In software engineering, continuous integration (CI) is the practice of merging all developer working copies to a shared mainline several times a day.
Hello everyone,
I am André from MedVertical. We are exploring InterSystems-native ways to operationalize continuous FHIR conformance: repeatable regression runs, baseline/delta comparisons, and evidence-style reporting to detect drift after releases and IG changes.
In many FHIR implementations, validation is done “point-in-time” in pre-prod, but conformance degrades in production due to IG/profile updates, terminology changes, mapping evolution, upstream releases, and configuration drift.
Welcome to the next chapter of my CI/CD series, where we discuss possible approaches toward software development with InterSystems technologies and GitLab.
Today I want to share a few approaches that will decrease your compilation time (especially if you're doing incremental/diff compilation rather than a full build).
Code load and compilation are affected by a variety of flags and qualifiers. If you write deployment scripts for InterSystems platforms, I highly recommend reading them at least once through.
We are a group of interface analysts in a healthcare setting, running IRIS for Health 2024, having upgraded over time from an old ENSEMBLE environment. We have been working on a wish list of development goals, but are having trouble finding the correct, best practice method/path for getting to what we envision.
Current state: We run IRIS for Health on a Redhat 8 virtual machine. We run Interoperability productions (IE.cls) out of 6 namespaces. We have a dev/test box and a production box.
This web interface is designed to facilitate the management of Data Lookup Tables via a user-friendly web page. It is particularly useful when your lookup table values are large, dynamic, and frequently changing. By granting end-users controlled access to this web interface (read, write, and delete permissions limited to this page), they can efficiently manage lookup table data according to their needs.
The data managed through this interface can be seamlessly utilized in HealthConnect rules or data transformations, eliminating the need for constant manual monitoring and management of the lookup tables and thereby saving significant time.
Note:
If the standard Data Lookup Table does not meet your mapping requirements, you can create a custom table and adapt this web interface along with its supporting class with minimal modifications. Sample class code is available upon request.
Hi all,
I'm developing a Azure Pipeline to automate the deployment process in Caché.
I use selfhosted agent to execute code im my Caché Server.
My problem is that cession execution via cmd always terminate with exit code 1 and the pipeline finishes with error, but the execution in Caché is fine, the method executed returns $$$OK
I use the following line to execute a class in Caché.
C:\InterSystems\Cache\bin\csession.exe CACHE -U %RELEASE_TRIGGERINGARTIFACT_ALIAS% "##Class(sgf.pipeline.DeploymentManager).
Hi all,
I'm exited to announce a GitHub Action to do direct deploy code from a github repository direct to a IRIS Instance.
Pleas visit https://openexchange.intersystems.com/package/Github-Action-IRIS-Deployer