boto / botocore

The low-level, core functionality of boto3 and the AWS CLI.

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Performance issue due to SSLContext being recreated over and over

mm-matthias opened this issue · comments

Describe the bug

botocore request/response times are much slower than expected in certain scenarios due to unexpected SSL overhead.

Expected Behavior

botocore /boto3 performs fast for all requests.

Ideally the first request does not take longer than any following requests (e.g. the SSLContext could be initialized during module init or be triggered by the user of the library in some way before any requests happen).

Current Behavior

Request/responses are too slow, see below.

Reproduction Steps

botocore performance is much slower than expected in certain scenarios. This can easily be reproduced by

import boto3
import time

session = boto3.session.Session()
for i in range(10):
    start = time.time()
    session.resource("s3").Object("mybucket", "mykey").get()["Body"].read()
    print(time.time() - start)

which yields

0.4858591556549072
0.1862480640411377
0.20270681381225586
0.22403812408447266
0.19844722747802734
0.18699288368225098
0.17718195915222168
0.18413686752319336
0.1918637752532959
0.18160700798034668

This can be optimized by sharing the resource between iterations:

import boto3
import time

session = boto3.session.Session()
resource = session.resource("s3")
for i in range(10):
    start = time.time()
    resource.Object("mybucket", "mykey").get()["Body"].read()
    print(time.time() - start)

which yields

0.25886106491088867
0.05055093765258789
0.050694942474365234
0.05214500427246094
0.05020618438720703
0.05117917060852051
0.04602789878845215
0.048911094665527344
0.048056840896606445
0.04799509048461914

One can see that the initial request is always quite slow.

But the issue goes further. If there is some delay between requests all the requests get slow. This can be reproduced with:

import boto3
import time

session = boto3.session.Session()
resource = session.resource("s3")

for i in range(10):
    start = time.time()
    resource.Object("mybucket", "mykey").get()["Body"].read()
    print(time.time() - start)
    time.sleep(10)

This yields

0.22714900970458984
0.17821383476257324
0.21504521369934082
0.17998909950256348
0.2338550090789795
0.19853711128234863
0.23908185958862305

Switching to sleep(5) yields fast requests again (except for the first one).

The reason for the slowness is that

  • the http keep-alive timeout that botocore uses implicitly via urllib3 seems to be rather low (probably between 5 and 10 seconds) and there doesn't seem to be a straightforward way to increase it. This causes an increased number of connection creations and ssl handshakes the as well as the issue mentioned in the next point.
    • enabling debug logging for urllib3 suggests that is_connection_dropped returns True for the connections that are issue after a sleep(10). So presumably something (the s3 server?) closed the connection. In this case there might not be a lot of things that botocore could do, except for the next point about making SSL connection creation faster.
  • initializing SSL connections has become a lot slower in recent python versions, see python/cpython#95031 . Other major libraries like requests are also affected, see psf/requests#6667 .
    The slow requests are slow, because load_verify_locations is called once for each of them. This happens through the urllib3 PoolManager/HTTPConnectionPool and the recreation of SSLContext.
    You can verify this by running any of the above reproducers in a profiler and look at the number of calls to/time spent in load_verify_locations.
  • The problem is even exacerbated when using a proxy as this leads to even more SSL calls. Adding different hosts to this makes the problem even worse as this leads to more HTTPConnectionPools being created.

Possible Solution

  • The solution for the http keep-alive timeout is to make this configurable somehow so that more requests can benefit from connection pooling.
  • The solution to avoid the overhead from load_verify_locations is probably to share the SSLContext across multiple invocations/threads. The requests issue I've mentioned above has a proposed workaround.

Additional Information/Context

No response

SDK version used

1.34.98

Environment details (OS name and version, etc.)

MacOS & Linux
Python 3.12.3

Thanks for reporting this issue — after discussing with the team we decided that we should continue tracking this for further review and investigation.