helpful-crowd-74546
08/16/2022, 6:00 AM~/.flyte/config.yaml
and configure backend to authenticate using OIDC flow with clientId
& clientSecret
but not sure if I am missing anything else? Basically what I want to achieve is something in line with what you described at Set up DevOps in this blogpost: https://mlops.community/mlops-with-flyte-the-convergence-of-workflows-between-machine-learning-and-engineering/
2. How would you add tolerations to the Pod Specifications for a task/workflow to run on dedicated node pool such as e.g., nodes with GPU/dedicated CPU nodes?tall-lock-23197
helpful-crowd-74546
08/16/2022, 7:39 AMtall-lock-23197
icy-agent-73298
08/16/2022, 9:36 AM1. Yeah, I believe so. @icy-agent-73298, is that the preferred technique?Yes that should be right way if you are leveraging github action . Also for reference config file we use in flyte CI for executing functional tests https://github.com/flyteorg/flytetools/blob/master/functional-tests/config.yaml
@icy-agent-73298, can tolerations be provided at launch plan level?Currently no. These are only supported through plugin configuration
freezing-airport-6809
tall-lock-23197
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jolly-whale-9142
08/16/2022, 4:34 PMhelpful-crowd-74546
08/16/2022, 6:35 PMadmin:
# For GRPC endpoints you might want to use dns:///flyte.myexample.com
endpoint: dns:///development.uniondemo.run
# Change insecure flag to ensure that you use the right setting for your environment
insecure: false
clientId: flytepropeller
clientSecretLocation: /home/runner/secret_location
logger:
# Logger settings to control logger output. Useful to debug logger:
show-source: true
level: 1
helpful-crowd-74546
08/16/2022, 6:43 PMtall-lock-23197
tall-lock-23197
kubectl -n flyte rollout restart deploy flytepropeller
. Reference thread: https://discuss.flyte.org/t/432335/Trying-to-use-GPUs-I-added-a-tolerations-section-as-describe.freezing-airport-6809
jolly-whale-9142
08/17/2022, 7:58 AMadmin:
endpoint: dns:///console.flyte.example.com
insecure: false
authType: ClientSecret
clientId: github-client
logger:
show-source: true
level: 1
storage:
type: stow
stow:
kind: s3
config:
auth_type: iam
region: eu-west-1
container: whatever-name-container
Footer
Then during the step, we create a /etc/secrets
directory like the following
docker run \
-e TAG=$TAG \
--entrypoint /bin/sh \
${{ needs.setup.outputs.path_builder }} \
-c "\
mkdir /etc/secrets && \
echo ${{ secrets[format('{0}_FLYTE_CLIENT_SECRET', needs.setup.outputs.flyte_client_domain )] }} > /etc/secrets/client_secret && \
pyflyte -c ci/cfg/flyte.config package --image ${{ needs.setup.outputs.path_runner }} -f && \
flytectl register files --k8sServiceAccount xxx -p ${{ env.PROJECT }} -d ${{ needs.setup.outputs.domain_name }} --version ${{ env.VERSION }} --archive flyte-package.tgz
Depending on the domain we either get the secrets for our dev cluster or or production cluster.jolly-whale-9142
08/17/2022, 7:58 AMtall-lock-23197
freezing-airport-6809
Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.
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