It's an enterprise edition of the cloud that has been provided to us.  

Deployment is an easy task on the cloud because the deployment link is readily available on Google Cloud. So, we only needed to embed that deployment link on different platforms, like for websites or anything else on the mobile application. It's easy.

For deployment, in the case of MLOps, I don't require any help because it's in the process. So, from model building to deployment, I can do it on my own.

For the maintenance part, we'll only look out at how the model is performing. So that is the only part of maintenance. Another case is when whenever there will be more users come to the platform, then we have the unicorn in place so that they will take care of that scaling part.

I can do the deployment myself. We need to do regular upkeep. We can opt-in for automatic updates from Google. It depends on what cloud we use.

The deployment time is impressively quick, typically taking ten to fifteen minutes. The process involves accessing the Google Cloud Console, navigating to the appropriate product section, and creating an instance. During instance creation, selecting the right specifications, such as CPU, RAM, and the required libraries is crucial. This can be done through manual configuration or opting for a predefined environment.

We implemented this solution with our own in-house team.