firebase-functions-python
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Container silently freezes on making a request to firestore if multiple requests were created before container starts
Context
We've noticed this issue on our production and dev environments in Firebase, and launched an investigation together with GCP support (Support Case 49715474). GCP acknowledged the strange behaviour, but they were eventually unhelpful, offering generic advice on how it can be partially mitigated, which does not work in our use case, and it doesn't solve the issue. I continued the investigation on my own, and I think I pinned down the cause.
The issue seems to be rather generic and in my opinion very serious (silent failure -> no recovery until container goes out of scope), and happens for at least 1 use case which I presume is common in Firebase Functions: reading a document in Firestore using firebase_admin
library (and hence google-cloud-firestore
client). In my view it renders Firebase Functions for Python near-unusable if one needs to do operations on the firestore.
I decided to raise an issue here in an attempt to get some clarity, perhaps I am missing something. Please bear with me, as reproducing it takes a bit of a set up. Due to long feedback cycles (needing to deploy the function for every code change) and I am only reporting my particular use case, but I would be surprised that the issue is isolated only to google-cloud-firestore
client.
I'd be very grateful for any suggestions to solve or mitigate this issue in the meanwhile, as we've completely blocked on that right now.
I have raised a twin issue on firebase-admin-python
as it concerns also that library: https://github.com/firebase/firebase-admin-python/issues/774
Description
- In the even of cold start, Python function is silently freezing on an attempt to read a document in firestore (
firestore.client().document.get()
) if multiple invocations were requested in a short period of time (in my tests I used as low as 5 invocations submitted as quickly as possible). - Further attempts to invoke the function do not produce any result.
This behaviour is observed in both http-triggered functions and firestore-triggered functions.
Reproduction
Environment
Standard Firebase Functions for Python setup, as suggested by the official documentation.
Here I provide minimal code to reproduce the behaviour. I provide the code for http-triggered function, as it is easier to test (for firestore-triggered need to get service key to write to db, etc; but the behavior is exactly the same).
firebase.json
...
"functions": [{
"source": "functions-python",
"codebase": "functions-python",
"ignore": ["venv", ".git", "firebase-debug.log", "firebase-debug.*.log"],
"runtime": "python311"
}],
...
functions-python/requirements.txt
firebase_functions==0.2.0
functions-python/main.py
(I added print statements before every code line so that it is apparent where the function freezes)
from firebase_admin import firestore, initialize_app
from firebase_functions import https_fn, options
initialize_app()
counter = 0
# note that defining firestore client inside or outside the function doesn't make any difference, I tried both
print("firestore.client()")
db = firestore.client()
@https_fn.on_request(
cors=options.CorsOptions(
cors_origins=["*"],
cors_methods=["get", "post"],
)
)
def http_trig_read_fs_l(req: https_fn.Request) -> https_fn.Response:
print("global counter")
global counter
print("db.collection('test')")
col = db.collection("test")
print("col.document('testDoc')")
doc = col.document("testDoc")
print("doc.get()")
get = doc.get()
print("get.to_dict()")
data_dict = get.to_dict()
print("counter += 1")
counter += 1
print("counter", counter, "data", data_dict)
return https_fn.Response(f"counter {counter} data {data_dict}")
Then I deploy the function to a Firebase Project (with Blaze plan).
npx firebase-tools --version
12.5.3
npx firebase-tools deploy --only functions:functions-python
Additional setup:
- In Firestore, create a collection "test" with document "testDoc" (and any content, e.g. {"test" : "test"}). I did it manually through Firebase Console. However, in reality this is not necessary, as the issue is reproducible even without it.
- In Cloud Run -> open Function -> Security -> Allow unauthenticated invocations
Reproduction and results
I use hey to generate requests.
hey -n 10 -c 10 https://http-trig-read-fs-l-<...>.a.run.app
Summary:
Total: 20.0057 secs
Slowest: 0.0000 secs
Fastest: 0.0000 secs
Average: NaN secs
Requests/sec: 0.4999
Response time histogram:
Latency distribution:
Details (average, fastest, slowest):
DNS+dialup: NaN secs, 0.0000 secs, 0.0000 secs
DNS-lookup: NaN secs, 0.0000 secs, 0.0000 secs
req write: NaN secs, 0.0000 secs, 0.0000 secs
resp wait: NaN secs, 0.0000 secs, 0.0000 secs
resp read: NaN secs, 0.0000 secs, 0.0000 secs
Status code distribution:
Error distribution:
[10] Get "https://http-trig-read-fs-l-<...>-uc.a.run.app": context deadline exceeded (Client.Timeout exceeded while awaiting headers)
As you can see, the endpoint is unresponsive. In the Cloud Run logs we can see the issue (I am posing the end of the log, there are no further log statements in response to this run:
The container becomes completely unresponsive, and functions run until they time out (can be seen in Cloud Run metrics -- run times just above 1 minute is when I did one of the load tests):
However, if after the container goes out of score, or the function is redeployed to renew the container revision, I first try to make a single request to "wake up" the container, it can then process very high loads.
hey -n 1 -c 1 https://http-trig-read-fs-l-<...>-uc.a.run.app
Summary:
Total: 0.6506 secs
Slowest: 0.6505 secs
Fastest: 0.6505 secs
Average: 0.6505 secs
Requests/sec: 1.5372
....
Status code distribution:
[200] 1 responses
hey -n 100 -c 100 https://http-trig-read-fs-l-<...>-uc.a.run.app
Summary:
Total: 1.9869 secs
Slowest: 1.9861 secs
Fastest: 0.4788 secs
Average: 1.2266 secs
Requests/sec: 50.3297
...
Status code distribution:
[200] 100 responses
Conclusion
The current issue seems extremely impactful for a very common use case, as it leads to silent failure on the backend and the backend becoming unresponsive for a long period of time. It is also quite difficult to catch and trace, as it depends on the cold / warm starts. We've seen our backend fail for weeks from time to time without any apparent cause, until we were able to pin down this issue. GCP support is not helpful in debugging or fixing the issue.
At this point, the only viable paths forward we see are to rewrite out backend in Node functions (which might not have this issue, but I am yet to test), or to move another tech stack migrating from Firebase completely.
Same issue. Until this gets fixed, to avoid the timeout errors I had to set the minimum number of instances to 1 (which incurs an additional cost with GCP).
@https_fn.on_request(
min_instances=1,
cors=options.CorsOptions(
cors_origins=["*"],
cors_methods=["get", "post"],
)
)
Also, the timeouts were commonly associated with with various internet bots invoking the functions, with several requests being generated during a cold start before the first request could be fulfilled. So, @antopolskiy's analysis and use of hey to generate a small load is accurate and essential to recreate the problem.
I suspect this is due to the issue described in https://github.com/grpc/grpc/issues/36265 (grpcio is a dependency of google-cloud-firestore). https://github.com/grpc/grpc/pull/36266 fixes this, but I suspect it won't be available until the next release of grpcio library (1.63.0).
Pinning grpcio==1.58.0 in my requirements.txt fixed the issue in my reproduction.