I am aware of the pros and cons of deploying rasa assistant in production using Docker compose, k3s and k8s thanks to this detailed blog post.
Now, I am curious how
deploying in an EC2 instance by imitating the methodology used in local installation would fair.
What I am suggesting is:
- Create a python environment inside the instance
- Pip install rasa and rasa X
- Move the folder containing code there from local and train a model.
- Open 5005 port of the instance and access it from API gateway.
- Similarly, access rasa X in the browser
- Attach a load balancer for traffic distribution across multiple identical instances.
To my understanding, it will make the deployment much easier. I am specifically interested in knowing cons of using this strategy. Thank you