Containerization is a lightweight alternative to full machine virtualization that involves encapsulating an application in a container with its own operating environment.
We are using IRIS health 2023.1 to build an application that runs on kubernetes cluster as container images. In the container image, we have our own PRODUCTION "APP" created with its routines database and global database located at:
I'm trying to deploy a container based on IRIS Community for Health ML image available from this url but when I start the container the memory consumption skyrockets to 99% making impossible to work with the instance (it never goes below the 95% of the memory). When I do the same with the IRIS Community for Health image it never goes over 80% of memory.
I've been running IRIS in a container for a while with the durable %SYS feature. Previously, I was running IRIS 2022.x version and decided to upgrade to 2023.1. During image build, I create some namespaces and install a FHIR repo into one of them using the following script: