Anthony Chu

One of the promises of serverless computing is automatic scaling based on load. I decided to run some HTTP load tests on Azure Functions to see how well it scales. In particular, how many instances does the function app scale out to? How does load affect response times and throughput? How stable is Azure Functions as it scales out?

Before we begin, I want to point out that this is by no means a scientific test. Take the results with a giant grain of salt.

Azure API Management comes with a rich set of built-in analytics to gain insight into the APIs' activities, such as usage by user, APIs, operations, and geography. But there are times when we want to perform custom queries over the activities. For this, API Management allows us to log API activities to Event Hubs.

Once the logs are flowing through Event Hubs, there are many ways we can use the data. For instance, we can save the logs into a Table Storage using Azure Functions and query it with Power BI; or we can process the live stream using Stream Analytics.

Today, we'll look at how to use Event Hubs Archive to automatically save the logs into Blob Storage. And we'll query the logs from Blob Storage using Data Lake Analytics.

I've already written an article with details on how to turn on Event Hubs Archive and query it using U-SQL with Data Lake Analytics. I won't repeat some of those details; instead I'll focus on how to use these tools with Azure API Management.

Inserting entities into Table Storage from Azure Functions is a breeze with the Azure Table Storage output bindings. However, the bindings don't directly support updating and deleting entities (yet).

But it's actually pretty easy to support updates and deletes. In C#, this can be done using the Table Storage output binding with a CloudTable parameter. In Node/JavaScript, we can use the azure-storage NPM package.

The other day I was helping someone with a PHP application running in Apache. Not having worked with PHP for a long time, I didn't have a proper LAMP stack development environment set up. Thankfully, Docker makes it easy to work with PHP and Apache without having to install them on my local machine.

These instructions should work on both Windows and macOS.

A year ago, if someone had told me that I would speak at a conference, become a Microsoft MVP, and meet a bunch of people I look up to, I would not have believed them. But in 2016, all those things happened, and more! It was easily the best year I've had so far in my career.

Microsoft MVP

In January, Shaun Luttin messaged me out of the blue and offered to nominate me for a Microsoft MVP Award. That simple message was probably what started a chain of events that led to this amazing year.

Through some hard work and help from a few people, I received an MVP Award in Azure in July. The recognition and free stuff were great, but my favourite part about being an MVP so far has been the awesome people I've met and the friends I've made. I'm so honoured to be a part of this community.