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https://issues.apache.org/jira/browse/NIFI-7550?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17138735#comment-17138735
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James Riley McHugh commented on NIFI-7550:
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This is an issue that I am currently facing. I run NiFi in a Docker container
in both Docker Swarm and Kubernetes deployments. Ideally, I would like to be
able to provide values to sensitive properties via Docker/Kubernetes secrets,
but there is currently no way of doing this. I could setup the secret values to
be accessible through environment variables, but sensitive properties do not
support the NiFi Expression Language so environment variables cannot be
accessed.
> Improve population and use of sensitive parameters
> --------------------------------------------------
>
> Key: NIFI-7550
> URL: https://issues.apache.org/jira/browse/NIFI-7550
> Project: Apache NiFi
> Issue Type: Improvement
> Components: Configuration Management, Core Framework
> Affects Versions: 1.11.4
> Reporter: Andy LoPresto
> Assignee: Andy LoPresto
> Priority: Major
> Labels: configuration, credentials, expression-language,
> parameter, properties, sensitive, variable
>
> There has been a lot of discussion recently around the challenges in
> deploying sensitive values (credentials, tokens, etc.) to specific processor
> properties.
>
> * Expression Language does not support sensitive variables
> * Sensitive properties do not support Expression Language
> * Sensitive properties can only reference sensitive parameters
> * Sensitive properties can only reference a single sensitive parameter
> * Sensitive parameters cannot be operated on by Expression Language
> * Sensitive properties which require constructed input (i.e.
> {{Authorization: bearer ABCDEF...}} header) require the sensitive parameter
> to contain format information separate from the sensitive value
> * Sensitive parameters cannot be automatically populated by an external
> source
> Please comment on this ticket with any additional requirements or challenging
> user experiences to inform the next set of decision-making around the
> sensitive parameter experience.
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