AI Center - ML Skill Failed / Kubernetes operation failed to create deployment

Learning Initatives Automation Starter
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Hi Everyone,

I have created ML Package and ran pipeline it was successful, still my ML Skill getting failed, Showing an error in the log - Kubernetes operation failed to create the deployment.

Any Guess?

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Hi @SrenivasanKanna

What is the status of ML Package.

Thanks.

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The current status is “undeployed”.

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Hi @SrenivasanKanna

It is expected for the ML package to show up as “Undeployed” if the ML Skill for the same package is not deployed and available.

Make sure you Create the ML Package and the ML Skill together and then run the pipeline.

The status of the ML Package should be Deployed and ML Skill should be Available.

Thanks

1 Like
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Thank you, Let me try again.

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Yes please, let me know if you face any issues.

Thanks.

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It’s running showing ‘Deploying’ status for both ML package and ML Skill. Let me wait and see the status. Meanwhile @suraj.setty Can you help me in live once, please.

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@SrenivasanKanna Sure.

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Could you provide your email id, I will send an email regarding the meeting note.

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hi @SrenivasanKanna

did the issue got resolved?

thanks.

1 Like
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Hey Hai Suraj , Your input was grateful. It is helped me to get good understanding on the right flow. Still the issue is not yet resolved. I raised ticket to uipath team and waiting for their reply.

Not sure about this error Kubernetes operation failed will wait for their reply.

1 Like
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Hi @SrenivasanKanna @suraj.setty I am facing the same issue. Any idea on what’s the solution? And did you do all the 3 pipelines, train, evaluation and full and then create the ML skill?

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Hi, We do not select the option (Make this an Evaluation Set) while importing your documents if you want to run your pipeline as Train run.
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Make Sure that, the pipeline will be run based on the Data set Import.

If you Choose as Evaluation set, The pipeline will get success only if you choose Evaluation run.

The Suggested way is - to use Train run to improve your ML Skill and the evaluation run does not improve your ML Skill.

Error Occurred : Resolved

ML Skill Failed / Kubernetes operation failed to create

The Reason is - We need to Follow the Below Order:

  1. Create DataLabelling - Import your doc and Export it. That will be available in your DataSets

  2. Create ML Packages

  3. Run Pipeline - If your pipeline got Success.

  4. Create ML Skill - While Creatin ML Skill Choose the package minor Verison of your latest pipeline version

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