How to run an AI agent 24/7

Running an agent 24/7 turns a script into a service. The model work is the easy part; the hard part is keeping the thing alive, triggered, and affordable without you watching it. Here is what that takes and how your platform choice changes the workload.

The four requirements

1. Somewhere it stays running. A place the agent lives between tasks — a managed platform that hosts it, a long-lived server, or on-demand compute that spins up per task.
2. A way to trigger it. Agents rarely run continuously in a hot loop; they wake on schedules (cron), events (a queue message, a database change), or webhooks (an inbound HTTP call).
3. Failure recovery. Processes crash. You need automatic restarts, retries with backoff, and enough logging to see what happened.
4. Cost control. An always-on agent that calls a large model on every tick gets expensive fast. Cap concurrency, batch work, and prefer event-driven wake-ups over tight polling.

Continuous vs on-demand

There are two shapes for "24/7", and they cost very differently:

• Always-on process. The agent runs continuously and reacts immediately. Lowest latency, highest idle cost.
• On-demand / event-driven. The agent is dormant and spins up when triggered, then tears down. Near-zero idle cost, slight cold-start latency.

Most workloads want event-driven wake-ups with a small always-on listener — you pay for work, not for waiting.

How platforms divide the labour

We record a Hosting model fact on every platform dossier, because this is exactly where categories diverge:

• Managed platforms run and operate the agent for you — provisioning, uptime, and lifecycle are the platform's job. Least operational overhead. See the best platforms for running agents 24/7, which ranks by our scalability score.
• Hosting & compute infrastructure gives you the machine or sandbox; you bring the agent and own the operations. More control, more responsibility. Compare options among the best agent hosting & compute.
• Frameworks and SDKs don't run anything for you — you deploy them onto one of the above.

If you want an agent live without wiring infrastructure, a managed platform carries the most of requirements 1, 3, and 4 for you. If you need control over the runtime, hosting infrastructure is the trade.

A checklist before you go live

• Trigger chosen (schedule / event / webhook) and tested.
• Automatic restart on crash confirmed.
• Retries with backoff on transient tool/model failures.
• Structured logs you can search after the fact.
• Spend caps or alerts so a runaway loop can't surprise you.
• Memory persisted so restarts don't lose state — see long-term memory.

Next steps

• Decide where it runs: browse the platforms directory and filter on hosting model.
• Give it tools to act on: How to connect an MCP server.