papierGaylard

I'm pretty sure that's got to do with how AWS Sagemaker determines what is a 'failed' processing job. It only causes it to 'fail' if there are specific kernel issues...

Here's an update with my log output from the 'install-run-notebook.sh': ``` sh-4.2$ bash install-run-notebook.sh Collecting https://github.com/aws-samples/sagemaker-run-notebook/releases/download/v0.20.0/sagemaker_run_notebook-0.20.0.tar.gz Downloading https://github.com/aws-samples/sagemaker-run-notebook/releases/download/v0.20.0/sagemaker_run_notebook-0.20.0.tar.gz (64 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 64.7/64.7 KB 1.3 MB/s eta 0:00:00 Preparing metadata (setup.py)...

**UPDATE:** If anyone else is looking to automate their jupyter notebook scripts in was JUPYTER LAB. Then follow the instructions for JUPYTER LAB and not AWS Sagemaker Studio! (for me)...

Any updates on this? Exact same issue

For me, I need to run my sagemaker processing job within a VPC and within a subnet, I'm specifying the subnet and VPC like such: `--extra '{ "NetworkConfig": { "EnableInterContainerTrafficEncryption":...

> Hi @tomfaulhaber , Any progress with this? It really makes the solution unreliable. Anything I can help? So I think you need to create a VPC enpoint. For some...