyword argument. You can retrieve the logger by calling `kwargs.get('logger')` within the block.

Example:

```python theme={null}
@data_loader
def load_data(*args, **kwargs):
    kwarg_logger = kwargs.get('logger')

    kwarg_logger.info('Test logger info')
    kwarg_logger.warning('Test logger warning')
    kwarg_logger.error('Test logger error')

    ...
```

## Logging to external destination

### S3

To store logs in S3, you need to set the `logging` config in your project's `metadata.yaml` file.

Example S3 logging config:

```yaml theme={null}
logging_config:
  type: s3
  level: INFO
  destination_config:
    bucket: <bucket name>
    prefix: <prefix path>
    aws_access_key_id: <(optional) AWS access key ID>
    aws_secret_access_key: <(optional) AWS secret access key>
    endpoint_url: <(optional) custom endpoint url>
```

To authenticate with S3, the credentials need to be configured in one of the following ways:

* Configure credentials in the `logging_config`.
* Configure credentials in environment variables: `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
* Authenticate with IAM role. Grant S3 access to the IAM role of the cloud instance.

The `endpoint_url` can be configured to connect to S3 compatible services (e.g. MinIO).

### Google Cloud Storage

To store logs in GCS, you need to set the `logging` config in your project's `metadata.yaml` file.

Example GCS logging config:

```yaml theme={null}
logging_config:
  type: gcs
  level: INFO
  destination_config:
    path_to_credentials: <path to gcp credentials json file>
    bucket: <bucket name>
    prefix: <prefix path>
```

<br />

*More destinations coming...*

<br />

***

## Edit pipeline logging

When you’re editing a pipeline (e.g. `/pipelines/[uuid]/edit`), you can execute the code for an
individual block and see the output. Any `print` statements in the block of code is displayed
in the block’s output.

However, you can redirect those `print` statements to output to logs.

To toggle this feature, go to the pipeline settings page (e.g. `/pipelines/[uuid]/settings`)
and check the box labeled
<b>When running a block while editing a pipeline, output the block messages to the logs</b>.