ApiClient creates a new httpx.AsyncClient per JWKS / OIDC fetch with no timeout and no single-flight, causing "Unknown auth error" storms under load
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 48/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Quiet
- Tech stack
- python
- Domain
- authentication, backend-api-design, performance
Research direction
Start with src/auth0_api_python/utils.py and trace ApiClient._fetch_jwks and _fetch_oidc_metadata through utils.fetch_jwks, utils.fetch_oidc_metadata, and InMemoryCache.get. Review how verify_request reaches these cache-miss paths and how httpx.AsyncClient is used. Done means JWKS and OIDC refetches avoid the reported client, timeout, and concurrent-request failure behavior without changing successful authentication semantics.
Written by the indexing model from the issue text.
Description
Checklist
- I have looked into the Readme and Examples, and have not found a suitable solution or answer.
- I have looked into the API documentation and have not found a suitable solution or answer.
- I have searched the issues and have not found a suitable solution or answer.
- I have searched the Auth0 Community forums and have not found a suitable solution or answer.
- I agree to the terms within the Auth0 Code of Conduct.
Description
ApiClient._fetch_jwks and _fetch_oidc_metadata (via
utils.fetch_jwks / utils.fetch_oidc_metadata) construct a brand-new
httpx.AsyncClient() on every cache miss with no explicit timeout
configured, and there is no single-flight protection around the
refetch path. Combined, these turn routine cache expiry into a
self-inflicted outage under any non-trivial concurrency.
Reproduction
- Stand up a FastAPI service that calls
ApiClient.verify_request
on every authenticated route. - Drive ≥ ~30 RPS of authenticated requests against it (we hit it
on a 4 vCPU ECS Fargate task during a k6 load test). - Wait for the in-memory JWKS cache to expire — by default Auth0
returnsCache-Control: max-age=600, so this happens every ~10
minutes under steady load. - Observe a sudden burst of
httpx.ConnectTimeoutchained out of
ApiClient._fetch_jwks, surfacing to callers as opaque "Unknown
auth error" 5xx responses on every authenticated route until the
herd subsides. Sentry trace shows
auth0_api_python.errors.UnknownAuth0Exception←
httpx.ConnectTimeout.
Additional context
In src/auth0_api_python/utils.py
async def fetch_jwks(jwks_uri, custom_fetch=None):
...
async with httpx.AsyncClient() as client: # 1
resp = await client.get(jwks_uri) # 2
...
- No connection pooling across calls. A fresh client is created
and torn down per fetch. Every cache miss = a fresh TCP + TLS
handshake tohttps://<tenant>.auth0.com/. Under load this
exhausts ephemeral source-port budget on the host and slows
everything else on the box. - No explicit timeout.
httpx.AsyncClient()with notimeout=
uses httpx's default 5-second connect/read/write/pool budget. On a
stressed event loop or a slow Auth0 region that 5s budget is
routinely blown, raisinghttpx.ConnectTimeout/
httpx.ReadTimeout. Those bubble up into_fetch_jwksand the
caller seesConnectTimeoutchained toUnknownAuth0Exception—
not a 401, not a 503, just an opaque "unknown auth error". - No single-flight on refetch. When the in-memory cache expires
(InMemoryCache.getreturnsNone), every concurrent request
that reaches_fetch_jwkssimultaneously fires its own outbound
JWKS fetch. N requests in flight at the moment of expiry = N
concurrent JWKS calls to Auth0. Auth0 throttles some of them, the
others time out per (1) and (2), and any request that lost the
race fails auth.
The same three problems apply verbatim to fetch_oidc_metadata and
_fetch_oidc_metadata.
auth0-api-python version
1.0.0b8
Python version
3.11
- Dominant language
- Python
- Stars
- 4
- Forks
- 9
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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