AI
Once more than one team shares a company's model API budget, "please don't call the API too much" stops being a workable policy — someone needs a system that actually enforces a number. LiteLLM Proxy exists specifically for this: it's an open-source reverse proxy for LLM APIs that adds authentication, spend tracking, and budget enforcement in front of whichever providers you actually use, so the limit lives in one place instead of being re-implemented (or forgotten) in every application.
Setting up team-level budgets
1. Stand up the proxy in front of your model providers. Applications call the LiteLLM Proxy's OpenAI-compatible endpoint instead of calling OpenAI/Anthropic/Azure directly; the proxy forwards the request and tracks the cost.
2. Create a team and assign a max_budget. Using the /team/new admin endpoint, set a max_budget in USD and a budget_duration (e.g., 30d) — every key issued under that team inherits the shared limit.
3. Choose enforcement behavior per team. A hard budget rejects new requests once spend hits the ceiling; a soft budget alert can notify finance or engineering leads without blocking anyone, useful for teams still calibrating their expected usage.
# Create a team with a hard $500/month budget via the LiteLLM Proxy admin API
curl --location 'http://localhost:4000/team/new' \
--header 'Authorization: Bearer sk-admin-key' \
--header 'Content-Type: application/json' \
--data '{
"team_alias": "growth-marketing",
"max_budget": 500,
"budget_duration": "30d"
}'| Budget Type | Behavior at Limit | Best For |
|---|---|---|
| Soft budget | Sends an alert; requests still succeed | Teams still establishing a usage baseline |
Hard budget (max_budget) |
Proxy rejects further requests until the period resets | Cost centers with a firm, non-negotiable ceiling |
Centralizing spend control at the proxy layer solves a problem that per-application code can't: it works even for teams and tools you don't fully control, since every request has to pass through the same gate to reach the model provider at all. That's a meaningfully different guarantee than the code-level token counter covered elsewhere in this track, which protects a single application's own call graph rather than an entire organization's usage.
Practical Challenge
Run LiteLLM Proxy locally, create two teams with different max_budget values, and confirm that a team's requests are actually rejected once its budget is exhausted rather than merely logged.
Concept Check
Sources & Further Reading
- LiteLLM Docs: Setting Team Budgets — the official reference for the
/team/newendpoint and budget configuration used above. - LiteLLM Docs: Budgets, Rate Limits — broader coverage of user, key, and team-level budget and rate-limit options.
- LiteLLM Docs: Spend Tracking — how the proxy attributes cost per request for budget calculations.