Jamstack: Azure Serverless Functions App With React

Jamstack: Azure Serverless Function App With React

Matt McCandless Architecture, Azure, Development Technologies, 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 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 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 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.

FHIR APIs

Part 1: Creating an FHIR API – Google or Azure?

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

Data interoperability is one of the hardest problems in Healthcare IT. The most popular approach is to exchange HL7v2 messages between systems. These pipe-delimited messages are difficult to read by a human and often need additional customizations between implementations.

The next major paradigm shift is towards FHIR (Fast Healthcare Interoperability Resources), a JSON-based standard that is evolving ahead of the needs of the industry. Cloud vendors like Microsoft, Amazon, and Google are trying to lay their claim to be the one-stop shop for healthcare on the cloud.

This blog is part of a 4 part series diving into an actual use case I recently encountered while working with a client. I had to stand up an FHIR repository/API for 2+ million patients that could be used by hundreds of users every day, as well as countless background processes.