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Description
- Concourse version:
3.8.0
- Deployment type (BOSH/Docker/binary): Binary
- Infrastructure/IaaS: GCE
Our setup is composed of a minimum of 4 nodes in an autoscaling group. Nodes are configured as 1-standard-4
(4vcpu, 15GiB ram) with attached NVMe of 375GiB. The os is Ubuntu 16.04 LTS.
The following settings are of interest :
CONCOURSE_WORK_DIR
is redirected to NVMe storageCONCOURSE_BAGGAGECLAIM_DRIVER
is set tooverlay
CONCOURSE_BAGGAGECLAIM_VOLUMES
is redirected to NVMe storageCONCOURSE_BAGGAGECLAIM_OVERLAYS_DIR
is redirected to NVMe storageCONCOURSE_GARDEN_DESTROY_CONTAINERS_ON_STARTUP=true
CONCOURSE_GARDEN_DEPOT
is redirected to NVMe storageCONCOURSE_GARDEN_PROPERTIES_PATH
is redirected to NVMe storageCONCOURSE_GARDEN_ASSETS_DIR
is redirected to NVMe storage- The NVMe is formatted with the following settings
mkfs.xfs -f -n ftype=1 /dev/nvme0n1p1
and is mounted withnoatime
which is aligned with the Google storage recommendations for GCE - The NVMe partition is labeled GPT and is block aligned
We tested the NVMe on those instances and get performance in the ballpark of 330 MiB/s and 18k random IOPS on those kind of instances. We're hoping this should be sufficient to pull large images.
With the settings above, we are seeing certain tasks relying the Docker Image Resource where we know the images contain a lot of small files taking an average of 15 minutes before scheduling. The behaviour seems the consistent with what was observed in #1404 where a build will "hang" for a while in the loading state before announcing it's running.
We tried reverting to btrfs
only to enjoy stalled workers and garden variety mayhem. (...see what I did there? 😛 )
This issue seems to be following in the wake of #1230, for which we had a meeting with @vito @jama-pivotal, and @topherbullock . (Thanks again for that guys! It's much appreciated!) I'm not hoping for a quick fix to this, but I'm hoping to outline that this situation is a quantifiable problem for the organizations where we're running Concourse. I am also volunteering whatever resources you believe might help us alleviate the problem.
As one would say... Halp!