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Releases: hydroserver2/hydroserver

v1.6.3

12 Jan 17:33

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v1.6.3

Release Date: January 12, 2026

Fixed an issue causing SensorThings Thing endpoint to not properly fetch tag and file attachment metadata.

v1.6.2

12 Jan 17:31

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v1.6.2

Release Date: December 18, 2025

Added a referrer meta tag to index.html. This will allow custom basemap layers to load properly.

v1.6.1

09 Dec 10:23
971bb12

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v1.6.1

Release Date: December 6, 2025

Fixed an issue in the data management app causing some new HydroServer users to be unable to create new workspaces.

v1.6.0

01 Dec 18:42
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HydroServer v1.6 Release Notes

Release Date: December 1, 2025

📎 Support for Datastream Tagging and File Attachments

Datastreams can now be tagged and have files attached to them, matching similar functionality for things/sites.

🔌 HydroServer TypeScript Client

A new HydroServer TypeScript client is available to help streamline HydroServer app development. The client is installable via NPM at https://www.npmjs.com/package/@hydroserver/client.

v1.5.3

24 Oct 22:24
c6ca8bf

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Release Date: October 24, 2025

Fixed PostgreSQL execution plan bottleneck on observation checksum generation.

v1.5.2

21 Oct 17:42
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HydroServer v1.5.2 Release Notes

Release Date: October 21, 2025

Fixed a checksum generation issue on empty datastreams.

v1.5.1

08 Oct 16:13

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HydroServer v1.5.1 Release Notes

Release Date: October 8, 2025

Fixed an issue where observations would be deleted inefficiently when deleting a workspace, sometimes resulting in out of memory errors.

v1.5.0

06 Oct 20:26

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HydroServer v1.5 Release Notes

Release Date: October 6, 2025

📈 Additional Support for Result Qualifiers

Result qualifiers can now be uploaded and retrieved via HydroServer's Data Management API. One or more result qualifiers can be assigned to datastream observations.

Note: Result qualifier codes have an updated constraint requiring uniqueness per workspace. Before updating your instance, ensure each workspace (including system-wide qualifiers) have been assigned unique codes.

✅ Observation Response Checksums

A new response header for observations called X-Checksum has been added to HydroServer's Data Management API. This value is generated for any given selection of observations and will only change when one or more observations within that selection are created or deleted. This is useful for applications that need to track if changes have been made to observations without storing and comparing the full response.

📚 Updated Deployment Documentation

HydroServer's production deployment documentation has been updated. The updated documentation consolidates platform-independent guidelines into one document. The in-depth hydroserver-ops deployment guides and workflows have been replaced with lighter weight demo deployment examples for AWS, GCP, and local Docker deployments. These demo deployments are intended to provide a starting point for deploying HydroServer, but are not considered production ready out of the box and should be modified based on the needs of your organization.

v1.4.0

04 Sep 17:55
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HydroServer v1.4 Release Notes

Release Date: September 4, 2025

⚙️ Improved Deployment Workflows

HydroServer’s Vue-based frontend is now pre-built and bundled with the HydroServer Django service in a ready-to-run Docker image released with each version. As part of this change, a new Web app is available in the Django admin dashboard, allowing administrators to configure HydroServer website settings such as map layer options and the About page.

We’ve also added a simple guide to help you get started deploying HydroServer with Docker Compose.

🔃 Enhanced ETL Data Transformations

HydroServer’s ETL dashboard and the hydroserverpy client library have been updated with expanded data transformation functionality. These updates allow users to define and apply a broader set of transformations during data ingestion and management workflows.

⚠️ Deployment Note

We will be deprecating and ending support for the hydroserver-ops deployment workflows in an upcoming release. Instead, we will provide reference Terraform examples for AWS and GCP to help you get started with non-production HydroServer deployments. If you previously forked hydroserver-ops, you may continue using and maintaining those workflows for your own deployments, but they will no longer be updated or supported.

This release also changes how HydroServer is deployed in AWS and GCP. The HydroServer web frontend is now prebuilt, bundled into the HydroServer Docker image, and served through Django’s static file system. You no longer need to build and deploy the frontend separately—just point your load balancer to the Django backend, which also serves the static files (optionally backed by a storage bucket). If you are using hydroserver-ops, simply pull version 1.4.0 and run Initialize HydroServer Deployment.

v1.3.0

01 Aug 17:58
676ef27

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HydroServer v1.3 Release Notes

Release Date: August 1, 2025

📈 Improved API Functionality

HydroServer's API now supports additional parameters for sorting, paginating, and filtering data. New endpoints have been added for managing observations, including improved support for creating observations and a new endpoint for deleting ranges of observations from a datastream. The hydroserverpy package has been updated to reflect these changes.

Note: Review and update any scripts using hydroserverpy before deploying this release. Several method signatures for retrieving collections have changed and may cause compatibility issues with existing scripts. Updated examples can be found in HydroServer's documentation.

🧭 Enhanced Job Orchestration Setup

The Job Orchestration page now offers expanded time zone offset options when configuring data sources. Additional datastream context is also displayed on this page and other areas where datastreams can be selected.

⚠️ Deployment Note

This release changes the observation index model. As a result, TimescaleDB hypertables are no longer supported for the observation table. If you are using TimescaleDB, ensure that the observation table is not a hypertable prior to deploying.

The observation index change will be applied automatically on deployment. However, if your observation table is large, consider running this release’s migrations manually, as reindexing may take longer than usual.