How I cut my OpenAI Agent latency by replacing cloud sandboxes with a local microVM

Source: Dev.to

Introduction

A few days ago I was building a coding agent using the new OpenAI Agents SDK. I plugged in one of the official cloud sandboxes (they’re all generally good). The agent worked, but it felt incredibly sluggish.

The logs showed the agent averaging about 15 tool calls per task. Because the sandbox was hosted in the cloud, the physical path looked like this:

My Agent Runtime → Internet → Cloud Sandbox → MicroVM → Internet → My Agent Runtime

Every exec_command required two round trips across the public internet—30 network hops per task. The provider advertised a “90 ms cold start,” but the constant RTT overhead on every tool call was killing the UX.

I tried the SDK’s default local option (bubblewrap on Linux). It was fast, but it relies on process‑level syscall filters, and running untrusted LLM‑generated code directly on the host kernel felt risky.

Finding the middle ground: BoxLite

I wanted the hardware isolation of a cloud VM with the zero‑latency of a local process. I discovered BoxLite – essentially the SQLite of sandboxing. It’s an embedded microVM that uses KVM (Linux) or Hypervisor.framework (macOS) to spin up a dedicated guest kernel right on your machine.

BoxLite has no daemons to configure, no Docker sockets, and no root access required. Install it with a single pip command:

pip install boxlite-openai-agents

The 1‑Line Swap

I didn’t need to rewrite my agent logic; I only changed the sandbox client in the RunConfig:

from boxlite_openai_agents import BoxLiteSandboxClient, BoxLiteSandboxClientOptions

# ... agent setup ...

await Runner.run(
    agent,
    "Write fizzbuzz.py for n=15 and run it.",
    run_config=RunConfig(
        sandbox=SandboxRunConfig(
            client=BoxLiteSandboxClient(),  # <-- Changed this line
            options=BoxLiteSandboxClientOptions(
                image="python:3.12-slim"
            ),
        ),
    ),
)

The Result

Latency dropped immediately. Because the microVM runs in the same process as the agent runtime, the internet hops went from 30 down to zero—communication is now microsecond‑level IPC.

Additionally, BoxLite uses QCOW2 snapshots, so I no longer have to reinstall packages like pandas for every session. I can snapshot the VM state and resume it the next day in under a second.

If you’re building coding agents on your laptop and are tired of cloud latency and timeouts, give local microVMs a try. It completely changed my workflow.