How to Handle Anthropic 529 'Overloaded' Errors

A 529 from the Claude API is not your fault. It means Anthropic's servers are temporarily overloaded and shedding load. The error type is overloaded_error. Because it is transient, the correct response is a short retry with backoff, plus an optional fallback so users do not see a hard failure.

• A working Claude API integration
• A retry helper or a queue you control
• Optionally, a smaller or alternate model to fall back to

Step 1: Detect the 529 specifically

Do not lump 529 in with 4xx errors. A 400 means your request was wrong and retrying is pointless. A 529 means try again shortly. Branch on the status code so each gets the right treatment.

Step 2: Retry with exponential backoff

Wait a moment and try again, doubling the delay each time. Add jitter so a wave of clients does not all retry at the same instant and re-overload the service.

import time, random
from anthropic import Anthropic, APIStatusError

client = Anthropic()

def send(messages, attempts=4):
    for i in range(attempts):
        try:
            return client.messages.create(
                model="claude-opus-4-5", max_tokens=512, messages=messages
            )
        except APIStatusError as e:
            if e.status_code not in (429, 529) or i == attempts - 1:
                raise
            time.sleep((2 ** i) + random.random())

Step 3: Add a fallback path

If retries keep failing during a long overload, degrade gracefully. Queue the request for later, show the user a friendly retry message, or route to a smaller model that may have more capacity.

Step 4: Spread out load you control

If a batch job triggers many 529s at once, add a small delay between requests and cap concurrency. Lower steady pressure means fewer overload responses overall.

Result

After adding three retries with jitter and a queued fallback, a support bot that occasionally threw 529s during peak hours now answers every message, sometimes a few seconds late but never with an error.