We just introduced The Bluemix Developer Console. Extending the current Bluemix Mobile Dashboard, this new experience goes beyond mobile and introduces new tools for quickly creating Cloud Native applications across web, mobile and backend. They aim to greatly cut down on development time by generating application starters with all the necessary boilerplate, build and configuration code, so that developers can start coding business logic faster.
For many developers, the Hello World starter applications on Bluemix are too basic and the sample applications on IBM-Bluemix.github.io page are a bit too advanced. If you agree with this, you'll find our recently released Runtime Getting Started guides extremely helpful.
The IBM Bluemix platform is home to an ever growing number of cognitive computing services that, as developers, we can use in our applications to learn more about our data. Earlier this year fellow Twilio developer evangelist Ricky Robinett showed us how combining Watson’s question and answer API, Twilio and Node.js could get us answers to health questions. Also living under the Watson banner, AlchemyAPI is a set of services for understanding content and context within text and images. Today we're going to look into analysing the sentiment of text messages using one of the AlchemyAPI services hosted on Bluemix. We'll build up an application that receives SMS messages and deals with them differently based on the sentiment in the message.
Many web services require consumers to specify known IP addresses that their requests will originate from to prevent abuse and attacks from the wider Internet. This is commonly referred to as "IP whitelisting". Due to the scalable nature of Bluemix, the IP address of your Bluemix app will frequently change as you deploy and scale making it impossible to guarantee your IP address ahead of time. Statica solves this problem by offering a proxy service with guaranteed static IP addresses.
MQ Light provides clients in Ruby, Python, Node.js, and Liberty for Java. The sample applications make it easy to get started. The sample app demonstrates how MQ Light can help with a "worker offload" pattern.
To call attention to popular articles on Bluemix available on IBM developerWorks, this weekly post will introduce three "best of" articles. This week's entry focuses on the top 10 apps, securing your application with social media authentication, and developing applications at the speed of Bluemix.
Here are come tips and tricks for migrating your Ruby On Rails app to Bluemix. They include a couple code tweaks as well as including some best practices.
The challenge with analytics has been two fold. First, the computational load resulted in processing subsets of data with tremendous hardware overheads. Secondly, it took a data scientist weeks, months, or years to give you useful analysis. The Bluemix team was excited to see a demonstration of IBM Blu Acceleration technology that made it possible to do on-the-fly analytics surfaced on a mobile application.