Transient exception handling and retry logic are considered an important defensive programming practice, especially in the public cloud. But how good is your exception handling? Unfortunately, it’s not always easy to simulate transient exceptions.

Consider the Azure Redis Service for example. It does not have a way to simulate failures. So we decided to create our own Chaos Redis library. Fortunately, Microsoft has developed a Windows port of Redis Cache.

We decided to modify the code so we can inject chaos. Read More…

It’s 2017 and it’s official: Government agencies want to move to the cloud. But they are often unprepared for the transition, or stuck in the middle of a confusing process. So this week, AIS and Microsoft kicked off the new year with a terrific AzureGov Meetup full of valuable information, training resources and demos on exactly where and how to start a successful government cloud journey.

The full line-up of cloud experts includied David Simsik, Cloud Practice Manager at AcceleraDan Patrick, Chief Cloud Strategist at OpsgilityBrian Harrison, Cloud Solution Architect at Microsoft, and AIS’ own Vishwas Lele, who presented a demo of the AIS Service Catalog offering, which is specifically designed to ease cloud adoption for government agencies.

See below for some photos of this (packed!) event and a video of Vishwas’ Service Offering presentation. For future DC AzureGov Meetup dates and details, go here. We hope to see you next time!

(Check out our Cloud Adoption Framework for more on how AIS can take you step-by-step through the Cloud Journey here.)

At a recent holiday dinner, a conversation with a friend eventually progressed to the topics of self-driving cars and facial-recognition software – and the overall roles and capabilities of artificial intelligence (AI). My friend’s assertion was that “AI is ultimately about pattern matching.” In essence, you equip the AI with a library of “patterns” and their corresponding associated actions. Based on the input it receives from the real world, the AI software program will then make an attempt to match the input to a stored pattern and execute the corresponding associated action.

Of course any program, regardless of whether it is designed to steer a car or detect a face in an image, relies on pattern-matching at the lowest level. That said, as we will see shortly, a deep learning-based approach is a fundamentally different way to solve the problem. And it’s an approach that is poised to reinvent computing. Read More…

With the explosion of new sensors and service offerings producing geospatial telemetry, there’s an ever-increasing need for tools to gain business insights from this data. One of the premier tools for this in the geospatial domain is GeoServer.

Fully open-source and free to use, GeoServer provides Open Geospatial Consortium (OGC) web service interfaces to rendering images or complete metadata in most common geospatial interchange formats. In a consulting capacity, Applied Information Sciences has leveraged Geoserver with great success, allowing us to deploy a complete software stack in minutes instead days or weeks. In this post I’ll give an overview of the DevOps practices we’ve applied to enable this capability, as well as a brief overview of the supporting technologies. Read More…

AIS recently worked with the General Services Administration (GSA) Technology Transformation Services Division, better known as 18F.  The engagement involved working with 18F to digitize the Department of Labor’s Section 14(c) certification application process (part of the Fair Labor Standards Act). This is currently a paper-based process that 18F hoped to modernize as an intuitive, online application…and to do it using agile methodologies.

AIS was tasked with building the first version of the digital form within a 60-day period of performance – much shorter than typical federal contracts.  AIS pulled together a multi-disciplinary team comprised of user researchers, designers, and front- and back-end web developers to work closely with 18F and the Department of Labor (DOL) Product Owner. The team built the entire form with complex validation along with a registration and login and an administrative section to process the form applications. They performed multiple usability tests with actual end users, and followed 18F’s principles of working in the open using a public GitHub repository. All User Stories and discussion threads were thoroughly documented in that repository’s issues list.

AIS was able to work together with many divisions inside DOL to make this happen.  We addressed security concerns by the Chief Information Security Officer (CISO) and worked with the CIO office to coordinate delivery of the application and a testing and staging environment for deployment. We also set up a Continuous Integration/Continuous Deployment process so that multiple DOL stakeholders could stay abreast of what was happening and exercise the existing application state.  We were even able to address legal concerns with testing by external citizens by getting signed consent forms for testing and recording the sessions.

The collaboration was so successful that our client wrote their own blog post on the project, detailing exactly “how government and private industry can work together using agile methodologies to produce great results.” You can read it here. 

These types of successful, agile engagements break down the myths that software development for the government needs to take months (or even years). Government can and will move faster, and after every small win like this project, the traditional methods of building software and procuring software development are changing across the industry.  This bodes well not just for the citizens who need to interact with these digital services… but also for saving our tax dollars.

Companies are adopting Docker containers at a remarkable pace and for a good reason – Docker containers are turning out to be key enablers for a micro-services based architecture.

As a quick recap, Docker containers are:

  • Encapsulated, deployable components that can run as isolated instances
  • Small in size with a fast boot-up time
  • Include tools that enable containerized application images to be easily moved across the public cloud and on-premises
  • Capable of applying limits on physical resources consumed by any given application

Given the popularity of Docker containers, it should come as no surprise that the Azure platform already provides first-class support for a container hosting solution, in the form of Azure Container Service (ACS). ACS makes it simple to create a cluster of Virtual Machines that can run containerized applications. ACS relies on popular open-source tools – with Docker as the container format, and a choice of Marathon, DC/OS, Docker Swarm and Kubernetes for orchestration and scheduling, etc. All this makes it possible to easily run containerized workloads on Azure in a portable manner.

But the Docker containerization story on Azure does not stop here.

It is also being weaved more and more into existing PaaS offerings, including Azure Batch, Azure App Service and Azure Service Fabric. Let’s briefly review the latest developments to see how Docker integrates with Azure PaaS: Read More…