Best Practices for Scaling GenieACS in a Large Network Deployment

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Hello everyone,

I’m currently working on a large-scale network deployment and looking to optimize our GenieACS setup for better performance and scalability. Our network consists of thousands of CPEs, and as the number of connected devices continues to grow, we want to ensure that GenieACS can handle the load efficiently.

I have a few key questions and would really appreciate insights from anyone who has experience managing large deployments with GenieACS:

  1. Hardware Recommendations: What are the recommended hardware specs (CPU, RAM, storage) for handling 10,000+ CPEs? Should we focus more on CPU performance or RAM capacity?
  2. Database Optimization: We are using MongoDB as the backend database. Are there any specific configurations or indexing strategies that have worked well for large deployments?
  3. Performance Tuning: What are the best practices for tuning GenieACS parameters (e.g., queue size, workers, etc.) to avoid bottlenecks?
  4. Load Balancing & Redundancy: Has anyone implemented a multi-instance GenieACS setup for high availability? If so, how do you distribute the workload effectively?
  5. Handling Bulk Provisioning & Firmware Updates: When pushing updates or provisioning a large number of CPEs, what strategies can help prevent overload and ensure a smooth rollout?

If anyone has experience with similar setups or can share lessons learned, I’d love to hear your thoughts. Any real-world examples or configurations that have worked well for you would be especially helpful.

I also checked this: https://forum.genieacs.com/t/best-way-to-test-cpes-tr069-implementation-with-genieacs/looker

Thanks in advance for your time and insights!

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