Agent Swarm Infrastructure — Scalable Distributed Execution

I will build production infrastructure for your agent swarm — covering a distributed task queue for work distribution, auto-scaling agent worker pods on Kubernetes, distributed result aggregation, fault tolerance with worker failure recovery, rate limiting across the swarm for LLM API management, and comprehensive monitoring of swarm health and throughput. Agent swarms at production scale face infrastructure challenges that single-agent deployments don't — LLM API rate limits impose a ceiling on swarm concurrency that requires careful management, worker failures mid-task require partial result preservation and task reassignment, and result aggregation from thousands of concurrent workers requires distributed coordination.

The infrastructure covers Kubernetes worker pod configuration with auto-scaling, distributed task queue (Celery with Redis or SQS), partial failure recovery, distributed result aggregation, swarm-level rate limit management, and a monitoring dashboard showing queue depth, worker utilisation, and throughput.