Best cloud platform to run agents

Deploying AI agents to the cloud requires understanding the different execution shapes—persistent loop, scheduled run, and event-triggered invocation—each of which corresponds to distinct cloud primitives to avoid wasted costs or missed work. The guide uses Render as an example to illustrate how to match these execution shapes to the appropriate cloud primitives, emphasizing the importance of understanding trade-offs for specific workloads. It outlines five platform-agnostic criteria for evaluating cloud platforms: execution model support, state persistence, secrets management, observability, and cost model for idle versus active time. The persistent agent pattern is described as a continuous loop suitable for real-time responsiveness, while the scheduled agent pattern is ideal for periodic tasks without low-latency needs, and the event-triggered agent pattern responds to external signals. Render Workflows offers orchestration and durable execution for multi-step tasks, providing a solution for maintaining reliability when individual steps fail. The focus is on identifying the best match between an agent's execution shape and the cloud primitive, with attention to statefulness and observability in production.

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