| TMO-3831 |
- Summary: On Openshift Azure (4.10) environment, user is unable to score spark models using an end to end scoring pipeline.
- Workaround: None. Spark models must be scored in other deployment environments like Azure or AWS.
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| TMO-3745 |
- Summary: TIBCO ModelOps throws an error when trying to use an array-type field with a Python model.
- Workaround: None.
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| TMO-3744 |
- Summary: TIBCO ModelOps shows an error when trying to use a base64-encoded binary data in a Python model.
- Workaround: None.
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| TMO-3735 |
- Summary: When a model artifact is exported with a project, the “Model Type” property is not included in that project metadata. As such, when it is imported this data is missing and the model type is set to “Other”.
- Workaround: After importing a project, users must manually set the model type property again.
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| TMO-3733 |
- Summary: When approving a data channel or pipeline artifact to “Testing” or “Production” environments, there are two requirements: the artifact must be published and the artifact must be approved to any preceding environments in the predefined environment flow. Currently, informational messages only specify the requirement to be published.
- Workaround: None.
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| TMO-3686 |
- Summary: When editing a Scoring Pipeline artifact that had references to data channels that no longer exist, the user interface incorrectly does not indicate this as an error, and the user does not see the selectors with the previously saved information.
- Workaround: None.
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| TMO-3460 |
- Summary: The WS connection between the request-response data channel and the scoring flow engine is broken.
- Workaround: None. When this issue occurs, the user must terminate the data channel and redeploy it.
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| TMO-3337 |
- Summary: The Python Runner does not support the Python syntax
from <module-name> import <name> for modules in the requirements.txt file. An error is thrown when the python runner loads the script.
- Workaround: Use
import modulename and then specify the complete package name when referenced. |
| TMO-2832 |
- Summary: If a scoring flow runs for a short period of time, it is possible that metrics and usage data do not get recorded by TIBCO ModelOps.
- Workaround: None.
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| TMO-2735 |
- Summary: When using Kafka sink channels which use the Kafka producer adapter, “date” data type converts to “datetime” format.
- Workaround: None. Note that the “time” portion of the “datetime” format will default to midnight and must not be used for data precision.
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| TMO-2676 |
- Summary: Filtering by day in the Usage view might fail to display some intended deployments as the local timezone and the server time zone might differ.
- Workaround: Increase the filtering range to account for deployments that might have happened in a previous or future day because of timezones.
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| TMO-2648 |
- Summary: When attempting to approve a published data channel or scoring pipeline to an execution environment that is only restricted to published artifacts(testing and production in the default configuration), the user may find these options disabled in the Approve dialog with the message: Artifacts must be published before they can be approved for this Environment. This is due to the fact that a Sandbox copy of the artifact was automatically created upon opening the file used to reach the Approval dialog.
- Workaround: Use the Approve feature available on “Data Channel Deployments” and “Scoring Pipeline Deployments” pages. The user can use these pages to select the revision of the artifact that the user want to approve, specifically a published revision, and then approve that specific revision to a given environment.
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| TMO-2620 |
- Summary: The LetsEncrypt certificate provider requires domain names to be shorter than 64 characters to issue a valid certificate.
- Workaround: When installing ModelOps, the user is responsible for ensuring their domain name is sufficiently short to ensure they receive a valid certificate.
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| TMO-2555 |
- Summary: The user interface may become slow and unresponsive (possibly with a browser warning about this) as the total number of artifacts stored and managed by TIBCO ModelOps increases.
- Workaround: Reduce the number of projects first, and then reduce the number of artifacts.
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| TMO-2533 |
- Summary: TIBCO ModelOps does not support deleting published projects and artifacts.
- Workaround: None.
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| TMO-2312 |
- Summary: Files added to a file source user folder are not streamed in some circumstances.
- Workaround: None. When this issue occurs, the user must terminate the data channel and redeploy it.
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| TMO-2225 |
- Summary: If the user use a Kafka Data channel, and use authentication configured via the broker string, the user interface displays the entirety of this string in plain text on screen and it might also appear in logs.
- Workaround: None.
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| TMO-2219 |
- Summary: The status string displayed in the user interface for a running Data Channel displays some tasks as incomplete. However, this is not an error or a warning of any kind..
- Workaround: None.
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| TMO-1858 |
- Summary: As a scoring flow shuts down, the last records might not reach the channel in time to be written.
- Workaround: Avoid canceling or scheduling such a flow as a batch job. The user can also use a Python step to insert a sleep delay when the end of the batch has been recognized by the flow.
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| TMO-1409 |
- Summary: When you use a previously used deployment name, the user interface shows no error. However, the deployment fails with an error about the deployment needing a unique name, even if previous deployments are completed.
- Workaround: Use a unique name for each deployment.
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