I’m creating a Lead Generation Rasa Chatbot using the Rasa Open Source Platform. I want to deploy it on an AWS server. Can you help me determine the processing speed required by Rasa 3.1 to deploy it online? Will the bot be compatible with Rasa Open Source, or do I need to use something else?
Hello,
Rasa 3.1 Processing Speed for AWS Deployment Unfortunately, there’s no one-size-fits-all answer for the processing speed required by Rasa 3.1 on AWS. It depends on several factors:
Complexity of your bot: A bot with a simple conversation flow and limited NLP tasks will need less processing power than a complex bot with advanced features. Number of concurrent users: The more users interacting with your bot simultaneously, the more processing power you’ll need. Model size: Larger Rasa models (NLU and Dialogue) will require more resources. Here are some general recommendations:
Start with a small instance: Begin with a smaller, cost-effective AWS instance like a t2.micro or c4.large. You can always scale up later if needed. Monitor performance: Use AWS CloudWatch to monitor your instance’s CPU and memory utilization. This helps you identify bottlenecks and adjust resources if necessary. Consider serverless options: Services like AWS Lambda can be a good option for handling occasional spikes in traffic.
Yes, your Lead Generation Rasa Chatbot built with Rasa Open Source (3.1 or later) will be compatible for deployment on an AWS server. Rasa Open Source is designed to be deployed in various environments.
I hope the information may help you.
Okay, thanks a lot.