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கணினி மற்றும் தொழில்நுட்ப செய்திகள் - Computer & Technical Informations / Re: AI Audio Mixer App: Questions Meet Music
« Last post by SiVa000000 on Today at 09:58:18 PM »Good and hard work effort made from FTC TEAM ROCKERZZ Really appreciated small team with friends can able to do 
Keep Rocking
Reply #5 Having questions (technical)
Few points note it my suggestion:
> Server-side rendering on the same CPU core that runs our FTC service can interfere with realtime processing. Don’t schedule heavy SSR work on the FTC core — instead offload rendering to a separate core or service (API/container), rate-limit and queue render jobs, or use ephemeral worker instances. This prevents contention and keeps FTC latency stable.
Do:
Isolate heavy SSR work to separate cores or nodes (use CPU affinity / cgroups).
Offload rendering to a dedicated service or worker pool (container, VM, or serverless API).
Use asynchronous queues and backpressure (RabbitMQ, Kafka, SQS) for render jobs.
Add rate limits, timeouts and circuit breakers to rendering calls.
Monitor CPU, latency and queue depth; trigger autoscaling before service impact.
Don’t:
Don’t run CPU-intensive SSR on the same core that handles FTC or other realtime tasks.
Don’t allow uncontrolled parallel renders that saturate system CPU.
Don’t rely only on manual restarts — automate isolation and scaling. Note:Reference for admin: this post an part of work you can remove any time with out my permission
Keep Rocking Reply #5 Having questions (technical)
Few points note it my suggestion:
> Server-side rendering on the same CPU core that runs our FTC service can interfere with realtime processing. Don’t schedule heavy SSR work on the FTC core — instead offload rendering to a separate core or service (API/container), rate-limit and queue render jobs, or use ephemeral worker instances. This prevents contention and keeps FTC latency stable.
Do:
Isolate heavy SSR work to separate cores or nodes (use CPU affinity / cgroups).
Offload rendering to a dedicated service or worker pool (container, VM, or serverless API).
Use asynchronous queues and backpressure (RabbitMQ, Kafka, SQS) for render jobs.
Add rate limits, timeouts and circuit breakers to rendering calls.
Monitor CPU, latency and queue depth; trigger autoscaling before service impact.
Don’t:
Don’t run CPU-intensive SSR on the same core that handles FTC or other realtime tasks.
Don’t allow uncontrolled parallel renders that saturate system CPU.
Don’t rely only on manual restarts — automate isolation and scaling. Note:Reference for admin: this post an part of work you can remove any time with out my permission
