Hello everyone, I'm planning to build a self-hosted AI chatbot using n8n and would appreciate your feedback on my proposed setup and whether it can handle the expected workload. Project Overview: - Core Technology: Self-hosted n8n on AWS. - Expected Workload: Approximately 400-600 messages per day. - AI Model: Gemini 2.5 Flash or 2.0 Flash (first tier). - Planned AWS Instance: I'm considering upgrading to a t4g.medium (2 vCPU, 4 GB RAM) or a c6d.large. I'm looking for advice on which would be more suitable. My Proposed Workflow is as follows: 1. A webhook receives an incoming message. 2. The message is passed to an n8n AI agent powered by Gemini. 3. This agent will have simple memory capabilities and access to a company database for context-aware responses. 4. A code node will then be used to clean and format the AI's output. 5. Finally, the cleaned response will be sent back via the webhook. Future Enhancements: I also plan to implement a system to set usage limits for users to prevent spam and abuse which will add some node . My Questions: 1. Can a self-hosted n8n instance on an AWS server, such as a t4g.medium, comfortably handle 400-600 messages per day with this workflow? 2. Is the t4g.medium a good choice, or would the c6d.large be significantly better for this use case? 3. Are there any real-world examples of companies successfully using a self-hosted n8n setup for their AI chatbots? I'm open to any suggestions or best practices you might have. Thanks in advance for your help!

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