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  1. Red Hat OpenShift Data Science
  2. RHODS-7948

[DSG] Upload Secret in workbench double encodes the values

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    • Icon: Bug Bug
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    • RHODS_1.26.0_GA
    • RHODS_1.25.0_GA
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    • 1.26.0
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      == Uploading a secret file containing environment variables results in double-encoded values

      Previously, when creating a workbench in a data science project, if you uploaded a YAML-based secret file containing environment variables, the environment variable values were not decoded. Then, in the resulting OpenShift secret created by this process, the encoded values were encoded again. This issue is now fixed.
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      == Uploading a secret file containing environment variables results in double-encoded values Previously, when creating a workbench in a data science project, if you uploaded a YAML-based secret file containing environment variables, the environment variable values were not decoded. Then, in the resulting OpenShift secret created by this process, the encoded values were encoded again. This issue is now fixed.
    • Bug Fix
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    • Yes
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    • RHODS 1.26

      Description of problem:

      when you upload a secret yaml file, the values do not get decoded before storing them into the Secret. It means, the values get re-encoded. If you add a new environment variable in the workbench using the Key/Value method, it doesn't happen.

      Prerequisites (if any, like setup, operators/versions):

      Steps to Reproduce

      1. create a DS project
      2. create a workbench and add env variables by uploading a Secret (yaml format)
      3. fill the remaining workbench data
      4. submit the workbench creation
      5. check the Secret which gets created in OpenShift

      Actual results:

      values under "data" section of the Secret get encoded twice: the yaml file has already the values encoded

      Expected results:

      values under "data" section of the Secret do not get re-encoded

      Reproducibility (Always/Intermittent/Only Once):

      Always

      Build Details:

      RHODS 1.25

      Workaround:

      decode the values when using the environment variables in Jupyter

      Additional info:

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