I’ve recently started using Codealike, a service that tracks various metrics while I’m coding. The data it collects is then presented in a bunch of really useful ways to help determine when I’m being most productive, as well as the places our code base I spend most of my time and various other things. One of the metrics they calculate as part of this process is how “focused” you are and from this they determine whether or not someone should interrupt you - they have three different levels, No Activity, Can Interrupt and Cannot Interrupt.

At DrDoctor we’ve been using Nancy as our web framework for quite sometime now. We’ve found it to have many advantages over ASP.Net MVC (we still have one legacy ASP.Net MVC site running) as well as excellent community support. Recently we started using New Relic to monitor the performance of our web applications. However I was a bit disappointed when I was first looking at the data it collected and saw this

If you haven’t tried NCrunch before then stop reading this and go download the trial and try it out, it will forever change your testing habits* - for the better. NCrunch is the breakfast of champions -KenR At DrDoctor we use Nancy (rather than the typically used ASP.Net MVC Framework) the main reason is summed up by the overall goal of the framework: The goal of the framework is to stay out of the way as much as possible and provide a super-duper-happy-path to all interactions.

I recently came across this brilliant quote while reading the Klarna engineering blog and thought it was worth posting. If development is frequently called in the middle of the night, automation is the likely outcome. If operations is frequently called, the usual reaction is to grow the operations team. -James Hamilton (source)

In my last post I gave a high level overview of the CallStats proof-of-concept app that I built using Azure Stream Analytics, in this post I’m going to explain how to get it running for yourself. Prerequisites You will need an Azure subscription with the Stream Analytics preview enabled. Setting up Service Bus The first step is to configure some Event Hubs, these will be the ingest and output for Stream Analytics.

There have been a number of new Azure services announced in recent weeks, one that caught my eye was Azure Stream Analytics. Stream Analytics is a cloud based event processing engine, which ingests real time events from various sources, runs a temporal query and then outputs the results for you to consume or to store for later analysis. The feature set currently available is a simplified version of StreamInsight, the on-premise predecessor.