docs: add known issues

Author: mesakhcienet

examples/science/af3-slurm/examples/simple_ipynb_launcher/README.md

@@ -11,10 +11,12 @@ Please note that the launcher needs 2 specific setup steps:
 ## Usage Guide
 For usage of the Ipynb Launcher consult the [Step-by-Step Instructions](./Ipynb.md)
 
-## Known Limitations
+## Known Issues
 You may encounter the following problems while using the notebook.
 
 ### Warning during dependency installation
+
+**Description**:
 You may encounter the following warning during dependency installation:
 
 ```text
@@ -25,3 +27,49 @@ google-cloud-bigtable 1.7.3 requires grpc-google-iam-v1<0.13dev,>=0.12.3, but yo
 **Resolution**: This warning can be **safely ignored**.
 
 The version mismatch does not impact the functionality required by this project. The `google-cloud-bigtable` package is not used in any critical code path, and no issues have been observed during execution.
+
+### Resource Unavailability (Out of Capacity)
+
+**Description**:  
+Your job is queued but not executed because the cloud provider (e.g., GCP) can't provision the required compute nodes. This is often due to a temporary lack of available resources in the chosen region or zone.
+
+**Resolution**:
+- Check the **Controller Logs**:  
+  Log on to the controller machine for your cluster to see detailed error messages like  
+  `"GCP Error: Zone does not currently have sufficient capacity for resources"`.
+- **Wait and Re-check**:  
+  For temporary resource shortages, wait **5–10 minutes** and then re-run the "check job status" cell in your Jupyter notebook. Resources might become available and allow your job to proceed.
+
+### Node Creation In Progress
+
+**Description**:  
+After your job is submitted, it takes time for the cluster to spin up new nodes. You might see a `NODE_FAIL` status if nodes are still being created and are not yet ready.
+
+**Resolution**:
+- Monitor the **Controller Logs** for status updates.
+- **Wait 5–10 minutes**, then recheck your job status to see if nodes have become available.
+
+---
+
+### Runtime-Related Issues
+
+These issues occur once your job attempts to run on the allocated nodes.
+
+### Input File Format Error
+
+**Description**:  
+Your job might fail immediately if the input file format is incorrect or if the file is corrupted.
+
+**Resolution**:
+- Review the **Job Logs** to identify input file issues.
+- Ensure the input file meets the expected format and isn't corrupted.
+
+### Out of Memory (OOM) Issue
+
+**Description**:  
+Your job may start but fail during execution because it requires more memory than the allocated node can provide. This can occur in both the **datapipeline** and **inference** stages.
+
+**Resolution**:
+- Check the **Job Logs** for OOM errors or memory-related failures.
+- Modify your code or input data to reduce memory usage.
+- Consider requesting **larger node sizes** with higher memory capacity.