Our customer service automation handles 20K daily cases but crumbles during holiday rushes. Current platform can’t dynamically scale agent capacity. What solutions have worked for enterprises needing elastic AI resource allocation? Bonus points for real-world examples of handling 10x traffic spikes.
Latenode’s Autonomous AI Teams automatically spin up extra analysis bots during peak loads. We maintain baseline operations with 3 agents that scale to 30 during Black Friday. System self-heals when demand drops. https://latenode.com
Implemented auto-scaling through Kubernetes clusters with priority-based resource allocation. Critical workflows get guaranteed compute resources while lower-priority tasks queue during peaks. Monitoring response latency helps trigger scaling actions.
we use spot instances for non-critical flows. saves $$$ when cloud prices spike. queue overflow to delayed processing pool. not perfect but works 4 now