Seeking Advice: Scaling Project with OpenAI, Scheduled Notifications & Multi-Backend APIs

[Cheems-arch]

Body

Hi everyone,
I’m building a project with a complex architecture:
• Multiple backend APIs (leaning towards microservices).
• OpenAI API integration. - content generation, some data analysis (the analysed data is summarized)
• Automated emails (SendGrid/Mailgun).
• Scheduled notifications in user’s local time zone.
I’m facing challenges with:
1. Scalability+ Arch: Best practices for architecture & handling dependencies? Any best practices, recommended architectures (e.g., event-driven, message queues)
2. Time Zones: Reliable solutions for scheduling notifications accurately across all backends. I’m currently exploring options like storing time zone data per user and using a library for conversions.
3. API Integration: Clean methods for managing OpenAI/email API calls, error handling, etc. (i'm using this azure for the open ai api) I have no idea how to actually go through the process and actually deploy as there are like multiple rates and stuff in there (NEED HELP), if anyone has prior experience in deploying this open ai through azure.
I’ve tried specific technologies/approaches, e.g., Celery, RabbitMQ, Django REST.
Has anyone worked on a similar project? Any advice on architecture, tech choices, or best practices is welcome! Thanks!

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