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@@ -25,6 +25,9 @@ _sidebar.rst.inc
 # The requirements lockfile is generated when packaging the chart
 helm-chart/renku/requirements.lock
 
+# Charts dependencies downloads
+helm-chart/renku/charts
+
 # Created by https://www.gitignore.io/api/vim,macos,linux,emacs,scala,python,visualstudiocode,helm
 # Edit at https://www.gitignore.io/?templates=vim,macos,linux,emacs,scala,python,visualstudiocode,helm
 
 
@@ -0,0 +1,54 @@
+---
+title: High Memory Usage
+---
+
+## Why This Alert Was Triggered
+
+Your session is using more than 90% of its allocated memory capacity. This can happen when:
+
+- Your code is processing large datasets
+- Your code has memory leaks or is accumulating data in memory without releasing it
+- The memory allocation for your session is too small for your workload
+
+## What This Means
+
+When memory usage is this high, your session is at risk of:
+
+- Becoming unresponsive or slow
+- Being terminated by the system if it exceeds its memory limit ([Out of Memory kill](./20-session-restarted.md))
+- Losing unsaved work if the session terminates unexpectedly
+
+## Steps to Remedy
+
+### Immediate Actions
+
+1. Commit and push any important changes to avoid losing them
+2. Free up memory:
+   - Stop any running processes you don't need
+   - Clear large variables from memory in your notebooks or scripts (e.g., `del variable` in Python)
+   - Restart your Python kernel if using Jupyter notebooks
+
+### Longer-Term Solutions
+
+1. Optimise your code:
+   - Process data in smaller chunks
+   - Use generators or iterators instead of loading full datasets
+   - Delete variables you no longer need during execution
+   - Use memory-efficient data types and libraries
+
+2. Request more memory:
+   - Pause your current session
+   - Modify the session resources to use a resource class with more memory, if available
+   - Resume your session
+   - See [Resource Pools and Classes](../30-resource-pools-and-classes.md) for more information
+
+3. Profile memory usage:
+   - Use memory profiling tools to identify which parts of your code use the most memory
+   - For Python: `memory_profiler`, `tracemalloc`, or `guppy3`
+   - For R: `pryr::mem_used()` or `profmem`
+
+## Prevention
+
+- Choose an appropriate resource class when starting sessions based on your expected workload
+- Test code with small datasets first to estimate memory requirements
+
@@ -0,0 +1,62 @@
+---
+title: Session Restarted (Out of Memory)
+---
+
+## Why This Alert Was Triggered
+
+Your session ran out of memory and was automatically killed and restarted. This happens when:
+
+- Your session tried to use more memory than was allocated to it.
+- Memory usage spiked suddenly, exceeding the limit before you could react
+- A process had a memory leak that gradually consumed all available memory
+- Multiple memory-intensive operations ran simultaneously
+
+## What This Means
+
+When a session is restarted:
+
+- Any changes not committed to Git and pushed to remote, or saved to disk are gone
+- In-progress processes were terminated
+- Your Python kernel, R session, or other runtime environments have been reset
+
+## Steps to Remedy
+
+### Immediate Actions
+
+1. Check what was lost:
+   - Review your Git status to see if you have uncommitted changes: `git status`
+   - Look for any auto-saved files or checkpoints
+   - Check if your notebook or IDE has auto-recovery features
+
+2. Prevent recurrence before restarting work:
+   - Review what you were running when the restart occurred
+   - Identify memory-intensive operations that need optimisation
+
+### Longer-Term Solutions
+
+1. Optimise memory usage:
+   - Process data in smaller chunks instead of loading everything at once
+   - Use memory-efficient data structures and algorithms
+   - Stream data from disk rather than loading it all into memory
+   - Delete large variables when you're done with them: `del variable` in Python, `rm(variable)` in R
+   - Use generators or iterators for large datasets
+
+2. Request more memory:
+   - Pause your current session
+   - Modify the session resources to use a resource class with more memory, if available
+   - Resume your session
+   - See [Resource Pools and Classes](../30-resource-pools-and-classes.md) for more information
+
+3. Monitor memory usage:
+   - Add memory profiling to your code
+   - Use the [High Memory Usage](./10-high-memory-usage.md) alert as an early warning system
+
+4. Save work frequently:
+   - Commit and push changes to Git regularly
+   - Save intermediate results to disk
+   - Use checkpoint systems in long-running computations
+
+## Prevention
+
+- Choose an appropriate resource class when starting sessions based on your expected workload
+- Test code with small datasets first to estimate memory requirements
@@ -0,0 +1,62 @@
+---
+title: Low Disk Space
+---
+
+## Why This Alert Was Triggered
+
+Your session has less than 10% of its disk space remaining. This typically happens when:
+
+- You've downloaded or generated large files in your session
+- Intermediate files have accumulated over time
+- Log files or cache directories have grown large
+
+## What This Means
+
+When disk space is this low:
+
+- You may not be able to save new files
+- Running processes might fail
+- Your session may become unstable or crash
+
+## Steps to Remedy
+
+### Immediate Actions
+
+1. Push any important changes to your Git repository or external storage to avoid data loss.
+
+2. Identify large files:
+   ```bash
+   # Find the largest files in your Renku volume
+   du -h $RENKU_MOUNT_DIR | sort -h | tail -20
+   ```
+
+3. Free up space:
+   - Delete temporary files, old logs, or intermediate computation results
+   - Remove downloaded datasets you no longer need
+
+### Longer-Term Solutions
+
+1. Manage data more efficiently:
+   - Use a [Data Connector](../../40-data/00-data.md) to access data from external storage without copying it to your session's disk (e.g., S3, Azure Blob Storage, external data repositories)
+   - Use data streaming instead of downloading entire datasets
+   - Clean up output files regularly
+
+2. Request more disk space:
+   - Save any unsaved work, push all data you wish to keep to your code repositories and/or data connectors and shut down your current session
+   - Increase the disk storage by editing the session launcher. This will only be possible if the maximum disk storage for the selected resource class size has not already been met. If it has, you may be able to switch to a different resource class with a larger maximum disk size.
+   - Restart your session.
+   - See [Resource Pools and Classes](../30-resource-pools-and-classes.md) for more information
+
+3. Optimise your workflow:
+   - Configure applications to use temporary directories that you can clean regularly
+   - Write outputs to compressed formats when possible
+   - Implement automatic cleanup of intermediate files in your scripts
+
+## Prevention
+
+- Monitor disk usage regularly: `df -h $RENKU_MOUNT_DIR`
+- Set up your code to clean up temporary files automatically
+- Choose an appropriate resource class with sufficient storage when starting sessions
+- Keep only necessary files in your session workspace
+- Use a [Data Connector](../../40-data/00-data.md) to store and access large datasets from external storage instead of keeping them on your session disk
+
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+label: Alerts
+collapsed: true