Revise sample configs, increase memory requests, update Ray versions #761

DmitriGekhtman · 2022-11-25T17:22:37Z

Signed-off-by: Dmitri Gekhtman dmitri.m.gekhtman@gmail.com

Why are these changes needed?

This PR

Cleans up and updates sample configs and test files
Increments Ray versions to the latest Ray release (2.1.0)

Memory resource requests are increased in some sample configs.
The Ray head pod has a high risk of running out of memory if it is allocated less than 2Gb memory, so that's fixed.

Related issue number

Checks

I've made sure the tests are passing.
Testing Strategy
- Unit tests
- Manual tests
- This PR is not tested :(

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

kevin85421

Thank @DmitriGekhtman for this contribution! Would you mind to update:

(1) rayVersion and image for all sample YAML files in ray-operator/config/samples

(2) Update the following line to the latest ray release (i.e. 2.1.0)

kuberay/tests/framework/test_sample_raycluster_yamls.py

Line 57 in 49c44bf

os.getenv('RAY_IMAGE', default='rayproject/ray:2.0.0'),

(3) Run configuration tests on your local machine. Currently, only 3 small configuration YAMLs can be tested in KubeRay CI. We can test ray-cluster.autoscaler.yaml and ray-cluster.complete.yaml by running the following command in your local environment:

python3 test_sample_raycluster_yamls.py 2>&1 | tee log

kuberay/tests/framework/test_sample_raycluster_yamls.py

Lines 29 to 31 in 49c44bf

    
           "ray-cluster.getting-started.yaml", 
        
           "ray-cluster.ingress.yaml", 
        
           "ray-cluster.mini.yaml"

kevin85421 · 2022-11-25T19:07:29Z

By the way, would you mind describing more about the relationship between increasing memory requests and OOM? Thanks!

Without the context of GKE, it is hard to understand. For me, I thought a Pod will be killed by OOM when

(1) Memory usage exceeds memory limit. => In this case, making memory request equal to memory limit cannot resolve OOM.

(2) When the cluster runs out of resources, Pods with memory usage (>= memory request, but <= memory limit) will be killed before those Pods with memory usage (<= memory request). => In this case, making memory request equal to memory limit will make other Pods OOM or Pods cannot be scheduled.

Only in the context of GKE autopilot, it makes sense to avoid OOM by increasing memory requests. Thanks!

DmitriGekhtman · 2022-11-25T21:20:37Z

Right, there are two related motivations:

GKE autopilot has a tendency to automatically decrease memory limits to requests, which will cause unexpected OOMs.
Ray has no understanding of limits vs. requests, as Ray was designed with VMs in mind. KubeRay advertises the memory limit to Ray as the Ray node's memory capacity and that's all that Ray sees. Thus, for consistency of Ray's behavior, it's best to simply line up limits and requests.
Otherwise, whether your Ray pod OOMs or not is sensitive to the K8s environment in ways that are difficult to understand.
[K8s container limit] == [K8s container request] == [Ray node resource capacity] is much easier to work with.

DmitriGekhtman · 2022-11-25T21:26:20Z

(2) When the cluster runs out of resources, Pods with memory usage (>= memory request, but <= memory limit) will be killed before those Pods with memory usage (<= memory request). => In this case, making memory request equal to memory limit will make other Pods OOM or Pods cannot be scheduled.

In particular, if you don't set requests=limits, you're prone to unexpected results due to the K8s behavior you've described.
You are more prone to noisy neighbors issues that depend on what your K8s nodes look like and what other workloads are running on these nodes. So when a Ray worker OOMs, you won't know if you made a mistake setting up your Ray workload or if another user was running a resource-intensive application that overlapped on the same physical K8s nodes.

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

DmitriGekhtman · 2022-11-25T21:42:20Z

TODO: Run configuration tests.

I'll also add a blurb to the development docs about these tests (if that's not there already)

kevin85421 · 2022-11-26T06:51:06Z

The update looks good to me. Feel free to merge it if the configuration tests pass.

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

kevin85421

Update the version of Ray from 2.0.0 to 2.1.0 in configuration test CI.

kuberay/.github/workflows/test-job.yaml

Lines 343 to 360 in 49c44bf

    
           sample-yaml-config-test-2_0_0: 
        
             needs: 
        
               - build_operator 
        
               - build_apiserver 
        
               - lint 
        
             runs-on: ubuntu-latest 
        
             name: Sample YAML Config Test - 2.0.0 
        
             steps: 
        
               - name: Check out code into the Go module directory 
        
                 uses: actions/checkout@v2 
        
                 with: 
        
                   # When checking out the repository that 
        
                   # triggered a workflow, this defaults to the reference or SHA for that event. 
        
                   # Default value should work for both pull_request and merge(push) event. 
        
                   ref: ${{github.event.pull_request.head.sha}} 
        
               - uses: ./.github/workflows/actions/configuration 
        
                 with: 
        
                   ray_version: 2.0.0

Update the default Ray image from 2.0.0 to 2.1.0 in configuration test scripts.
- test_sample_raycluster_yamls.py#L57
- test_sample_rayservice_yamls.py#L33

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

DmitriGekhtman · 2022-11-28T19:53:20Z

Need to debug some of the tests -- great to see the tests catching misconfigurations.

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

tests/config/ray-cluster.mini.yaml.template

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

DmitriGekhtman · 2022-12-01T06:23:02Z

Woooooo, the CI is green after #759
Nice work @kevin85421. Would you mind giving this PR a final review?

Jeffwan

most parts look good to me. I did't check test framework part. leave it to Kevin

kevin85421

It looks good to me, but it is hard for me to verify this big PR. The good thing is that I will check all sample YAML files [1] before v0.4.0 release except ray-cluster.complete.large.yaml and ray-cluster.autoscaler.large.yaml. Hence, feel free to merge this PR if you double-check the two large YAML files. Maybe we can update their memory requests, cpu requests, and repliacs to enable them to be tested on your laptop.

[1] https://docs.google.com/spreadsheets/d/1wlTXCWNtQxCUENa0fP2-dV6UYNUhUCix4exiGsep5GQ/edit#gid=1603824512

kevin85421 · 2022-12-01T08:20:14Z

tests/config/ray-service-cluster-update.yaml.template

@@ -44,30 +44,13 @@ spec:
    headGroupSpec:
      # Kubernetes Service Type, valid values are 'ClusterIP', 'NodePort' and 'LoadBalancer'
      serviceType: ClusterIP
-      # the pod replicas in this group typed head (assuming there could be more than 1 in the future)


This file should be deleted.

https://github.com/ray-project/kuberay/pull/759/files#diff-db7eeddbec6895cf05cb70312b97d42f54bdd61ac34ee18d3f74d02ab349b5bfL274

Thanks for pointing that out!

kevin85421 · 2022-12-01T08:20:32Z

tests/config/ray-service-serve-update.yaml.template

@@ -44,30 +44,18 @@ spec:
    headGroupSpec:
      # Kubernetes Service Type, valid values are 'ClusterIP', 'NodePort' and 'LoadBalancer'
      serviceType: ClusterIP
-      # the pod replicas in this group typed head (assuming there could be more than 1 in the future)


This file should be deleted.

https://github.com/ray-project/kuberay/pull/759/files#diff-db7eeddbec6895cf05cb70312b97d42f54bdd61ac34ee18d3f74d02ab349b5bfL274

DmitriGekhtman · 2022-12-01T19:21:19Z

It looks good to me, but it is hard for me to verify this big PR. The good thing is that I will check all sample YAML files [1] before v0.4.0 release except ray-cluster.complete.large.yaml and ray-cluster.autoscaler.large.yaml. Hence, feel free to merge this PR if you double-check the two large YAML files. Maybe we can update their memory requests, cpu requests, and repliacs to enable them to be tested on your laptop.

I'll double check those.
The configuration test passes!

Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

DmitriGekhtman · 2022-12-01T20:59:01Z

I tested raycluster.complete.large and raycluster.autoscaler.large on GKE -- everything lgtm.

DmitriGekhtman · 2022-12-01T22:10:06Z

CI looks nice and green. Manual testing does not reveal any issues. Merging!

Closes #805 which was caused by incomplete config cleanup in #761 . Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

…ay-project#761) This PR - Cleans up and updates sample configs and test files - Increments Ray versions to the latest Ray release (2.1.0) - Memory resource requests are increased in some sample configs. - The Ray head pod has a high risk of running out of memory if it is allocated less than 2Gb memory, so that's fixed. Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

Closes ray-project#805 which was caused by incomplete config cleanup in ray-project#761 . Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

DmitriGekhtman added 2 commits November 25, 2022 09:12

More documentation.

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more

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DmitriGekhtman requested review from waleedkadous and kevin85421 November 25, 2022 17:22

kevin85421 reviewed Nov 25, 2022

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Update Ray versions

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DmitriGekhtman added 2 commits November 26, 2022 08:36

More version updates.

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Add issue reference.

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kevin85421 reviewed Nov 26, 2022

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DmitriGekhtman added 11 commits November 26, 2022 09:47

Skip untracked files in configuration test.

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Mention configuration tests in development.md

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Clean-up

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More cleanup

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More version updates.

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More removal of extraneous configuration.

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More cleanup

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More cleanup

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More updates.

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Eliminate outdated example config.

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More cleanup

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DmitriGekhtman changed the title ~~Revise sample configs, increase memory requests.~~ Revise sample configs, increase memory requests, update Ray versions Nov 28, 2022

Fix requirements.txt.

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tweak

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kevin85421 mentioned this pull request Nov 28, 2022

[Feature] Add a hook to check static Rules #767

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More cleanup

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kevin85421 reviewed Nov 29, 2022

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DmitriGekhtman added 3 commits November 29, 2022 14:17

Fix selector.

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More cleanup

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Rerun CI.

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DmitriGekhtman requested review from kevin85421 and Jeffwan November 29, 2022 22:57

DmitriGekhtman added 7 commits November 29, 2022 15:31

fix

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reintroduce redis env

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Fix dash

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Fix again.

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tweak

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Add issue reference

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Merge branch 'master' into dmitri/match-memory-requests-and-limits

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DmitriGekhtman added 2 commits December 1, 2022 12:34

Remove outdated templates.

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Swap small and large

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DmitriGekhtman merged commit 5d38eda into ray-project:master Dec 1, 2022

DmitriGekhtman mentioned this pull request Dec 7, 2022

[RayJob][Doc] Fix RayJob sample config. #807

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[RayJob][Doc] Fix RayJob sample config. (#807)

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Closes #805 which was caused by incomplete config cleanup in #761 . Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

kevin85421 mentioned this pull request Dec 13, 2022

[Feature] Move some functions from prototype test framework to a new utils file #837

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kevin85421 mentioned this pull request Apr 18, 2023

[Bug][GCS FT] Worker pods crash unexpectedly when gcs_server on head pod is killed #1036

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Revise sample configs, increase memory requests, update Ray versions #761

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	"ray-cluster.getting-started.yaml",
	"ray-cluster.ingress.yaml",
	"ray-cluster.mini.yaml"

	sample-yaml-config-test-2_0_0:
	needs:
	- build_operator
	- build_apiserver
	- lint
	runs-on: ubuntu-latest
	name: Sample YAML Config Test - 2.0.0
	steps:
	- name: Check out code into the Go module directory
	uses: actions/checkout@v2
	with:
	# When checking out the repository that
	# triggered a workflow, this defaults to the reference or SHA for that event.
	# Default value should work for both pull_request and merge(push) event.
	ref: ${{github.event.pull_request.head.sha}}
	- uses: ./.github/workflows/actions/configuration
	with:
	ray_version: 2.0.0

Revise sample configs, increase memory requests, update Ray versions #761

Revise sample configs, increase memory requests, update Ray versions #761

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DmitriGekhtman commented Nov 25, 2022 • edited

Why are these changes needed?

Related issue number

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