SAM Doctor

ERROR REFERENCE

ReservedConcurrentExecutions below the account minimum

Setting ReservedConcurrentExecutions on a function would leave the account with less than its minimum unreserved concurrency (usually 100). This is an account-wide ceiling, not a problem with this function's template or permissions - and it is especially common on a fresh account, where the concurrency limit can still be at the 1,000 default, or lower in a new or burst-limited account, sometimes as low as 10-50, where no reservation is possible at all.

WHAT IT MEANS

What this error means

AWS Lambda always keeps a minimum amount of unreserved concurrency available in an account, so that functions with no reservation of their own are never starved out by functions that reserved everything. The account's total concurrency limit minus every function's ReservedConcurrentExecutions must stay at or above that minimum. Reserving concurrency for one function can push the account below the floor even when that function's own reservation looks reasonable in isolation.

FIX

How to fix it

  1. Read the account's concurrency limit (read-only): 
    aws lambda get-account-settings \
  --query 'AccountLimit.[ConcurrentExecutions,UnreservedConcurrentExecutions]'
  2. Sum existing reservations across the account - not just this template: 
    aws lambda list-functions \
  --query 'Functions[?ReservedConcurrentExecutions!=`null`].[FunctionName,ReservedConcurrentExecutions]'
  3. Lower or remove the reservation in the template so the account keeps at least the minimum unreserved, or:
  4. Request a concurrency quota increase for the account through Service Quotas when the reservation is genuinely needed and the account limit is the real constraint.

AUTOMATE THE TRIAGE

Diagnose this automatically

SAM Doctor recognizes the reserved-concurrency wording (high confidence) and keeps it distinct from other InvalidParameterValueException messages that share the same exception name for an unrelated reason. Runs locally; no AWS access, no log upload. 

python -m pip install sam-doctor
sam-doctor diagnose deployment.log --format markdown

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