Interactive analysis have become a major part of the field of Data Science. Two tools have become very popular, Jupyter and Zeppelin.
This article will show you how to provision a Spark cluster and run analysis on it with the help of Zeppelin.
The Internet of Things (IoT) has finally arrived (some time ago). An important part is to analyze sensor data in motion. For that a streaming system is necessary. You could use Apache Storm or Apache Spark Streaming to do that, but if you want to run it as a service on Azure without going through the pain to set up a cluster Azure Stream Analytics is a good choice.
In this post I’m going through the basics of Azure Stream Analytics and DocumentDB, which is used as a destination for our data after the streaming is done, and how you can create a simple Stream Analytics job using Blob storage as the input and DocumentDB as the output.
Continous delivery (or continuous deployment or continuous integration) is an important part of the modern software development lifecycle.
Azure WebJobs on the other hand is a nice little feature to run processes in the background.
This article describes in short why continuous delivery is a good thing, what Azure WebJobs are and how you can use both together.
Over a year ago a friend of mine aroused my interest for RethinkDB. At that time I played a little bit with it and thought that it appears to be a nice database. After that I focused on other topics, but recently I came back to RethinkDB. In this post I would like to explain how you can setup RethinkDB on Azure and play around with it.
DocumentDB is the latest storage option available on Azure. During the last weeks I had the opportunity to play with it and give some presentations about it. This article will introduce you to this new service.
Probably you already have heard about Cloud9 and have done some development of it. Maybe it is your favorite IDE. Before I actually go on I have to admit that Cloud9 is not my personal favorite. For Node.js and plane HTML projects I use WebMatrix and Visual Studio with the Python Tools installed comes handy for Python projects. But that is the point! I use two different IDEs, which in this case works nicely together, but that must not be the situation in every development environment.
Some days ago I watched the Introduction to Node.js from Paul O’Fallon and he is using Cloud9 throughout the whole course and I was impressed about what you can actually do with it. Literally years after I have used Cloud9 for the first time it was time to give it another try. In this post I am going to talk about the capabilities Cloud9 has and my experiences with it.
Recently I have done some research about HTML local storage and the offline functionality for websites in preparation for a project. In this article I want to share my experience with you. All of the content discussed in this article was tested in Google Chrome 27, Firefox 22, and Internet Explorer 10.
This article will only show some aspects. For more information and examples have a look at the literature listed beneath.
In the past native applications had some capabilities which were missing in the web area. One of this capabilities was to store data on the client. A solution for this problem was the usage of cookies. This solution introduced some problems, especially if you have security in mind. An alternative proposed by the World Wide Web Consortium (W3C) is called Web Storage. In this section I want to discuss some of the basics of one approach coming from the Web Storage proposal: local storage. Local storage, which is sometimes referred to as DOM Storage, is a simple persistent key-value storage directly in the browser. An important advantage of local storage is that it is natively implemented in browsers, which means that it is available even when external plug-ins are not.