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Posts Tagged "azure"

Why You Shouldn’t Discount Discount Cloud Services Part 2

In the first post of this series, we discussed what a Discount Cloud Instance is and when they are beneficial to use. In this post, we will look at the specific offerings by Amazon (EC2 Spot Instances) and Google (Preemptible VMs) and compare them to Azure’s Low Priority Virtual Machines. In addition to each having a different name, they also treat them in very different ways and have their own individual benefits and drawbacks.
Historical Data
When a provider is willing to provide historical data relative to the availability of their Discount Cloud Instances, it can allow potential users to analyze it for a number of different purposes. Most notably, being able to better time their requests so that they obtain the best pricing when otherwise they might miss their chance. Thus far, Azure does not seem to offer this data. Google…

Microsoft Cloud-Hybrid Integration Roadmap Announcement

Over the past several years, there has been a lack of clarity about Microsoft’s integration roadmap.  Various integration tools have been offered, rebranded and renamed, and ultimately retired.  With a lack of a published roadmap, it is hard to make an informed investment into an integration platform that needs to meet today’s needs and still be relevant into the future.
Since 2000, BizTalk has been around to meet critical on-premises integration needs.  Many customers have implemented complex business-critical solutions based upon BizTalk.   With the migration to the cloud and the advent of Integration Platforms as a Service (iPaaS) offerings, there have been concerns about the future of BizTalk and its role in Microsoft’s integration strategy.
A recent announcement by Microsoft’s Jon Fancey, the Azure Integration Services PM Lead, attempts to clear up some concerns about Microsoft’s integration roadmap and lays the foundation for what…

Five Ways Microsoft Helps you do Amazing Things with Data in the Cloud

1: Build data-driven apps that learn and adapt
Applications show intelligence when they can spot trends, react to events, predict outcomes or recommend choices—often leading to richer customer experiences, improved business process, or addressing issues before they arise. The three key ingredients to creating an intelligent app are:

Ingest data in real time
Query across historical and real-time data
Analyze patterns and make predictions with machine learning

With Azure, you can make your applications intelligent by establishing feedback loops, and applying big data and machine learning techniques to classify, predict, or otherwise analyze explicit and implicit signals. Today, apps for consumers and enterprises can deliver greater customer or business benefit by learning from user behavior and other signals.
Pier 1 Imports launched a mobile-friendly pier1.com, making shopping online easier. It enabled the selection of delivery options like direct shipment, picking up products in the local store,…

Deploying a Site to an Azure VM using Web Deploy

Introduction:
Deploying to an Azure VM is a seemingly simple and easy process, but there are many steps, and thus many places to make mistakes.  Recently I discovered that many, if not all, of the online resources detailing this process are either incomplete or severely outdated.  Here I will outline the configuration and deployment process with up to date information, including instructions pertaining to the new Microsoft Azure Portal.
To get started, you will need a few things that this tutorial does not cover. This tutorial assumes that your Azure VM is already provisioned, deployed, and running IIS (Internet Information Services). The VM should be running Windows Server 2012 R2 or later.  This also assumes that you have administrator access to the Azure Subscription associated with the VM.
Configuring IIS on the Virtual Machine:
First, we’re going to need to install some IIS features.  To assist…

Safeguarding Your Cloud Resources with Azure Security Services

While cloud security continues to be a top concern, Microsoft recently shared insights from a survey that show overall concern has dropped significantly since 2015. They’re now at a stage where half of organizations contend the cloud is more secure than their on-premises infrastructure. In conversations Microsoft has with their customers and partners, they hear increasingly about how using the cloud improves an organizations’ security posture. As many organizations push forward on their digital transformation through increased use of cloud services, understanding the current state of cloud security is essential.
Maintaining a strong security posture for your cloud-based innovation is a shared responsibility between you and your cloud provider. With Microsoft Azure, securing cloud resources is a partnership between Microsoft and their customers, so it’s essential that you understand the comprehensive set of security controls and capabilities available to you on…

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Adding R Packages In Azure ML

The Execute R Script module in Azure Machine Learning is incredibly useful for manipulating data in ways that other modules do not cover. Its functionality can be further expanded by adding R packages that are not included in Azure ML by default. We will first show you how to get a list of packages that are already in your workspace and then how to add additional packages.
Checking Which R Packages are in Your Workspace
Create a new experiment, and place the following R code in an “Execute R Script” module:
data.set <-data.frame(installed.packages());
maml.mapOutputPort(“data.set”);

Run the experiment. The output of the Execute R Script module will be a list of the available packages.
Adding R Packages
Before you can use the package in Azure ML, you need to set up the zip file structure in which ML expects the packages to appear. To do this, start by installing the…

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16 Things Only People Who Work with Azure ML Will Understand

Azure Machine Learning is part of the Cortana Intelligence Suite. It’s a cloud based collaborative drag and drop tool that can be used to build, test, and deploy predictive analytics solutions. We recently worked with Casella Waste Systems to analyze their customer and sales data using Azure ML. We found Azure ML to be a useful tool that allowed us to visualize our work and avoid coding when it wasn’t necessary. However, the process of creating successful experiments didn’t come without some speed bumps. Here are some things that we discovered along our ML journey, delivered in the spirit of a Buzzfeed article.
1. Your experiment starts out nice and simple

2. And ends up looking like this

3. You have multiple people working on an experiment

 
4. But you see this when everyone tries to edit the experiment at the same time

All that…

Mobile-first, cloud-first makes Microsoft a Leader in the Gartner Magic Quadrant for Mobile Application Development Platforms

In the few months since Microsoft acquired Xamarin, Scott Guthrie and Nat Friedman have laid out our roadmap that builds on the complementary strengths in mobile development and cloud services that made our companies great partners for years. Microsoft is excited to report that Visual Studio with Xamarin plus Azure is working. They have already seen a massive upswing in developer participation, and they’re receiving validation from outside the developer community, as well.
Yesterday, Gartner recognized Microsoft as a Leader in its 2016 Magic Quadrant for Mobile Application Development Platforms. The designation reflects the fact that Microsoft’s Mobile Application Development Platform vision has expanded dramatically, evidenced by the Xamarin integration, enhancements to Azure App Service, and improved mobile DevOps capabilities.
Over the past year Microsoft has made incredible progress toward their vison of “Any developer, any app, any platform.” Developers need to balance the efficiency of a full-stack solution with the flexibility…

Setting Up Automated Azure IaaS VM Shutdown

The Tallan Integration Practice heavily utilizes Azure Infrastructure as a Service (IaaS) virtual machines for quickly setting up isolated environments for prototypes and BizTalk development environments.  However, with so many virtual machines it is often difficult to remember to shut them off when not needed.  With Azure‘s Automation features, we can setup a scheduled job to shut down non mission critical VM’s, saving on hosting costs.

Sending a Message to an Azure Service Bus Queue Using Dell Boomi

Today we will be going over how to send a message from a Dell Boomi process to an Azure Service Bus queue, and then read that message off the queue, again in a Dell Boomi process.
In Boomi, we can interact with the Service Bus via simple HTTP Post. We will be calling these with the HTTP Connector shape in our Dell Boomi process, from there we will be able to construct our request in full. Then we will show that we can find the message in our queue.

Setting up the Process
Start off by creating a new process in the Atomsphere dashboard and give it an associated name, then click create:

This will bring up our blank process. It will prompt us to setup the Start Shape, select “No Data”, we will be manually creating a sample message for the time being….

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