Integrating Azure Functions with Cosmos DB SQL API in .NET Core 2.2

Zach Gardner .NET Core, Azure, Technology Snapshot, Tutorial Leave a Comment

I am working on a project that leverages both Azure Functions as well as Cosmos DB. In trying to get both of these components wired together, I found that there are very few examples that work with the most recent versions of these components. I also saw examples that could work at a small scale, but don’t show industry-standard best practices, and would lead to performance issues if deployed in an environment with any meaningful traffic.

To that end, I put together this blog post showing how to set up an Azure Functions project in .NET Core 2.2 to integrate with Cosmos DB’s SQL API using its native tooling.

Building a Java Cloud Native Spring Microservice Application on Azure, Part 1

Zach Gardner Azure, Cloud, Java, Microservices, Technology Snapshot Leave a Comment

The big three cloud providers (AWS, Azure, and Google Cloud, in that order) have their various strengths and areas of expertise. Most large organizations though typically pick one cloud provider for their cloud computing needs. This works well if you’re a Java shop that’s on AWS, or a Microsoft shop on Azure. But what if you’re on a large Java project in an organization that wants to use Azure? You’re in luck.

Microsoft Azure has come a long way, and is very supportive of non-Microsoft technologies. The proof though is in the pudding. Which is where this blog post comes in. I take Josh Long’s Bootiful Microservice Services, a great starting point to get a cloud native Spring microservice application up and running, and show how it can be run on Azure.

This first blog post will be all about setting up our basic microservices by walking through the various parts of Josh’s example application, with some best practices and patterns that I’ve found to be effective. Rather than a simplistic ToDo application, we’ll be basing our application off of my favorite bagel shop in New York, Original Bagel Boss in Hicksville, to manage its orders, inventory, etc. If we can run a bagel shop on a Spring application running on Azure, and keep customers happy and full of carbohydrates, then it proves out for applications of a similar size and complexity.

We’ll be staying mostly inside the familiar Java confines, then slowly start working our way out to getting our application deployed to Azure. Then we’ll start introducing additional complexity like Spring Batch jobs, a React front end, etc. A setup this complex will show that Azure is ready for prime time when it comes to running applications in production, even if they are built on non-Microsoft technologies…

Quick Start: AWS SQS + Spring Boot Processing FIFO Queues

Brandon Klimek AWS, Microservices, Spring Boot, Technology Snapshot Leave a Comment

AWS SQS (Simple Queue Service) can provide developers with flexibility and scalability when building microservice application(s). In this quick start tutorial, we will demonstrate how to configure a FIFO queue for a fictional online marketplace.

What Is A FIFO Queue?

A FIFO (first in, first out) queue is used when the order of items or events is critical, or where duplicates items in the queue are not permitted. For example:

– Prevent a user from buying an item that isn’t available on a marketplace.

AWS Amplify GraphQL Queries with TypeScript and Hooks

Mat Warger AWS, JavaScript, React, Technology Snapshot, Tutorial, TypeScript Leave a Comment

I’m a big fan of Amplify. I’m also a big fan of TypeScript. Amplify is not built with TypeScript, and to use it effectively, sometimes you need to give it a little help, especially when it comes to GraphQL. With the advent of hooks, we can create some nice utilities for ourselves that let us leverage the power of TypeScript with our GraphQL queries. Let’s see what that looks like.

I’ll be assuming familiarity with React and TypeScript, i…

Originally posted by Mat Warger on mw.codes April 19, 2019.

AWS Lambda With NestJS

Greg Emerick AWS, JavaScript, Node, Technology Snapshot Leave a Comment

In my previous blog post, I showed running a Spring Boot Java application in AWS Lambda. I discussed the pros and cons of using Java and Spring with Lambda. In this blog post, I’ll cover another Lambda option with NestJS. NestJS provides a framework that is not too different from a typical Spring application. It also addresses some of the negatives of using Java and Spring in a Lambda function.

To recap, AWS Lambda provides low cost compute with zero maintenance. Lambda runs your code on demand, without provisioned and managed servers. Lambda automatically runs and scales your code. You are charged for every 100ms your code executes and the number of times your code is triggered. Lambda has clear cost and maintenance benefits over typical on-premise or EC2 deployments. What does it take to run a Nest application as a Lambda? Does NestJS provide benefits over a Java Spring application?