# Debug lifecycle configurations
Debug lifecycle configurations

The following topics show how to get information about and debug your lifecycle configurations.

**Topics**
+ [

## Verify lifecycle configuration process from CloudWatch Logs
](#jl-lcc-debug-logs)
+ [

## Lifecycle configuration timeout
](#jl-lcc-debug-timeout)

## Verify lifecycle configuration process from CloudWatch Logs


Lifecycle configurations only log `STDOUT` and `STDERR`.

`STDOUT` is the default output for bash scripts. You can write to `STDERR` by appending `>&2` to the end of a bash command. For example, `echo 'hello'>&2`. 

Logs for your lifecycle configurations are published to your AWS account using Amazon CloudWatch. These logs can be found in the `/aws/sagemaker/studio` log stream in the CloudWatch console.

1. Open the CloudWatch console at [https://console.aws.amazon.com/cloudwatch/](https://console.aws.amazon.com/cloudwatch/).

1. Choose **Logs** from the left navigation pane. From the dropdown menu, select **Log groups**.

1. On the **Log groups** page, search for `aws/sagemaker/studio`. 

1. Select the log group.

1. On the **Log group details** page, choose the **Log streams** tab.

1. To find the logs for a specific space, search the log streams using the following format:

   ```
   domain-id/space-name/app-type/default/LifecycleConfigOnStart
   ```

   For example, to find the lifecycle configuration logs for domain ID `d-m85lcu8vbqmz`, space name `i-sonic-js`, and application type `JupyterLab`, use the following search string:

   ```
   d-m85lcu8vbqmz/i-sonic-js/JupyterLab/default/LifecycleConfigOnStart
   ```

## Lifecycle configuration timeout
Lifecycle configuration timeout

There is a lifecycle configuration timeout limitation of 5 minutes. If a lifecycle configuration script takes longer than 5 minutes to run, you get an error.

To resolve this error, make sure that your lifecycle configuration script completes in less than 5 minutes. 

To help decrease the runtime of scripts, try the following:
+ Reduce unnecessary steps. For example, limit which conda environments to install large packages in.
+ Run tasks in parallel processes.
+ Use the nohup command in your script to make sure that hangup signals are ignored so that the script runs without stopping.