f1b6d4ded6
handle directx nodes the same as gpu nodes
2022-09-23 09:55:14 +02:00
1698e0e583
Separate and refactor custom resources logic
2021-04-07 10:31:11 +00:00
655b4081f4
Migrate to klog v2
2020-06-05 17:22:26 +02:00
af270b05f6
cluster-autoscaler/taints: ignore taints on existing nodes
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Signed-off-by: Julien Balestra <julien.balestra@datadoghq.com>
2020-02-25 13:55:17 +01:00
90666881d3
Move GPULabel and GPUTypes to cloud provider
2019-03-25 13:03:01 -07:00
016bf7fc2c
Use k8s.io/klog instead github.com/golang/glog
2018-11-26 17:30:31 +01:00
52aaac362f
Remove GetGpuRequests function
2018-09-05 11:58:46 +02:00
800ee56b34
Refactor and extend GPU metrics error types
2018-07-05 13:13:11 +02:00
553db2c9fc
Separated errors
2018-07-05 11:30:12 +02:00
aae4d1270a
Make GetGpuTypeForMetrics more robust
2018-06-26 21:35:16 +02:00
5eb7021f82
Add GPU-related scaled_up & scaled_down metrics ( #974 )
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* Add GPU-related scaled_up & scaled_down metrics
* Fix name to match SD naming convention
* Fix import after master rebase
* Change the logic to include GPU-being-installed nodes
2018-06-22 21:00:52 +02:00
57ea19599e
Explicitly return AutoscalerError from GetNodeTargetGpus
2018-06-14 15:46:58 +02:00
087a5cc9a9
Respect GPU limits in scale_down
2018-06-13 14:19:59 +02:00
bada827839
Simplify the code by removing superfluous variable
2018-05-18 09:38:47 +02:00
f877f5a64e
Remove unused error handling
2018-05-10 12:15:42 +02:00
abbc45da2e
Delay scale-up including GPU request
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Nodes with GPU are expensive and it's likely a bunch of pods
using them will be created in a batch. In this case we can
wait a bit for all pods to be created to make more efficient
scale-up decision.
2018-03-02 15:55:04 +01:00
d876d74912
Ignore unfitness in price expander if using GPU
2018-03-02 15:50:43 +01:00
b7f8622eb2
Create node groups with GPU in scale-up.go
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This is still not implemented in cloudprovider.
Extended NewNodeGroup inteface to have a way of passing
parameters for more complex resources.
2017-12-11 13:12:22 +01:00
6554919700
Helper function to calculate GPU requests for NAP
2017-12-11 13:12:22 +01:00
f8c0e20ad9
Source fix after godep update
2017-11-28 14:01:43 +01:00
d81dca5991
Mark nodes with uninitialized GPUs as unready
2017-11-10 17:56:10 +01:00
2b28ac1a04
Add a workaround for scaling of VMs with GPUs
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When a machine with GPU becomes ready it can take
up to 15 minutes before it reports that GPU is allocatable.
This can cause Cluster Autoscaler to trigger a second
unnecessary scale up.
The workaround sets allocatable to capacity for GPU so that
a node that waits for GPUs to become ready to use will be
considered as a place where pods requesting GPUs can be
scheduled.
2017-11-06 16:04:22 +01:00
Flavian
Bartłomiej Wróblewski
Maciek Pytel
Julien Balestra
Jiaxin Shan
Łukasz Osipiuk
Aleksandra Malinowska
Karol Gołąb
Łukasz Osipiuk
Marcin Wielgus
Beata Skiba