This blog post will go over the procedure for upgrading a Tator deployment to the upcoming major release, 1.0.0, with most features recently merged with the main branch. This release requires an upgrade to Postgresql 14 and drops the Elasticsearch dependency for standard queries (although it is still used for storing logs). Deprecated bucket definition formats are also removed in this release. This post assumes that the tator deployment is currently running version 0.2.23, was installed with the install script, and is running on microk8s.

What changed​

In the 1.0.0 release of Tator, the fields related to default upload, live, and backup buckets in the values.yaml configuration file have changed to match the changes from the 0.2.22 release. This is a breaking change and your tator deployment will be broken if your deployment administrator does not follow these instructions during the upgrade to 1.0.0.

What changed​

In the 0.2.22 release of Tator, support for OCI Object Storage as a bucket was added. This required a refactor of how bucket configurations are stored by Tator, which is not backwards compatible. The 0.2.22 release deprecates the existing method of creating and updating buckets, but still allows for buckets created this way to function. Release 1.0.0 will deprecate the functionality of buckets created this way, but there is a utility that will assist your migration from the old configuration to the new one.

Creating a tator-py AWS Lambda Layer​

To use python packages that are not included in the AWS Lambda runtime, you must create a Layer. This post explains what AWS Lambda is and outlines how to create a Layer containing tator-py and add it to your Lambda.

Using Okta as an Identity Provider for Tator​

This will require setting up a SAML-based application integration in Okta and then setting the SAML metadata configuration URL in Tator.

As a video data analyst, it doesn't matter whether you're looking at coral reef or discarded haddock, every pixel counts. In upcoming versions of Tator higher video quality of 4k and 8k are unleashed for analysis. While maintaining frame accurate playback, between multiple sources, video sources can now scale up to 8k resolution.

Figure 1: Comparison of common video resolutions

This blog post will go over the procedure for upgrading a Tator deployment to the latest release, 0.2.19. This release updates the versions of some dependencies, which require more user actions than the standard upgrade process. It assumes that the tator deployment was set up using the install script and is running on microk8s.

In this blog post, we will cover how to install Tator on a GCP VM. The main trick is updating the domain to the virtual machine's public IP address after running the install script. This is necessary because by default the install script will discover the internal IP address only, and use that IP address for the load balancer, Kubernetes API server, and domain name. For the most part we simply need to run the install script and make one change to the Helm config file, but we will also cover VM setup in the GCP console.

Upcoming versions of Tator, specifically 0.2.18, utilize a cutting edge browser feature known as the WebCodecs API. Based on browser security, features such as WebCodecs API are turned off in insecure origins.

Our next release of Tator, version 0.2.14, will include support for Argo 3.