I thought Per Werngren made some important observations in his recent article for Redmond Channel Partner Magazine. His main point: System Integrators (SIs) need to evolve their business models or risk disintermediation. As workloads are migrated to AWS and Azure, automation replaces the need for people to perform those tasks. This automation enables governance and compliance to standards, while also setting the stage for better downstream, fully-automated management, monitoring and operations. This, of course, further reduces the need for people performing in those roles,
Meanwhile, the new generation of intelligent PaaS services for predictive analytics, artificial intelligence, machine learning, etc. are also replacing jobs once done by hand. These new tools allow us to build better and more intelligent applications.
Despite all this potential for automation, we still regularly see organizations allowing contractors to move workloads manually. It’s simply in a staffing contractor’s best interest to have people do this, despite it being a time-consuming and error-prone process. But why would an SI recommend automation and reduce their long-term revenue? Read More…
The Microsoft Azure team recently announced significant (up to 72%) discounts for customers willing to make one- to three-year reservations. Reserved Instances (RI) are not new, of course – Amazon Web Services (AWS) has had RI for a long time. But are there differences in how the Azure team rolled out RI?
For example: When does it really make sense to use an RI? Can RI discounts be combined with unique offers, like Azure Hybrid Benefit? Can customers cancel their reservation or exchange reserved VM types? What are some of best practices when making these decisions about one-year vs. three-year reservations?
We tried to answer many of these questions in the slide deck below, which we prepared for an internal briefing.
Hope this helps, and please let us know if you have any additional questions in the comments below!
While cloud is fast becoming the “new normal” for government, agencies are still challenged with the daunting task of IT modernization and developing a cohesive cloud migration strategy. Oftentimes, what’s holding back progress is that there simply isn’t a one-size-fits-all cloud playbook. That, combined with agency culture, hinders many agencies from making the move to cloud.
The November #AzureGov Meetup this week brought in both a packed house and a great lineup of government and industry experts who shared their best practices on critical components for cloud success, including: stakeholder engagement, evaluation, planning, implementation, outcomes…and the cultural changes you need to ensure a smooth transition.
We also celebrated the two year anniversary of the #AzureGov Meetup!
(NIST SP 800-53 security controls could be an entire series of blog posts in itself…so if you want to learn more than I cover here, check out NIST’s website.)
The NIST SP 800-53 Rev 4 Azure Blueprint Architecture applies a NIST SP 800-53 Rev 4 compliant architecture with the click of a button to the Azure Government Cloud subscription of your choice. Okay, maybe there are a few clicks with some scripts to prep the environment, but I swear that’s it! This allows organizations to quickly apply a secure baseline architecture build to their DevOps pipeline. They can also add it to their source control themselves to accompany their application source code. (If you want assistance in implementing this within your greater cloud and/or DevOps journey, AIS can help with our Compliance and Security Services offering.) Read More…
Specifically, this application was designed to help analysts get personalized recommendations (based on their own preference settings, ratings provided by their co-workers) for stories they need to analyze as part of their daily work.
The demo included in this video was part of our Ignite talk on cloud innovation with Azure Government. We use CNTK for an image detection problem: Identifying objects within the refrigerator. Image detection is a harder class of problem than image classification, as image detection goes beyond classification to include localization of object(s) within an image. This is the reason for dropping down into the deep learning library. (Earlier in this presentation, Steve Michelotti showed the use of Cognitive API for image classification.)
In a nutshell, we took the Marvel Universe Social Database and loaded it in Azure Cosmos DB as a graph database. Then we built a simple web page that invoked Gremlin queries against Cosmos DB.
The key theme of this demo is the ease with which you can create a globally distributed database that can support low latency queries against the Marvel Universe graph database. In the context of AzureGov (as shown below), we can seamlessly replicate the data across the three AzureGov regions by clicking on these regions within the Azure portal.
Earlier this week, my colleagues and I attended the 2017 Microsoft Government Cloud Forum at the Ronald Reagan building in D.C. This invitation-only event discussed topics such as IT modernization, cybersecurity, mobility, shared services, citizen engagement, and workforce management, all of which are top-of-mind these days for government employees.
AIS spent the day with Microsoft, government leaders and other partners, as we collaborated on how to both innovate and deliver more efficiently and effectively.
Lots of exciting news came out of the event, and we wanted to take a quick second to go over some of the bigger announcements: Read More…