Avaya Agent for Desktop with React and SignalR

Code Tutorial: Integrating Avaya Agent For Desktop With React And SignalR

Keyhole Software .NET, Articles, Azure, Company News, Development Technologies & Tools, Programming, React, Tutorial Leave a Comment

Keyhole Software gives readers an in-depth code walkthrough and tutorial for how to integrate Avaya Agent for Desktop using React and SignalR.

This integration allows the web-based application to asynchronously receive information about an inbound call, which enriches agents’ experiences and protects against context switching and double documenting. As for technology, AAfD (Avaya Agent for Desktop) is used as the softphone, React as the library to compose the SPA (Single Page Application), and SignalR as the bi-directional message hub.

The hypothetical scenario in this tutorial can be extended to many other use cases where there needs to be coordination between disparate systems, with an end user’s web browser being informed of the traffic without needing to do any long polling or other methodologies.

Asynchronous data flow is useful to many different business verticles, and SignalR is a powerful tool that will likely become a larger part of the custom Application Development enterprise ecosystem in years to come.

Jamstack: Azure Serverless Functions App With React

Jamstack: Azure Serverless Function App With React

Matt McCandless Architecture, Articles, Azure, Development Technologies & Tools, Node.js, React Leave a Comment

A new trend of creating applications is emerging called Jamstack. No, this isn’t slapping together your favorite flavor of jelly (grape is the best) with peanut butter and two pieces of bread. The intent is an architecture that is faster, more secure, and easier to scale. It focuses on pre-rending and decoupling. This way, the solutions created are more reliable and resilient than before.

Pre-rendering comes by the way of using a static website via a CDN for high availability and security. No more serving your React app via web server like we’ve become accustomed to. It reduces cost and complexity by eliminating the regular maintenance and configuration of traditional servers.

Also, the idea of APIs and the ability to move them to things like Serverless functions creates more cost savings, elimination of traditional servers, and use of features only when they are requested. For more information, check out the Serverless website.

Part 4: Creating an FHIR API – Wrapping Things Up

Zach Gardner API Development, Articles, Cloud, Creating an FHIR API, Tutorial Leave a Comment

Welcome to the fourth and final installment of Creating an FHIR API with GCP. So far, we’ve covered a lot!

We discussed the differences between Google and Azure, landing on GCP as the best option for FHIR in Part 1. We began our implementation in Part 2, creating both the BigQuery resources and your FHIR repository resources. And finally, in Part 3, we tackled authentication methods and populating data in our FHIR repository.

This time, we’ll wrap everything up with a nice little bow. First, we’ll finish our implementation, and then, I’ll share the limitation I found – for the sake of transparency. Let’s dive in.

Part 3: Creating an FHIR API – Implementation Part B

Zach Gardner API Development, Articles, Cloud, Creating an FHIR API, Tutorial Leave a Comment

This is Part 3 of our series on creating an FHIR API using Google Cloud’s offering. In the last installment, we began implementing an FHIR using GCP. We covered creating both the BigQuery resources and your FHIR repository resources. if you missed Part 1 and Part 2, be sure you go back to read those – they’re critical to understanding!

This time, we’re continuing the implementation. I’ll explain the authentication methods, and we’ll also tackle populating data in our FHIR repository.

Creating an FHIR API Part 2

Part 2: Creating an FHIR API – Implementation Part A

Zach Gardner API Development, Articles, Cloud, Creating an FHIR API, Tutorial Leave a Comment

Welcome back to our series, Creating an FHIR API. This is Part 2 in our 4-part series on standing up an FHIR using GCP. In Part 1, we talked through two of the offerings out there, Google and Azure, and based on the pros and cons, I decided to use GCP FHIR Cloud Healthcare API.

In this part, we’ll start in on our implementation. A forewarning: we won’t be able to finish it during this installment, so stay tuned for parts 3 and 4! Let’s dive in.