That would be an advanced form of machine learning :)
Here's another example:
I put a water bucket in a container. It's job is to store water. As a user of the water bucket, I place the container with the water bucket under a faucet and fill the water bucket with water. I leave it unattended and come back to see not only the bucket is full, but water has also filled up the container.
I can see that the container has done its job in keeping the water bucket secure and prevented the water from leaking out of the container. The bucket has also done its job in storing water. However, the bucket has a flaw: it keeps accepting water even though it is full. And now because the container and water bucket is full, it no longer holds water. Now the water is all over the container, I have to clean it up in order to have the water bucket continue to do its intended function with more water.
In real world terms:
water bucket = app
container = Glassware container/productivity container
water = disk space
What we see here is that while the container has done its job, the app still has a bug/security vulnerability. While the bug still exists, the container has prevented the bug from affecting anything outside of it (ie. the host OS). That's assuming that the container has safeguards that prevent disk from consuming everything on the host OS. The water bucket is still broke though!
How do we fix this bug?
* Refactor the water bucket and add controls in to prevent the bucket from overflowing.
* Configure the container to redirect to external storage (ie. Google Drive, OneDrive, SnapCloud, etc)
* Refactor the storage component out of water bucket and into another container using a Windows Server or Docker container. The storage component becomes a microservice that is running in a different container. Note: This is not a productivity container and why I have always said Glassware does not compete with Docker.
