Why AI Agents Need Sleep/Wake Architecture

Running AI agents in production is expensive. Not because the compute is inherently costly, but because the traditional deployment model is fundamentally wasteful.

The Always-On Problem

When you deploy an AI agent on a standard cloud VM or container, you're paying for 24/7 uptime. But most agents aren't processing requests around the clock. A customer support agent might handle 50 queries a day. A data analysis agent might run once every few hours. A monitoring agent checks in every 15 minutes.

That means you're paying for hours of idle time between each invocation. At $50-100/month per container, the math doesn't work — especially when you're running multiple agents.

What is Sleep/Wake Architecture?

Sleep/wake is a deployment pattern where your agent is suspended to cold storage when idle, then restored to a warm state when triggered. Think of it like serverless functions, but for stateful AI agents.

Here's what happens under the hood:

1. Request arrives — A webhook, cron trigger, or API call hits your agent's endpoint
2. Wake — The agent container is restored from a checkpoint in under 2 seconds
3. Process — Your agent handles the request with full state and memory intact
4. Sleep — After a configurable idle timeout, the agent is checkpointed and suspended

The key insight is that agent state (conversation history, embeddings, tool configurations) is preserved across sleep cycles. Your agent doesn't start from scratch each time.

The Economics

Let's compare costs for a typical agent that handles ~100 invocations per day, each lasting about 30 seconds:

The difference is stark. With sleep/wake, you're only paying for actual compute time — roughly 50 minutes per day instead of 1,440 minutes.

When Always-On Makes Sense

Sleep/wake isn't for every use case. If your agent needs sub-100ms response times or handles hundreds of concurrent requests, always-on infrastructure is the right call. Maritime offers an Always-On tier for exactly this reason.

But for the vast majority of AI agents — the ones that respond to webhooks, run on schedules, or handle moderate traffic — sleep/wake is the economically rational choice.

Getting Started

Maritime handles the sleep/wake lifecycle automatically. Push your agent code, configure your triggers, and the platform manages the rest. No infrastructure changes, no custom orchestration, no cold-start optimization.

maritime deploy --tier smart ./my-agent

Your agent gets a dedicated API endpoint, sleeps when idle, and wakes in under 2 seconds when called. That's it.