Securely manage and autofill passwords across all your mobile devices with Microsoft Authenticator

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

Howdy folks,

Today we are announcing the general availability of password management and autofill capability in the Microsoft Authenticator app. Ever since we announced the public preview, we’ve seen a lot of interest among both enterprises and individual users. Users love the convenience of the Authenticator app syncing and autofilling their strong passwords for all their identities even as they move across devices – mobile or desktop. On desktops, you can autofill these passwords using either Microsoft Edge or Google Chrome extension.

The passwords are saved as part of your personal Microsoft account and they are encrypted both on the device as well as in the cloud. In addition, every password autofill from the Authenticator requires the same bio-gesture you provide for sign-ins, enforcing a multi-factor authentication.

Since the public preview, we have made a few additional changes to this feature:

• Enable autofill even when a work account is added to the Authenticator – During the preview, the autofill feature was disabled if a work account was configured in the Authenticator app. Based on your feedback, we have now allowed this Microsoft account-based capability for your users even when they have a work account in the Authenticator app. Enterprises can request this feature to be disabled on Authenticator apps that have work or school accounts added.


• Passwords import – We also saw a lot of interest for importing existing passwords from your other password solutions. We have added support for importing passwords from Google Chrome and select password managers.

Autofill is rolling out in Authenticator app on iOS (iOS 12.0+) and Android (Android 6.0+). To learn more about the autofill feature, visit our FAQs page.

As always, we’d love to hear from you. Please let us know what you think in the comments below or on the Azure AD feedback forum. 

Best regards,

Alex Simons (@Alex_A_Simons)

Corporate VP of Program Management

Microsoft Identity Division

Reinforcement learning in Minecraft: Challenges and opportunities in multiplayer games

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

How to set Spark / Pyspark custom configs in Synapse Workspace spark pool

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

In Azure Synapse, system configurations of spark pool look like below, where the number of executors, vcores, memory is defined by default.

There could be the requirement of few users who want to manipulate the number of executors or memory assigned to a spark session during execution time.

Usually, we can reconfigure them by traversing to the Spark pool on Azure Portal and set the configurations in the spark pool by uploading text file which looks like this:

But in the Synapse spark pool, few of these user-defined configurations get overridden by the default value of the Spark pool.

What should be the next step to persist these configurations at the spark pool Session level?

For notebooks

If we want to set config of a session with more than the executors defined at the system level (in this case there are 2 executors as we saw above), we need to write below sample code to populate the session with 4 executors. This sample code helps to logically get more executors for a session.

Execute the below code to confirm that the number of executors is the same as defined in the session which is 4 :

In the sparkUI you can also see these executors if you want to cross verify :

A list of many session configs is briefed here . 

We can also setup the desired session-level configuration in Apache Spark Job definition :

For Apache Spark Job:

If we want to add those configurations to our job, we have to set them when we initialize the Spark session or Spark context, for example for a PySpark job:

Spark Session:

from pyspark.sql import SparkSession

if __name__ == “__main__”:

      # create Spark session with necessary configuration

      spark = SparkSession

    .builder

    .appName(“testApp”)

    .config(“spark.executor.instances”,”4″)

    .config(“spark.executor.cores”,”4″)

    .getOrCreate()

Spark Context:

from pyspark import SparkContext, SparkConf

if __name__ == “__main__”:

      # create Spark context with necessary configuration

      conf = SparkConf().setAppName(“testApp”).set(“spark.hadoop.validateOutputSpecs”, “false”).set(“spark.executor.cores”,”4″).set(“spark.executor.instances”,”4″)

      spark = SparkContext(conf=conf)

Hope this helps you to configure a job/notebook as per your convenience with the number of executors.

Integrating AI: Best Practices and Resources to Get Started

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

We use AI (Artificial Intelligence) integrated applications daily, from search engines optimized to find the most relevant content, to recommendation engines for streaming or shopping. During AI’s early years rising to popularity, improving applications with AI was only possible for companies with big budgets dedicated to research and experts, preventing companies that cannot effort an AI team to compete. Today AI is readily available for any product, without having to invest in research and development. There are open-source libraries that help you train Machine Learning models like TensorFlow. With a fraction of the effort and a little bit of cost, AI services are available to easily integrate into your applications, with pre-trained models and ways to train custom models for your specific use case. In Integrating AI series, I aim to help you decide if and how to integrate AI into your applications, get you started with Azure’s ready to use AI solutions, Cognitive Services and answer your most frequent questions when getting started.

Let’s start with these fundamental questions: 

• What are the problems you can solve with AI?


• What do you need to know before starting to build your solution?


• How do you measure the success of your new AI features? 

What are the problems you can solve with AI? 

AI is a groundbreaking technology but not a magical solution for everything. It is important to know if you are adding value or solving an actual user problem. There are complex products like Wikipedia and Reddit that have a lot of information but use crowdsourcing and simple search to cater to unique needs without the help of AI. To make an informed decision, you need to start with your users’ needs. What are the problems they face? Is there a process that you can automize like filling expense forms that can be automated with Form Recognizer service? Send voice messages to your customers with updates using Speech Services? Do they make complex choices while using your product that could be customized to your users with the use of Personalizer? Do you need to improve the usability of your application with voice interactions and Language Understanding? It is important to solve a real need for your users instead of assuming the solution that will be useful. User research is the best way to figure out the issues and a lot can be surfaced by user analytics. You can use Metrics Advisor AI service to detect anomalies and figure out future AI solutions as well.  

Once you have a clear definition of the problem and define how to measure success, it is time to explore practical solutions.  

Most AI solutions can fall into two categories. The first major use case for AI is automating the mindless repetitive jobs. If the users of an expense report or a hiring application need to type in information from a form or a receipt to your system, it is easily automated by OCR (Optical Character Recognition). Similar automations are possible for close captioning, translation, classifying images and automizing alert messages.  

The second category of AI solutions can be categorized as complex human decisions based on data. You could give your friends recommendations on what to watch next easily, knowing what they like, what they don’t like. For example, a streaming service with thousands of movies to choose from, cannot surface relevant content with simple filtering of the genres or release dates. It would take forever to choose what to watch by browsing unless you know the exact name of the movie. For a decision like recommendation among thousands or millions of results, AI might be better at recommending to your best friend, maybe even better than you over time. Understanding the language and intent of people is another example. A human can understand and classify a review as positive or negative easily. For machines to detect the same emotions, you must do more than detect certain words to get sentiment. 

What do you need to know before starting to build your solution? 

 
Some problems are easier to solve than others with AI. Experimenting with different tools to confirming your solutions is important. All the Cognitive services are easy to try out and here is how to do that: 

• AI Demos Website gives you a hand-on experience of Cognitive Services

• You can also download the Intelligent Kiosk app to try out the demos on your local machine.

Will your users love your solution? 

Scaling an application and polishing the user experience takes most of the development time. It is better to try out features fast and adjust before making the investment in perfecting the wrong experience. You might assume an application flow that users are going to interact, but users can surprise you in their own creative ways of using your tools. Prototype your applications quickly and get user feedback early on. 

Power platform is one of the tools that allows you to create mobile apps that integrates important AI capabilities without writing any code. With power platform, you can easily deploy and share your prototypes, without leaving the platform’s UI. After the free trial period, both training and using your AI models will cost but not as much as the development time of an actual app with AI and having to make major changes after the release. Check out some of the capabilities and use cases of AI Builder on Power Platform and how to train a custom vision model and creating a mobile app on Power Platform in this article.

There are other fast and easy options to add AI to your applications, without a big development investment, especially if you are adding the capabilities to an existing application. You can use a logic app to design an application on Azure platform to find twitter mentions of your brand and analyze the sentiment of the tweets. You can visualize the data on Power BI or your choice of visualization platform or tools.  

Once you integrate your AI solution, you can make the new AI features to a limited group of users and compare the effectiveness of your solution with your non-AI features. 

Start your learning journey on AI Developer resources and sign up for a free Azure Account. Sign up for a free account.

Let us know the problems you are trying to solve and your specific use cases on the comments below.  

Friday Five: Teams Power Automate, Dynamics Deep Dive, More!

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

Dynamics is Weird

Kylie Kiser is a Power Platform enthusiast and two-time Business Applications MVP who has been working with Microsoft technologies for over 10 years. Kylie is passionate about the community and shows this through blogging, presenting, and hosting events. Further, she leads a thriving user group based in Washington, DC. For more, check out Kylie’s Twitter @KylieKiser

MSIX app attach WVD integration, my first test drive!

Freek Berson is an Infrastructure specialist at Wortell, a system integrator company based in the Netherlands. Here he focuses on End User Computing and related technologies, mostly on the Microsoft platform. He is also a managing consultant at rdsgurus.com. He maintains his personal blog at themicrosoftplatform.net where he writes articles related to Remote Desktop Services, Azure and other Microsoft technologies. An MVP since 2011, Freek is also an active moderator on TechNet Forum and contributor to Microsoft TechNet Wiki. He speaks at conferences including BriForum, E2EVC and ExpertsLive. Join his RDS Group on Linked-In here. Follow him on Twitter @fberson

How to easily use new Teams Power Automate application to increase personal and team productivity (aka creating flows without having to know how)

Vesku Nopanen is a Principal Consultant in Office 365 and Modern Work and passionate about Microsoft Teams. He helps and coaches customers to find benefits and value when adopting new tools, methods, ways or working and practices into daily work-life equation. He focuses especially on Microsoft Teams and how it can change organizations’ work. He lives in Turku, Finland. Follow him on Twitter: @Vesanopanen

ASP.NET CORE MVC: IMPORT/EXPORT CSV FILE

Asma Khalid is an Entrepreneur, ISV, Product Manager, Full Stack .Net Expert, Community Speaker, Contributor, and Aspiring YouTuber. Asma counts more than 7 years of hands-on experience in Leading, Developing & Managing IT related projects and products as an IT industry professional. Asma is the first woman from Pakistan to receive the MVP award three times, and the first to receive C-sharp corner online developer community MVP award four times. See her blog here.

Teams Real Simple with Pictures: Building a Call Queue

Chris Hoard is a Microsoft Certified Trainer Regional Lead (MCT RL), Educator (MCEd) and Teams MVP. With over 10 years of cloud computing experience, he is currently building an education practice for Vuzion (Tier 2 UK CSP). His focus areas are Microsoft Teams, Microsoft 365 and entry-level Azure. Follow Chris on Twitter at @Microsoft365Pro and check out his blog here.

New feature announcement: Data landing page

by Contributed | Feb 5, 2021 | Technology

This article is contributed. See the original author and article here.

New Data landing page which collect all One Click capabilities (ingestion, create table and (soon to come) create external table)  in one place.

1. Open Kusto Web Explorer 


2. Click on Data at the left side of the page 


3. Select one of the create or ingest functions