Author : All posts by ilikesql

12

Dec

Know exactly how much it will cost for enabling DR to your Azure VMs

Azure offers built-in disaster recovery (DR) solution for Azure Virtual Machines through Azure Site Recovery (ASR). In addition to the broadest global coverage, Azure has the most comprehensive resiliency strategy in the industry from mitigating rack level failures with Availability Sets and data center failures with Availability Zones to protecting against large-scale events with failover to separate regions with ASR. A common question we get is about costs associated with configuring DR for Azure virtual machines. We have listened and prioritized.

Configuring disaster recovery for Azure VMs using ASR will incur the following charges.

ASR licensing cost per VM. Network egress costs to replicate data changes from the source VM disks to another Azure region. ASR uses built-in compression to reduce the data transfer requirements by approximately 60 percent. Storage costs on the recovery site. This is typically the same as the source region storage plus any additional storage needed to maintain the recovery points as snapshots for recovery.

You can look at this sample cost calculator for estimating DR costs for a three-tier application using six virtual machines. All of the services are pre-configured in the cost calculator. The six virtual machines have 12 Standard SSD disks and 6

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12

Dec

Taking a closer look at Python support for Azure Functions
Taking a closer look at Python support for Azure Functions

Azure Functions provides a powerful programming model for accelerated development and serverless hosting of event-driven applications. Ever since we announced the general availability of the Azure Functions 2.0 runtime, support for Python has been one of our top requests. At Microsoft Connect() last week, we announced the public preview of Python support in Azure Functions. This post gives an overview of the newly introduced experiences and capabilities made available through this feature.

What’s in this release?

With this release, you can now develop your Functions using Python 3.6, based on the open-source Functions 2.0 runtime and publish them to a Consumption plan (pay-per-execution model) in Azure. Python is a great fit for data manipulation, machine learning, scripting, and automation scenarios. Building these solutions using serverless Azure Functions can take away the burden of managing the underlying infrastructure, so you can move fast and actually focus on the differentiating business logic of your applications. Keep reading to find more details about the newly announced features and dev experiences for Python Functions.

Powerful programming model

The programming model is designed to provide a seamless and familiar experience for Python developers, so you can import existing .py scripts and modules, and quickly start

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12

Dec

How smart buildings can help combat climate change
How smart buildings can help combat climate change

The Internet of Things (IoT) is changing the way governments and organizations tackle some of humanity’s thorniest challenges. In this three-part series, we looked first at common issues leaders must address to drive digital transformation in their cities. Next, we’ll be focusing on exciting, major applications of IoT. This post focuses on combatting climate change with technology, and a companion piece highlights advances in disaster management

With rising temperatures, extreme weather events, and other environmental impacts, signs of climate change are on the rise. Scientists are now warning that global temperatures are accelerating past the goal of the 2015 Paris Agreement (an increase of no more than 1.5°C to 2°C) and are expected to climb an average 3.2°C globally by 2100 if unchecked. In addition, significant demographic shifts are driving parallel impacts. The world’s population is anticipated to soar from 7.6 billion to 9.8 billion by 2050, with 70 percent living in urban areas.

Fast-paced urbanization will require large cites to maintain an uninterrupted supply of energy to power food and water production, transportation, residential and commercial life, and health and human services, all of which occurs in and around buildings. In fact, buildings and construction currently account for

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12

Dec

How news platforms can improve uptake with Microsoft Azure’s Video AI service

I’m Anna Thomas, an Applied Data Scientist within Microsoft Engineering. My goals are to enable the field and partners to better integrate various AI tools into their applications. Recently, my team reached out to Microsoft News to see how they’re analyzing their data, and how our services may be able to help.

Microsoft News ingests more than 100,000 articles and videos every day from various news providers. With so many different aspects such as classifying news topics, tagging and translating content, I was immediately interested in understanding how they process all of that information.

As it turns out, Microsoft News has been working on some pretty advanced algorithms that analyze their articles and determine how to increase personalization, which ultimately increases consumption, for years. However, when I asked them if there were any gaps, they were quick to answer that they would love more insight on their videos.

Analyzing videos at scale to obtain insights is a nontrivial task. Having insights on videos, especially for a news platform, can help with increasing search quality, user engagement through personalization, and the accessibility of videos through captioning, translating, and more. There are so many different aspects related to this: classifying different news

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12

Dec

Extracting insights from IoT data using the warm path data flow

This blog continues our coverage of the solution guide published by Microsoft’s Industry Experiences team. The guide includes the following components:

Ingesting data Hot path processing Cold path processing Analytics clients

We already covered the recommendation for processing data for an IoT application in the solution guide and suggested using Lambda architecture for data flow. To reiterate the data paths:

A batch layer (cold path) stores all incoming data in its raw form and performs batch processing on the data. The result of this processing is stored as a batch view. It is a slow-processing pipeline, executing complex analysis, combining data from multiple sources over a longer period (such as hours or days), and generating new information such as reports, and machine learning models, etc. A speed layer and a serving layer (warm path) analyze data in real time. This layer is designed for low latency, at the expense of accuracy. It is a faster-processing pipeline that archives and displays incoming messages, and analyzes these records, generating short-term critical information and actions such as alarms.

This blog post covers the warm path processing components of the solution guide.

Azure Event Hubs is a big data streaming platform and event

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11

Dec

Power BI Desktop December 2018 Feature Summary
Power BI Desktop December 2018 Feature Summary

https://powerbi.microsoft.com/en-us/blog/power-bi-desktop-december-2018-feature-summary/Source: https://powerbi.microsoft.com/en-us/blog/power-bi-desktop-december-2018-feature-summary/           December is a huge month for us in terms of accessibility. With this release, the entire product is completely accessible for both report consumption and report creation. We are also previewing one of READ MORE

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11

Dec

Native Python support on Azure App Service on Linux: new public preview!

We’re excited to officially announce the public preview of the built-in Python images for Azure App Service on Linux, a much requested feature by our customers. Developers can get started today deploying Python Web Apps to the cloud, on a fully-managed environment running on top of the Linux operating system.

This new preview runtime adds to a list of growing stacks supported by Azure App Service on Linux, which includes also Node.js, .NET Core, PHP, Java SE, Tomcat, and Ruby. With the choice of Python 3.7, 3.6 and soon 2.7, developers can get started quickly and deploy Python applications to the cloud, including Django and Flask, and leverage the full suite of features of Azure App Service on Linux. This includes support for deployments via “git push”, and the ability to deploy and debug live applications using Visual Studio Code (our free and open source editor for macOS, Linux, and Windows).

When you use the official images for Python on App Service on Linux, the platform automatically installs the dependencies specified in the requirements.txt​ file. Additionally, it detects common Flask and Django application structures and hosts them using gunicorn, and includes the necessary modules for connecting to Azure DB for

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11

Dec

Azure Monitor for containers now generally available
Azure Monitor for containers now generally available

We are happy to announce that Azure Monitor for containers is now generally available. Azure Monitor for containers monitors the health and performance of Kubernetes clusters hosted on Azure Kubernetes Service (AKS). Since the launch of the public preview at Build in May 2018, we have seen a lot of excitement from customers. Customers love the fact that you can enable monitoring as soon as you create an AKS cluster and get all the monitoring telemetry in a centralized location in Azure without having to login to containers or rely on other tools. Since the public preview, we have been adding more capabilities and refining the experience based on your feedback. Let’s look at some of the recent changes.

Multi-cluster view – You often have multiple AKS clusters to manage. Wouldn’t it be great to view and manage all your clusters together? The multi-cluster view discovers all AKS clusters across subscriptions, resource group, and workspaces, and provides you a health roll up view. You can even discover clusters that aren’t being monitored and with just few clicks start monitoring them. 

Drill down further into AKS cluster with Performance Grid view – To investigate further, you can drill down to

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11

Dec

KubeCon North America 2018: Serverless Kubernetes and community led innovation!

Welcome to KubeCon North America 2018, and welcome to Seattle. It’s amazing to get the chance to welcome you to my hometown, and the site of Kubernetes birth. It was barely five years ago that Joe, Craig, and I had the first small ideas and demos that eventually turned into the amazing project and community. I’m honored that all of you over the years have chosen to invest your time, energy, and enthusiasm in Kubernetes, whether this is your first KubeCon or you’ve been here since the first one in San Francisco four years ago, welcome!

For the Azure Kubernetes team, KubeCon is especially exciting. It’s been a busy and fulfilling year, Azure Kubernetes Service (AKS) has been the fastest growing service in the history of Azure Compute, that’s been quite a ride! With KubeCon here, it’s a great chance to meet up with our customers and community collaborators to celebrate all the incredible things.

For the Azure Kubernetes Service, we started with the journey of “how to make Kubernetes easier for our customers.” For example, by letting Azure take care of deployment, operations, and management of Kubernetes APIs and leveraging integrated tools, Maersk was able to free their engineers

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11

Dec

A hybrid approach to Kubernetes
A hybrid approach to Kubernetes

We’re excited to see everyone at Kubecon this week! We’ve been working with our customers to understand how they’re thinking about Kubernetes and what we can do to make it easier for them. Azure Stack unleashes new hybrid capabilities for developing applications. You design, develop, and maintain your applications just like you do with Azure and you can deploy to any of the Azure clouds. Your application’s location becomes a configuration parameter rather than a design constraint.

So how does Azure Stack work with containers exactly? The way that containers and hybrid cloud work together can allow you to solve many problems. You can create a set of apps in containers using the languages you love like NodeJS, Python, Ruby, and many others. You can also take advantage of the wide array of tooling available, including Visual Studio Code. You can deploy your container or set of containers to a mix of environments that meet your user’s requirements. For instance, you can keep your sensitive data local in Azure Stack and access current functionality such as Azure Cognitive Services in global Azure. Or you can develop your apps in global Azure where you developers are and then deploy the containerized

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