Rclone 1.53.3 memory (leak?) problem

What is the problem you are having with rclone?

I use rclone to backup (rclone sync) my docker volume for gitlab on azureblob storage. I also use docker to run rclone (using the official rclone/rclone image). I limit the rclone docker container memory to 500 mb.

This was working fine with version 1.52.3, memory would be stable at around 360 MB for many hours. When I update to rclone 1.53.3 it runs out of memory after a few minutes (between 2 and 4 minutes).

What is your rclone version (output from rclone version)


Which OS you are using and how many bits (eg Windows 7, 64 bit)

official docker container on centos 7.9

Which cloud storage system are you using? (eg Google Drive)


The command you were trying to run (eg rclone copy /tmp remote:tmp)

rclone sync --bwlimit=10M --azureblob-chunk-size 10M --links --create-empty-src-dirs --retries 1 --ignore-errors --delete-during --progress -v --log-file=$LOG_FILE $AZUREBLOB_BACKUP_SOURCE $$AZUREBLOB_BACKUP_DESTINATION

The rclone config contents with secrets removed.

The config file is created just before the sync is run using the following command

rclone config create azureblob azureblob type azureblob account $AZUREBLOB_ACCOUNT key $AZUREBLOB_KEY config_is_local false config_refresh_token false

A log from the command with the -vv flag

I cannot see anything interesting so here are the first few lines.

 "--delete-during" "--progress" "-vv" "--log-file=/logs/rclone.log" "/volumes" "azureblob:/backup-sc01-trt-test-2020-11-25"]
2020/11/25 14:00:47 DEBUG : Creating backend with remote "/volumes"
2020/11/25 14:00:47 DEBUG : Using config file from "/config/rclone/rclone.conf"
2020/11/25 14:00:47 INFO  : Starting bandwidth limiter at 10MBytes/s
2020/11/25 14:00:47 DEBUG : Creating backend with remote "azureblob:/backup-sc01-trt-test-2020-11-25"
2020/11/25 14:00:47 DEBUG : fs cache: renaming cache item "azureblob:/backup-sc01-trt-test-2020-11-25" to be canonical "azureblob:backup-sc01-trt-test-2020-11-25"
2020/11/25 14:00:47 DEBUG : Waiting for deletions to finish
2020/11/25 14:00:48 INFO  : rclone.log: Deleted

then a lot of skipping of existing files:

2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005dd32ca50895b354.s: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005dd32ca50895b354.s: Unchanged skipping
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005ddd0cdd1faa1634.s: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005ddd0cdd1faa1634.s: Unchanged skipping
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005de8ea5e1aa73ff4.s: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005de8ea5e1aa73ff4.s: Unchanged skipping
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e24558e1412a624.s: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e24558e1412a624.s: Unchanged skipping
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e51311320a1997c.u: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e51311320a1997c.u: Unchanged skipping
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e52829327c69ff4.s: Size and modification time the same (differ by 0s, within tolerance 1ns)
2020/11/25 14:00:49 DEBUG : gitlab_logs/grafana/@400000005e52829327c69ff4.s: Unchanged skipping

Then it is sending files until it crashes, with the -vv options it only takes a few seconds before it crashes. These are the last lines in the log file:

2020/11/25 14:01:14 DEBUG : gitlab_data/prometheus/data/28/ef6d8f5a0c673d.db: MD5 = 63a1b8e03b7bc15706ba122e0502ee2c OK
2020/11/25 14:01:14 INFO  : gitlab_data/prometheus/data/28/ef6d8f5a0c673d.db: Copied (new)
2020/11/25 14:01:14 DEBUG : gitlab_data/prometheus/data/28/f53ec267f2ed75.db: MD5 = 2e24681a8cb87f824176e62d0a457807 OK
2020/11/25 14:01:14 INFO  : gitlab_data/prometheus/data/28/f53ec267f2ed75.db: Copied (new)
2020/11/25 14:01:14 DEBUG : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_18/48429/67894/job.log: MD5 = 4969e00fd6e50230da06fd15d74f5e47 OK
2020/11/25 14:01:14 INFO  : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_18/48429/67894/job.log: Copied (new)
2020/11/25 14:01:14 DEBUG : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_07/46941/65967/job.log: MD5 = 0e24d8e2ec637e239a9f22a4e3efc743 OK
2020/11/25 14:01:14 INFO  : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_07/46941/65967/job.log: Copied (new)
2020/11/25 14:01:14 DEBUG : gitlab_data/gitlab-rails/shared/lfs-objects/1a/ad/4150f7141b6a7c87633372aa1b4620f478b30b66a61584a5956a28ccd2f5: MD5 = 06bed324dbed803568bd76dd45b48ba6 OK
2020/11/25 14:01:14 INFO  : gitlab_data/gitlab-rails/shared/lfs-objects/1a/ad/4150f7141b6a7c87633372aa1b4620f478b30b66a61584a5956a28ccd2f5: Copied (new)
2020/11/25 14:01:15 DEBUG : gitlab_data/gitlab-rails/shared/artifacts/21/6d/216da54b5931a6d37cca8e29953361fe02c680bbd8b482343f508e32e8e9cc3b/2019_09_04/21258/25787/job.log: MD5 = 4943fe6d52c48a6e61577f42203df9e5 OK
2020/11/25 14:01:15 INFO  : gitlab_data/gitlab-rails/shared/artifacts/21/6d/216da54b5931a6d37cca8e29953361fe02c680bbd8b482343f508e32e8e9cc3b/2019_09_04/21258/25787/job.log: Copied (new)
2020/11/25 14:01:15 DEBUG : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_13/47711/66998/job.log: MD5 = ac308e9bcf5672fd8af25c4c51c5b4ba OK
2020/11/25 14:01:15 INFO  : gitlab_data/gitlab-rails/shared/artifacts/1f/f7/1ff7b91c979ea344298826c212adf745783ae8a14a3eded36d56ba1b0f4bdeee/2020_02_13/47711/66998/job.log: Copied (new)
2020/11/25 14:01:15 DEBUG : gitlab_data/gitlab-rails/shared/lfs-objects/1e/81/638215e29c6e68acd0f50884abe33cc26d3b2cb269f618c0597146d7771f: MD5 = f13b0028a60d2da4bea2d8a944944519 OK
2020/11/25 14:01:15 INFO  : gitlab_data/gitlab-rails/shared/lfs-objects/1e/81/638215e29c6e68acd0f50884abe33cc26d3b2cb269f618c0597146d7771f: Copied (new)
2020/11/25 14:01:15 DEBUG : gitlab_data/gitlab-rails/shared/artifacts/20/9e/209eb5f20ab018ff6f1e42b98e5b57921aa4e2b7a7b683de32458b7153720a28/2019_01_17/2030/1950/job.log: MD5 = 6293774f59afd8ce2df3224579d26ae0 OK
2020/11/25 14:01:15 INFO  : gitlab_data/gitlab-rails/shared/artifacts/20/9e/209eb5f20ab018ff6f1e42b98e5b57921aa4e2b7a7b683de32458b7153720a28/2019_01_17/2030/1950/job.log: Copied (new)

You'd probably want to uncap it and get a profile of before with the old version and a profile of the new version.

There are no (significant) changes in the azureblob backend between those two versions.

I suspect that it might be a go runtime thing as 1.53.3 was compiled with go1.15.5 whereas 1.52.3 was compiled with go1.14.7

One thing you could try is --azureblob-memory-pool-use-mmap (or the config file equivalent) which will probably help with memory use.

I suspect the memory is just tipping over the edge for some reason, but a profile would be great if you can manage it.


I have uncapped the docker container and created a profile with the old version, the new version and also the new version using the --azureblob-memory-pool-use-mmap flag.

I have also done a cpuprofile if that can be of any help.

It does not look like --azureblob-memory-pool-use-mmap helped at all.

Let me know if you need me to try something else.

That was very interesting - thank you.

None of the profiles show rclone using a huge amount of ram.

For 1.53.3 memprofile it shows rclone using 53.51MB of RAM.

How much did the OS show it using?

If it is a lot more then maybe we need to run the garbage collector more often. This will use a bit more CPU but less RAM hopefully. You could try this

export GOGC=20

It appears that the RAM is nearly all allocated here

Which is

  1. in the azureblob SDK
  2. part of a sync.Pool

1 means it isn't in the rclone code directly. I didn't see an open or closed issue on the AzureBlob Go SDK repository though.

sync.Pool is notorious for memory leak problems. Setting GOGC should help with this.

It might also be worth trying the latest beta which has a later version of the SDK to see if that is any different.

With 1.53.3 docker stats showed the container was taking about 1.4 GB or RAM, as I said with 500 MB memory limit rclone would crash within minutes.

With GOGC=20 docker stats shows the container is stable at about 200 MB, so you seem to have found the problem.

I can try the latest beta later and let you know.
(the docker container has a beta tag, I assume I can simply use that)

With the latest beta it is the same, memory rises rapidly to about 1.4 GB

OK just wanted to double check.


That means that the azureblob SDK is generating a lot of garbage. If not collected quick enough it causes memory fragmentation and then the kind of problem you see.

Thanks for testing that.

I made an upstream issue here: https://github.com/Azure/azure-storage-blob-go/issues/233 if you want to follow along there.

Thanks for your help with this, I'm glad we found the issue rapidly and I will follow the github issue to see when it is ready.

If you need me to test a future beta release let me know I'll be happy to do it.

1 Like

Can you try this one?

v1.54.0-beta.5061.705d00b8b.fix-azureblob-memory on branch fix-azureblob-memory (uploaded in 15-30 mins)

This contains one of the potential fixes to the azureblob SDK. That fix isn't merged yet but it looks good to me.

Hi @ncw

I tried it (git clone + docker build on the fix-azureblob-memory branch) and it works.

Just to compare, syncing the same data into an empty azureblob storage, docker stats on version 1.52.3 would report memory use of 261MB / 500MB
docker stats with the fix reports 278 MB / 500 MB, so in par with 1.52.3

Hopefully they will merge the fix soon.

Great :slight_smile: Thank you for testing.