Updated the service.yaml template by removing unnecessary comments and
whitespace for better readability. The updates include cleanup of the
Kubernetes service definition while maintaining the original functionality.
These changes simplify the code structure without altering the service's
behavior. No breaking changes were introduced, ensuring compatibility with
existing configurations.
This update substantially refactors the paperless-ai Helm chart.
Key changes include:
- Complete removal of outdated files: `.helmignore`, `LICENSE`,
`README.adoc`, and several template files like `configfileConfigmap.yaml`,
`configmap.yaml`, `dataPvc.yaml`, `envfileSecret.yaml`,
`openAiApiSecret.yaml`, `paperlessApiSecret.yaml`, and others.
- Introduction of a new Persistent Volume Claim configuration in
`pvc.yaml` to simplify storage management.
- Significant updates to `Chart.yaml` for better metadata, including
a new maintainer and project description in German.
- Enhancements to the main deployment template in `deployment.yaml`,
focusing on clarity and proper utilization of Kubernetes security
contexts, environment variables, and container properties.
- Updated service definitions in `service.yaml` with better labels
and service properties.
- Refined the `ingress.yaml` to improve external service access
management, including annotations for potential customization.
These changes were implemented to modernize the Helm chart based on
the current best practices, improve user experience, and set a
foundation for future enhancements. There are no breaking changes to
the existing user configurations.
This commit restructures the paperless-ai Helm chart by moving all files
from the nested directory (charts/paperless-ai/paperless-ai/) to the
standard Helm chart directory structure (charts/paperless-ai/). The change
eliminates the redundant directory nesting that was causing issues with
Helm chart packaging and installation. No functional changes were made to
any files - this is purely a directory structure reorganization to follow
Helm best practices and improve chart maintainability.
