HL7 messaging automation on a enterprise software
Budget: $8 – $15 USD
The Qvera interface engine API set up for automating feed status, update, create, and delete
You will need to download the latest version of Qvera locally. The zip includes detailed api instructions. I wrote a helper app in bash (would have liked python but Azure DevOps plays well with bash).
The bash helper script called functions that would execute the intended api call. This was really easy to build and it worked.
I would need to add these functions to the Azure DevOps tool. This can be creating a ADO function YML file since they are using Azure Pipelines.
Qvera feed developer creates feature branch, then adds exported feed config. Checkin code. this would trigger build that may deploy to dev environment for inspection. Does this make sense?
You will need to download the latest version of Qvera locally. The zip includes detailed api instructions. I wrote a helper app in bash (would have liked python but Azure DevOps plays well with bash).
The bash helper script called functions that would execute the intended api call. This was really easy to build and it worked.
I would need to add these functions to the Azure DevOps tool. This can be creating a ADO function YML file since they are using Azure Pipelines.
Qvera feed developer creates feature branch, then adds exported feed config. Checkin code. this would trigger build that may deploy to dev environment for inspection. Does this make sense?