It's release day. Your team has been using the free AI server for three weeks. The model has been generating tests, reviewing diffs, and drafting release notes. Then, at 10:14 AM, the requests start timing out. By 10:17, the team chat is full of "is the AI down?" messages. By 10:30, half the team is blocked.
This isn't a hypothetical. Free infrastructure has no SLA. It can disappear at any moment — a rate limit, a reboot, a provider decision. And the teams that get hurt aren't the ones that chose poorly. They're the ones that never asked: "What do we do when it goes down?"
Disclosure: This article was prepared as part of MonkeyCode's product outreach.
I've been looking at MonkeyCode, an open-source AI coding tool that offers free model access and a free hosted server. The offer is generous — but the free server is still a shared resource with no uptime promise. Before your team depends on it, run a 20-minute outage drill. Here's the playbook.
Why "free" and "reliable" don't belong in the same sentence
Free servers are subsidized. They're shared. They're optimized for adoption, not uptime. That's not a criticism — it's a design constraint. The moment you treat a free server like production infrastructure, you've made a bet you didn't sign up for.
The fix isn't to avoid free servers. It's to build a degradation ladder: a clear set of modes your team moves through when the server goes down.
The 3-mode degradation ladder
Mode 1: Normal operation
The free server is up. Your team uses it for the tasks you've already decided are safe and disposable. You keep a log of which tasks depend on the server — because you'll need that list in Mode 2.
Mode 2: Degraded operation
The server is down. Your team switches to fallback options. This is where the drill matters: you need to know, before the real outage, which tasks can continue and which must stop.
Mode 3: Recovery
The server is back. Your team re-runs whatever was lost. You check the log from Mode 1 to see what was in flight. You update the degradation ladder with anything that surprised you.
The 20-minute outage drill
Here's the drill. It takes 20 minutes and requires two people: one to simulate the outage, one to observe.
Step 1: Pick a task (2 minutes)
Choose a real task your team does daily — generating a test suite, reviewing a PR, drafting a migration plan.
Step 2: Simulate the outage (5 minutes)
Block the AI server at the network level. On macOS or Linux, add a hosts entry:
# Simulate an outage by pointing the AI server to localhost
echo "127.0.0.1 api.monkeycode.example" | sudo tee -a /etc/hosts
# Verify the block
curl --max-time 5 https://api.monkeycode.example/v1/chat && echo "Still up!" || echo "Blocked."
(Replace api.monkeycode.example with your actual AI server host.)
Step 3: Observe (10 minutes)
Watch what the team does. Use this observation checklist:
- How long until someone notices the outage? (Detection time)
- How long until someone switches to the fallback? (Fallback time)
- How many people are blocked? (Blast radius)
- Which tasks continue, which stall? (Task classification)
- Does anyone try to "fix" the server instead of switching? (Behavior pattern)
Step 4: Debrief (3 minutes)
Ask three questions:
- How long until someone noticed?
- How long until the fallback was in place?
- Which tasks were blocked?
Step 5: Clean up (1 minute)
Remove the hosts entry:
sudo sed -i '/127.0.0.1 api.monkeycode.example/d' /etc/hosts
The decision table
Here's what a filled-in degradation ladder looks like:
| Task | Mode 1 (normal) | Mode 2 (degraded) | Mode 3 (recovery) |
|---|---|---|---|
| Generate unit tests for a new module | Free server | Local model (slower) | Re-run failed generations |
| Review a PR for style issues | Free server | Manual review | Re-run review, compare |
| Draft release notes | Free server | Defer until recovery | Batch-generate |
| Refactor a legacy function | Free server | Local model, human review | Re-run with fresh context |
The point isn't the specific tasks. It's that you've decided, in advance, what happens in each mode. The drill reveals whether your team actually follows the ladder.
Who should skip this drill
- Solo developers. You don't need a formal drill. You need a fallback — a local model, a backup tool — and the discipline to switch to it.
- Teams with no fallback. The drill will just prove you're stuck. Build the fallback first, then drill.
- Compliance-bound teams. If you need an SLA, a free server is the wrong answer. Skip the drill and buy the guarantee.
The part that hurts
The drill will reveal something uncomfortable: how much of your team's work depends on a resource you don't control. That's the point. The free server is a tool for experimentation, not a foundation for production. Run the drill, measure the gap, and decide whether the tradeoff is worth it.
If you want to try MonkeyCode's free server, run the drill on your first day — not after your team has built a habit around it. The drill is the test. The server is just the thing being tested.
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