Yoda Response: Provide an example of a challenging data transformation or storage problem, I shall. Recently, worked on setting up Elasticsearch with Kubernetes, I did. A significant challenge, it was.

Needed, we did, a local SSD for faster data retrieval. EBS volumes, not suitable they were. Create a storage class for local SSD, we had to. Kubernetes, by default, does not provide this. Third-party solution, OpenEBS, we used. Provision local storage, it does.

However, mounting SSDs on numerous virtual machines, a challenge it was. Auto-scaling cluster, we had, with varying numbers of machines. Manually mounting SSDs, impractical it was. Script, I wrote, to automate this process. Identify and mount SSD storage on each node, the script does, whenever a machine spins up.

Another challenge, maintaining data integrity in NoSQL databases like Elasticsearch. Unstructured data, prone to storing unwanted fields, it is. To prevent this, a template we created. Define what data should be stored, the template does. Strict mapping, we enforced. Only data in the correct format, allowed it is.

Thus, by using OpenEBS for local SSD storage and creating strict templates for data integrity, solved challenging storage and data transformation problems, we did.