When file uploads are stored in S3, this means that Zulip serves as a 302 to S3. Because browsers do not cache redirects, this means that no image contents can be cached -- and upon every page load or reload, every recently-posted image must be re-fetched. This incurs extra load on the Zulip server, as well as potentially excessive bandwidth usage from S3, and on the client's connection. Switch to fetching the content from S3 in nginx, and serving the content from nginx. These have `Cache-control: private, immutable` headers set on the response, allowing browsers to cache them locally. Because nginx fetching from S3 can be slow, and requests for uploads will generally be bunched around when a message containing them are first posted, we instruct nginx to cache the contents locally. This is safe because uploaded file contents are immutable; access control is still mediated by Django. The nginx cache key is the URL without query parameters, as those parameters include a time-limited signed authentication parameter which lets nginx fetch the non-public file. This adds a number of nginx-level configuration parameters to control the caching which nginx performs, including the amount of in-memory index for he cache, the maximum storage of the cache on disk, and how long data is retained in the cache. The currently-chosen figures are reasonable for small to medium deployments. The most notable effect of this change is in allowing browsers to cache uploaded image content; however, while there will be many fewer requests, it also has an improvement on request latency. The following tests were done with a non-AWS client in SFO, a server and S3 storage in us-east-1, and with 100 requests after 10 requests of warm-up (to fill the nginx cache). The mean and standard deviation are shown. | | Redirect to S3 | Caching proxy, hot | Caching proxy, cold | | ----------------- | ------------------- | ------------------- | ------------------- | | Time in Django | 263.0 ms ± 28.3 ms | 258.0 ms ± 12.3 ms | 258.0 ms ± 12.3 ms | | Small file (842b) | 586.1 ms ± 21.1 ms | 266.1 ms ± 67.4 ms | 288.6 ms ± 17.7 ms | | Large file (660k) | 959.6 ms ± 137.9 ms | 609.5 ms ± 13.0 ms | 648.1 ms ± 43.2 ms | The hot-cache performance is faster for both large and small files, since it saves the client the time having to make a second request to a separate host. This performance improvement remains at least 100ms even if the client is on the same coast as the server. Cold nginx caches are only slightly slower than hot caches, because VPC access to S3 endpoints is extremely fast (assuming it is in the same region as the host), and nginx can pool connections to S3 and reuse them. However, all of the 648ms taken to serve a cold-cache large file is occupied in nginx, as opposed to the only 263ms which was spent in nginx when using redirects to S3. This means that to overall spend less time responding to uploaded-file requests in nginx, clients will need to find files in their local cache, and skip making an uploaded-file request, at least 60% of the time. Modeling shows a reduction in the number of client requests by about 70% - 80%. The `Content-Disposition` header logic can now also be entirely shared with the local-file codepath, as can the `url_only` path used by mobile clients. While we could provide the direct-to-S3 temporary signed URL to mobile clients, we choose to provide the served-from-Zulip signed URL, to better control caching headers on it, and greater consistency. In doing so, we adjust the salt used for the URL; since these URLs are only valid for 60s, the effect of this salt change is minimal.
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File upload backends
Zulip in production supports a couple different backends for storing files uploaded by users of the Zulip server (messages, profile pictures, organization icons, custom emoji, etc.).
The default is the LOCAL_UPLOADS_DIR
backend, which just stores
files on disk in the specified directory on the Zulip server.
Obviously, this backend doesn't work with multiple Zulip servers and
doesn't scale, but it's great for getting a Zulip server up and
running quickly. You can later migrate the uploads to S3 by
following the instructions here.
We also support an S3
backend, which uses the Python boto
library
to upload files to Amazon S3 (or an S3-compatible block storage
provider supported by the boto
library).
S3 backend configuration
Here, we document the process for configuring Zulip's S3 file upload backend. To enable this backend, you need to do the following:
-
In the AWS management console, create a new IAM account (aka API user) for your Zulip server, and two buckets in S3, one for uploaded files included in messages, and another for user avatars. You need two buckets because the "user avatars" bucket is generally configured as world-readable, whereas the "uploaded files" one is not.
-
Set
s3_key
ands3_secret_key
in /etc/zulip/zulip-secrets.conf to be the S3 access and secret keys for the IAM account. Alternately, if your Zulip server runs on an EC2 instance, set the IAM role for the EC2 instance to the role. -
Set the
S3_AUTH_UPLOADS_BUCKET
andS3_AVATAR_BUCKET
settings in/etc/zulip/settings.py
to be the names of the S3 buckets you created (e.g."exampleinc-zulip-uploads"
). -
Comment out the
LOCAL_UPLOADS_DIR
setting in/etc/zulip/settings.py
(add a#
at the start of the line). -
If you are using a non-AWS block storage provider, you need to set the
S3_ENDPOINT_URL
setting to your endpoint url (e.g."https://s3.eu-central-1.amazonaws.com"
).For certain AWS regions, you may need to set the
S3_REGION
setting to your default AWS region's code (e.g."eu-central-1"
). -
Finally, restart the Zulip server so that your settings changes take effect (
/home/zulip/deployments/current/scripts/restart-server
).
It's simplest to just do this configuration when setting up your Zulip server for production usage. Note that if you had any existing uploading files, this process does not upload them to Amazon S3; see migration instructions below for those steps.
S3 local caching
For performance reasons, Zulip stores a cache of recently served user uploads on disk locally, even though the durable storage is kept in S3. There are a number of parameters which control the size and usage of this cache, which is maintained by nginx:
s3_memory_cache_size
controls the in-memory size of the cache index; the default is 1MB, which is enough to store about 8 thousand entries.s3_disk_cache_size
controls the on-disk size of the cache contents; the default is 200MB.s3_cache_inactive_time
controls the longest amount of time an entry will be cached since last use; the default is 30 days. Since the contents of the cache are immutable, this serves only as a potential additional limit on the size of the contents on disk;s3_disk_cache_size
is expected to be the primary control for cache sizing.
These defaults are likely sufficient for small-to-medium deployments.
Large deployments, or deployments with image-heavy use cases, will
want to increase s3_disk_cache_size
, potentially to be several
gigabytes. s3_memory_cache_size
should potentially be increased,
based on estimating the number of files that the larger disk cache
will hold.
You may also wish to increase the cache sizes if the S3 storage (or S3-compatible equivalent) is not closely located to your Zulip server, as cache misses will be more expensive.
S3 bucket policy
The best way to do the S3 integration with Amazon is to create a new IAM user just for your Zulip server with limited permissions. For both the user uploads bucket and the user avatars bucket, you'll need to adjust the S3 bucket policy.
The file uploads bucket should have a policy of:
{
"Version": "2012-10-17",
"Id": "Policy1468991802320",
"Statement": [
{
"Sid": "Stmt1468991795370",
"Effect": "Allow",
"Principal": {
"AWS": "ARN_PRINCIPAL_HERE"
},
"Action": [
"s3:GetObject",
"s3:DeleteObject",
"s3:PutObject"
],
"Resource": "arn:aws:s3:::BUCKET_NAME_HERE/*"
},
{
"Sid": "Stmt1468991795371",
"Effect": "Allow",
"Principal": {
"AWS": "ARN_PRINCIPAL_HERE"
},
"Action": "s3:ListBucket",
"Resource": "arn:aws:s3:::BUCKET_NAME_HERE"
}
]
}
The file-uploads bucket should not be world-readable. See the documentation on the Zulip security model for details on the security model for uploaded files.
However, the avatars bucket is intended to be world-readable, so its policy should be:
{
"Version": "2012-10-17",
"Id": "Policy1468991802321",
"Statement": [
{
"Sid": "Stmt1468991795380",
"Effect": "Allow",
"Principal": {
"AWS": "ARN_PRINCIPAL_HERE"
},
"Action": [
"s3:GetObject",
"s3:DeleteObject",
"s3:PutObject"
],
"Resource": "arn:aws:s3:::BUCKET_NAME_HERE/*"
},
{
"Sid": "Stmt1468991795381",
"Effect": "Allow",
"Principal": {
"AWS": "ARN_PRINCIPAL_HERE"
},
"Action": "s3:ListBucket",
"Resource": "arn:aws:s3:::BUCKET_NAME_HERE"
},
{
"Sid": "Stmt1468991795382",
"Effect": "Allow",
"Principal": {
"AWS": "*"
},
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::BUCKET_NAME_HERE/*"
}
]
}
Migrating from local uploads to Amazon S3 backend
As you scale your server, you might want to migrate the uploads from your local backend to Amazon S3. Follow these instructions, step by step, to do the migration.
- First, set up the S3 backend in the settings
(all the auth stuff), but leave
LOCAL_UPLOADS_DIR
set -- the migration tool will need that value to know where to find your uploads. - Run
./manage.py transfer_uploads_to_s3
. This will upload all the files from the local uploads directory to Amazon S3. By default, this command runs on 6 parallel processes, since uploading is a latency-sensitive operation. You can control this parameter using the--processes
option. - Once the transfer script completes, disable
LOCAL_UPLOADS_DIR
, and restart your server (continuing the last few steps of the S3 backend setup instructions).
Congratulations! Your uploaded files are now migrated to S3.
Caveat: The current version of this tool does not migrate an uploaded organization avatar or logo.