What this error means
BudgetExceededError (HTTP 429) is a LiteLLM failure pattern reported for developers trying to fix random litellm budgetexceedederror (429) when actual spend is near zero. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue #27639 on BerriAI/litellm (created 2026-05-11). Production deployment on EKS with 4 replicas, Redis cache enabled. Phantom BudgetExceededError cycles every 4 minutes. Root cause: reserve_budget_for_request() leaks Redis spend counters after upgrade. Directly impacts billing and user experience.
Common causes
- After upgrading to LiteLLM v1.83.10+, end users randomly receive HTTP 429 BudgetExceededError despite database spend being near $0. The Redis atomic counter
spend:end_user:<id>accumulates phantom reservations that are never finalized. Requests cycle between success and failure every ~4 minutes. Critical for production proxy deployments with Kubernetes. - GitHub issue #27639 on BerriAI/litellm (created 2026-05-11). Production deployment on EKS with 4 replicas, Redis cache enabled. Phantom BudgetExceededError cycles every 4 minutes. Root cause: reserve_budget_for_request() leaks Redis spend counters after upgrade. Directly impacts billing and user experience.
Quick fixes
- Confirm the exact error signature matches
BudgetExceededError (HTTP 429). - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.