LiteLLM / LiteLLM

LiteLLM deployment-level TPM enforcement is per-pod, not cross-pod — effective limit scaled by replica count

Fix LiteLLM proxy TPM enforcement to be cluster-wide across all pods rather than per-instance; prevent quota bypass through horizontal scaling Includes evidence for LiteLLM troubleshooting demand.

Source-backed Last updated May 19, 2026 1 source Needs local verification

Category: LiteLLM
Error signature: tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls
Quick fix: Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.
Updated: May 19, 2026
Verification status: Source-backed
Evidence: 1 public source URL

Before you change production

This page includes public source URLs in the imported troubleshooting record. Compare those references with your version and environment before applying changes.

Reproduce the smallest failing action and save non-secret logs before changing configuration.
Check versions for LiteLLM, related SDKs, package managers, CI runners, and hosting providers.
Change one setting or dependency at a time, then rerun the same failing command or request.
Avoid destructive commands, credential rotation, billing changes, or security relaxations without a rollback plan.

What this error means

tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls is a LiteLLM failure pattern reported for developers trying to fix litellm proxy tpm enforcement to be cluster-wide across all pods rather than per-instance; prevent quota bypass through horizontal scaling. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub Issue #27736 on BerriAI/litellm opened May 12, 2026. Proxy deployment issue directly impacts billing/revenue when clients are supposed to be rate-limited but scale past intended limits. Tags: bug, proxy. Mapping: LiteLLM proxy rate-limiting → LiteLLM (approved category).

Common causes

GitHub Issue #27736 on BerriAI/litellm opened May 12, 2026. Proxy deployment issue directly impacts billing/revenue when clients are supposed to be rate-limited but scale past intended limits. Tags: bug, proxy. Mapping: LiteLLM proxy rate-limiting → LiteLLM (approved category).

Quick fixes

Confirm the exact error signature matches tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls.
Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.

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.

Diagnostic flow for this page

Match tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls exactly before applying the quick fix.
Compare the failing environment with LiteLLM versions, account scope, provider settings, and deployment context.
Check the listed common causes in order, starting with the cause that best matches your logs.
Use the evidence status below to decide whether to confirm against public sources or official documentation.
Apply one reversible change, rerun the smallest failing action, and keep rollback notes.

FAQ

What does tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls mean in LiteLLM?

tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls indicates the workflow described by "LiteLLM deployment-level TPM enforcement is per-pod, not cross-pod — effective limit scaled by replica count" failed in a LiteLLM context. Start by confirming the exact signature and the component that emitted it.

What should I check first for tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls?

Check whether this cause matches your environment: GitHub Issue #27736 on BerriAI/litellm opened May 12, 2026. Proxy deployment issue directly impacts billing/revenue when clients are supposed to be rate-limited but scale past intended limits. Tags: bug, proxy. Mapping: LiteLLM proxy rate-limiting → LiteLLM (approved category).

Is the tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls guidance source-backed?

The "LiteLLM deployment-level TPM enforcement is per-pod, not cross-pod — effective limit scaled by replica count" page is labeled source-backed. It has 1 public source URL from github.com, so use that evidence status when deciding how much additional verification you need.

When should I avoid the quick fix for tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls?

For "LiteLLM deployment-level TPM enforcement is per-pod, not cross-pod — effective limit scaled by replica count", avoid applying "Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests." when the error text differs, the affected version or provider is different, or the change would touch credentials, billing, DNS, production deploy settings, or irreversible data.

What should I collect before debugging tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls?

For "LiteLLM deployment-level TPM enforcement is per-pod, not cross-pod — effective limit scaled by replica count", collect the failing LiteLLM command or request, non-secret configuration, versions, timestamps, request IDs when available, and the smallest reproduction that still triggers the signature.