MSTICPy and Jupyter Notebooks in Azure Sentinel, an update

by Contributed | Apr 26, 2021 | Technology

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

We published an overview of MSTICPy 18 months ago and a lot has happened since then with many changes and new features. We recently released 1.0.0 of the package (it’s fashionable in Python circles to hang around in “beta” for several years) and thought that it was time to update the aging Overview article.

What is MSTICPy?

MSTICPy is a package of Python tools for security analysts to assist them in investigations and threat hunting, and is primarily designed for use in Jupyter notebooks. If you’ve not used notebooks for security analysis before we’ve put together a guide on why you should.

The goals of MSTICPy are to:

1. Simplify the process of creating and using notebooks for security analysis by providing building-blocks of key functionality.


2. Improve the usability of notebooks by reducing the amount of code needed in notebooks.


3. Make the functionality open and available to all, to both use and contribute to.

MSTICPy is organized into several functional areas:

• Data Acquisition – is all about getting security data into the notebook. It includes data providers and pre-built queries that allow easy access to several security data stores including Azure Sentinel, Microsoft Defender, Splunk and Microsoft Graph. There are also modules that deal with saving and retrieving files from Azure blob storage and uploading data to Azure Sentinel and Splunk.


• Data Enrichment – focuses on components such as threat intelligence and geo-location lookups that provide additional context to events found in the data. It also includes Azure APIs to retrieve details about Azure resources such as virtual machines and subscriptions.


• Data Analysis – packages here focus on more advanced data processing: clustering, time series analysis, anomaly identification, base64 decoding and Indicator of Compromise (IoC) pattern extraction. Another component that we include here but really spans all of the first three categories is pivot functions – these give access to many MSTICPy functions via entities (for example, all IP address related functions are accessible as methods of the IpAddress entity class.)


• Visualization – this includes components to visualize data or results of analyses such as: event timelines, process trees, mapping, morph charts, and time series visualization. Also included under this heading are a large number of notebook widgets that help speed up or simplify tasks such as setting query date ranges and picking items from a list. Also included here are a number of browsers for data (like the threat intel browser) or to help you navigate internal functionality (like the query and pivot function browsers).

There are also some additional benefits that come from packaging these tools in MSTICPy:

• The code is easier to test when in standalone modules, so they are more robust.


• The code is easier to document, and the functionality is more discoverable than having to copy and paste from other notebooks.


• The code can be used in other Python contexts – in applications and scripts.

Companion Notebook

Like many of our blog articles, this one has a companion notebook. This is the source of the examples in the article and you can download and run the notebook for yourself. The notebook has some additional sections that are not covered in the article.

The notebook is available here.

Documentation and Resources

Since the original Overview article we have invested a lot of time in improving and expanding the documentation – see msticpy ReadTheDocs. There are still some gaps but most of the package functionality has detailed user guidance as well as the API docs. We do also try to document our code well so that even the API documents are often informative enough to work things out (if you find examples where this isn’t the case, please let us know). 

In most cases we also have example notebooks providing an interactive illustration of the use of a feature (these often mirror the user guides since this is how we write most of the documentation). They are often a good source of starting code for projects. These notebooks are on our GitHub repo.

Getting Started Guides

If you are new to MSTICPy and use Azure Sentinel the first place to go is the Use Notebooks with Azure Sentinel document. This will introduce you the the Azure Sentinel user interface around notebooks and walk you through process of setting up an Azure Machine Learning (AML) workspace (which is, by default, where Azure Sentinel notebooks run). One note here – when you get to the Notebooks tab in the Azure Sentinel portal, you need to hit the Save notebook button to save an instance of one of the template notebooks. You can then launch the notebook in the AML notebooks environment.

The next place to visit is our Getting Started for Azure Sentinel notebook. This covers some basic introductory notebook material as well as essential configuration. More advanced configuration is covered in Configuring Notebook Environment notebook – this covers configuration settings  in more detail and includes a section on setting up a Python environment locally to run your notebooks.

Although this article is aimed primarily at Azure Sentinel users, you can use MSTICPy with other data sources (e.g. Splunk or anything you can get into a pandas DataFrame) and in any Jupyter notebook environment. The Azure Sentinel notebooks can be found in our Notebooks GitHub repo.

Notebook Initialization

Assuming that you have a blank notebook running (in either AML or elsewhere) what do you do next?

Most of our notebooks include a more-or-less identical setup sections at the beginning. These do three things:

1. Checks the Python and MSTICPy versions and updates the latter if needed.


2. Imports MSTICPy components.


3. Loads and authenticates a query provider to be able to start querying data.

If you see warnings in the output from the cell about configuration sections missing you should revisit the previous Getting Started Guides section. This cell includes the first two functions in the list above. The first one – running utils.check_versions() – is not essential in most cases once you have your environment up and running but it does do a few useful tweaks to the notebook environment, especially if you are running in AML.

The init_notebook function automates a lot of import statements and checks to see that the configuration looks healthy.

The third part of the initialization loads the Azure Sentinel data provider (which is the interface to query data) and authenticates to your Azure Sentinel workspace. Most data providers will require authentication.

Assuming you have your configuration set up correctly, this will usually take you through the authentication sequence, including any two-factor authentication required.

Data Queries

Once this setup is complete, we’re at the stage where we can start doing interesting things!

MSTICPy has many pre-defined queries for Azure Sentinel (as well as for other providers). You can choose to run one of these predefined queries or write your own. This list of queries documented here is usually up-to-date but the code itself is the real authority (since we add new queries frequently). The easiest way to see the available queries is with the query browser. This shows the queries grouped by category and lets you view usage/parameter information for each query.

 

There is also a command-line equivalent function to the browser – qry_prov.list_queries().

 

Timespans

Nearly all queries need time range parameters. You can specify these as parameters to the query function but who wants to type long date-time strings? It usually easier to use the QueryTime widget to set your desired time range and just pass it to the query. In the example below we can see how to load the QueryTime widget. You pass the widget itself to the query function, where the start and end values will be inserted into the query before being run.

 

 

One thing you can see from this screen shot is that the data is returned as a pandas DataFrame. pandas is a package that is extremely popular in the data science community. MSTICPy uses it extensively as a universal data interchange format between different components. We’ll see more examples of DataFrames as we move through the article.

 

Although there are a lot of built-in queries, there will always be cases where you need something different. There are a couple of approaches:

1. Most queries will take an optional parameter add_query_items which allows you to tack on (some might say “inject”!) arbitrary KQL to the query.


2. You can write a query from scratch as a string and just execute it.

These options are shown below.

 

 

Visualizing Data

Now that we can get data, let’s do something more interesting with it.

 

Event Timelines

One of the most basic but also most useful visualizations is to project events onto a timeline. You can do this using MSTICPy‘s separate Timeline function or, more conveniently call it directly from a DataFrame using the mp_timeline pandas extension.

 

 

MSTICPy makes extensive use of the interactive graphics of Bokeh. These charts can be panned and zoomed. Each event also has a hover-over tooltip containing summary information about the event (the summary is derived from the source_columns parameter list).

 

Process Tree

A process tree is another common visualization used when investigating endpoint (host) data.

 

Like the timeline, the process tree supports panning, zooming, hover details and has an optional data table viewer (you need to specify show_table=True when calling the function).

 

Alert Viewer

MSTICPy also has a number of special-purpose viewers for things like alerts, where it is often difficult to see the required data in a tabular format.

 

 

This example combines both the timeline viewer and the SelectAlert browser.

 

Data Enrichment with Threat Intelligence, WhoIs and GeoIP

MSTICPy contains many enrichment components for geo-location, ASN/whois, threat intelligence, Azure resource data and others.

 

This example shows calling a method of the IpAddress entity class to get WhoIs information for an IP address.

 

 

Although the whois feature is available as a standalone function, we’ve used a pivot function of the IpAddress class here. To do this we needed to load the Pivot class.

Side note – Pivot functions

If what you want to do is entity-related, there is a good chance that the MSTICPy function will appear as an entity pivot function. Queries, enrichment functions and analysis functions that relate to a particular entity type are all exposed as pivot functions of that entity.

 

Wait – what is an Entity?

 

An entity is essentially a “noun” in the CyberSec world – for example: an IP Address, host, URL, account, etc. They are typically things that do stuff or have stuff done to them. Entities will always have one or more properties that identify the entity and might have additional context properties. For example, an IpAddress entity has its primary Address property and it might also have contextual properties like geo-location or ASN data.

 

Pivot functions are “verbs” to the entities “nouns”. They perform investigative actions (like data queries) on the entity and return a result. The Host entity class, for example, has data queries that retrieve process or logon events logged for that host. The IpAddress entity has functions to lookup its geolocation or query information about the address from threat intelligence providers.

 

Pivot functions are not statically coded into the entity classes. Instead, the pivot subsystem harvests pivot functions from available queries and components and dynamically adds them to the entities.  This gives us a lot of flexibility to add new functions as the features of MSTICPy evolve. It also allows you to use functions from third party libraries or write your own functions and expose them as pivot functions.

 

How do you find what pivot functions (and even what entities) are available? The easiest way to view the entities, their pivot functions and the help associated with each function is to use the Pivot browser (similar to the query browser shown earlier)

 

 

Being grouped with their respective entities makes the pivot functions easy find (compared with hunting through documents to find the right module or function to import). Pivot functions are grouped into related sub-containers of the entity (so all AzureSentinel queries have the form entity.AzureSentinel.query_function().

 

Another advantage of pivot functions (over standalone functions) is that they have a homogenous interface. They will all accept inputs as single values, lists of values or values stored in DataFrames. They also always return their results as DataFrames.

 

Back to Enrichment

A nice side benefit of pivot functions using DataFrames as both input and output is that we can chain several together in a pandas pipeline. Here we’re taking IP addresses from an alert and successively getting WhoIs data, geo-location data. Finally, we’re querying multiple Threat Intelligence providers to see if they have any data about the IP address. At each stage we’re asking for the new data obtained by each stage to be joined to the previous stage (via the join parameter) – although joining is optional.

 

 

We then display the results received from the threat intel providers in another special-purpose viewer – the TI browser.

 

 

Here is an example of a more manual pipeline that stitches together the base64 decoder, IoC pattern extractor and threat intel lookup. It’s taking an obfuscated PowerShell command line and extracting and examining the contents found in the decoded string. Finally, it displays the TI results in the TI browser.

 

 

We might also want to know where this IP address is physically located. We can do that by using our geo-location enrichment and displaying the results on a map.

 

Using advanced analysis (AKA simple machine learning)

MSTICPy has several more-advanced analysis components that help with identifying anomalous patterns in large data sets. 

 

First we’ll show the time series decomposition and visualization component. This works by determining regular patterns of bulk events (think of outbound network byte counts or logon failures) and then identifies outliers to this pattern with a simple statistical calculation.

 

 

You can see the daily cadence network traffic and the presence of two outlying events on 7-11 (the date, not the store).

 

Where the data is more complex than bulk counts, we can use another anomaly identification technique using Markov Chains. Markov chains is a technique used to predict the future probability of something occurring given the probability of things that happened previously. 

 

Here we are using it to analyze Office 365 data. We will build a model to determine the probability of specific sequences of actions and then identify rare sequences that deviate from this base probability.  Office activity data is first grouped into sessions based on user name and source IP address. The probability of a given sequence of actions within a session is measured during the creation of the model. For example, it would be very common to see actions like opening emails, reading a few files, etc. A session that reads hundreds of files or performs unusual actions like setting a mail forwarding rule or delegating control of a mailbox would be much less probable and so would detectable.

 

(the full code for this is given in the notebook)

 

 

There is clearly one session that stands out from the crowd in terms of the unusual actions seen in that session. We can use the rarity score (the inverse of the probability) to quickly filter out the other sessions and see what was happening. In this case, the event revealed a series of unexpected privilege assignment actions.

 

 

Conclusion

Thanks for sticking with me in through this marathon article. I hope it has given you a flavor of the power of Jupyter notebooks in CyberSec hunting and investigation tasks and a reasonable overview of many of the capabilities in MSTICPy.

 

Take-aways and actions.

• The very obvious first action is go and start playing with notebooks – whether in Azure Sentinel/Azure ML or on your own computer.


• Second would be install MSTICPy and kick the tires. We are always looking for feedback on what does and doesn’t work and are always open to requests or suggestions for new features.


• If you’re feeling adventurous, consider contributing to MSTICPy. These could be ideas that you have that you think would be helpful to the CyberSec community. If you’re a bit stuck for ideas but love security and Python coding, we have a few ideas of our own and way too few people to implement them.


• Read the docs here.


• File an issue, feature request, create a PR or just poke around the code on our GitHub repo.


• Read a summary of the latest release.


• Follow me (@ianhelle), Pete (@MSSPete) and Ashwin (@ashwinpatil) on Twitter.

 

New transactable offers from LANSA, Nuvento, and TransientX in Azure Marketplace

by Contributed | Apr 26, 2021 | Technology

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

Microsoft partners like LANSA, Nuvento, and TransientX deliver transact-capable offers, which allow you to purchase directly from Azure Marketplace. Learn about these offers below: LANSA Scalable License: This offer from LANSA provides a Microsoft Windows Server image to use with a Microsoft Azure Resource Manager template in constructing a production-ready Windows stack to deliver LANSA web, mobile, and desktop capabilities. LANSA accelerates development and enables digital transformation. Users can deploy an app to this production environment from any Visual LANSA IDE. NuOCR – OCR automation: This paper-to-digital solution from Nuvento uses optical character recognition (OCR) to automate data extraction. Scanned forms, invoices, surveys, and other documents can be uploaded to a database or to a Microsoft Excel sheet, making them searchable and editable. NuOCR comes with a prebuilt template library for healthcare, insurance, and other industries. TransientAccess Connector: TransientX’s TransientAccess is a zero-trust network access solution that offers an alternative to VPNs. Instead of connecting device to device, TransientAccess uses a temporary hidden network to connect apps on a remote user’s device to apps in a corporate network, dramatically reducing the attack surface. The Connector and the Client are essential components of TransientAccess.

Configuring BitLocker encryption with Endpoint security

by Contributed | Apr 26, 2021 | Technology

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

By Luke Ramsdale – Service Engineer | Microsoft Endpoint Manager – Intune

Administrators often work with a variety of devices—newer devices equipped with the trusted platform module (TPM) or older devices and virtual machines (VMs) without TPM. When you’re deploying BitLocker settings through Microsoft Endpoint Manager – Microsoft Intune, different BitLocker encryption configuration scenarios require specific settings. In this final post in our series on troubleshooting BitLocker using Intune, we’ll outline recommended settings for the following scenarios:

• Enabling silent encryption. There is no user interaction when enabling BitLocker on a device in this scenario.


• Enabling BitLocker and allowing user interaction on a device with or without TPM.

As we described in our first post, Enabling BitLocker with Microsoft Endpoint Manager – Microsoft Intune, a best practice for deploying BitLocker settings is to configure a disk encryption policy for endpoint security in Intune.

Enabling silent encryption

Consider the following best practices when configuring silent encryption on a Windows 10 device.

• First, ensure that the Hide prompt about third-party encryption setting is set to Yes. This is important because there should be no user interaction to complete the encryption silently.
  Hide prompt about third-party encryption settings
  
  


• It’s important not to target devices that are using third-party encryption. Enabling BitLocker on those devices can render them unusable and result in data loss.


• If your users are not local administrators on the devices, you will need to configure the Allow standard users to enable encryption during autopilot setting so that encryption can be initiated for users without administrative rights.


• The policy cannot have settings configured that will require user interaction.

BitLocker settings that prevent silent encryption

In the following example, the Compatible TPM startup PIN, Compatible TPM startup key and Compatible TPM startup key and PIN options are set to Blocked. BitLocker cannot silently encrypt the device because these settings require user interaction.

Figure 1. BitLocker – OS Drive Settings

Be aware that configuring these options to Required will also prevent silent encryption. The Required setting involves end user interaction, which is not compatible with silent encryption.

Figure 2. BitLocker – OS Drive Settings

Note
When assigning a silent encryption policy, the targeted devices must have a TPM. Silent encryption does not work on devices where the TPM is missing or not enabled.

Enabling BitLocker and allowing user interaction on a device

For scenarios where you don’t want to enable silent encryption and would rather let the user drive the encryption process, there are several configuration settings that you can use.

Note
For non-silent enablement of BitLocker, the user must be a local administrator to complete the BitLocker setup wizard.

If a device does not have a TPM and you want to configure start-up authentication, set Hide prompt about third-party encryption to Not configured in Base Settings. This will ensure the user is prompted with a notification when the BitLocker policy arrives on the device.

Example setting to configure start-up authentication

If you want to encrypt devices without a TPM, set Disable BitLocker on devices where TPM is incompatible to Not configured. This setting is part of the startup authentication settings and Start-up authentication required must be set to Yes.

Example to encrypt devices without a TPM

If you also want to allow users to configure startup authentication, then set the Startup authentication required setting to Yes and individual settings Allowed, as shown in the example above. These settings will offer all the startup authentication options to the end user.

Managing authentication settings conflicts

If you configure conflicting startup authentication setting options, the device will not be encrypted, and the end user will receive the following message:

BitLocker Drive Encryption error when BitLocker startup options are in conflict.

Or this message:

BitLocker Drive Encryption error when conflicting Group Policy settings are present.

You can use one of the following options to correct the error:

• Configure all the compatible TPM settings to Allowed.
  Compatible TPM settings set to Allowed.
  
  


• Configure Compatible TPM startup to Required and the remaining three settings
  to Blocked.
  Compatible TPM startup to Required and the remaining three settings to Blocked.
  
  


• Configure Compatible TPM startup key to Required and the remaining three settings
  to Blocked.
  Compatible TPM startup key to Required and the remaining three settings to Blocked.
  
  


• Finally, you can configure Compatible TPM startup PIN to Required and the remaining settings to Blocked.
  Compatible TPM startup PIN to Required and the remaining settings to Blocked.

Note: Devices that pass Hardware Security Testability Specification (HSTI) validation or Modern Standby devices will not be able to configure a startup PIN. Users must manually configure the PIN.

If you configure the Compatible startup key and PIN option to Required and all others to Blocked, you will see the following error when initiating the encryption from the device.

Example BitLocker Drive Encryption error when initiating the encryption from the device.

If you want to require the use of a startup PIN and a USB flash drive, you must configure BitLocker settings using the manage-bde command-line tool instead of the BitLocker Drive Encryption setup wizard.

The user role in encryption

After the device picks up the BitLocker policy, a notification will prompt the user to confirm that there is no third-party encryption software installed.

User experience to start BitLocker encryption.

When the user selects Yes, the BitLocker Drive Encryption wizard is launched, and the user is presented with the following start-up options:

User experience to start encryption from the BitLocker Drive Encryption wizard.

Note
If you decide not to allow users to configure start-up authentication and configure the settings to Blocked, then this screen will not be displayed.

If there is no TPM on the device, the user will see the following screen instead of start-up options. The user enters a password when the device restarts.

User experience when there is no TPM on the device.

The user will be presented with recovery key settings. (The options listed will depend on how the recovery key settings have been configured. For more information about recovery key settings, check out the blog on this topic.)

User experience to backup a BitLocker key in the BitLocker Drive Encryption wizard.

Once the recovery key has been saved, the user is prompted to encrypt the device and the process completes.

User experience to encrypt the device in the BitLocker Drive Encryption wizard.

Tip
If you’re unsure about a configuration setting, you can hover the tool tip to see a description and link to additional information:

Hovering over the tool tip to see a description and link to additional information about a BitLocker setting in the Microsoft Endpoint Manager admin center.

Summary

• It is possible to encrypt a device silently or enable a user to configure settings manually using an Intune BitLocker encryption policy.
  The user driven encryption requires the end users to have local administrative rights.


• Silent encryption requires a TPM on the device.


• Be careful when configuring the start-up authentication settings, conflicting settings will prevent BitLocker from encrypting and produce the Group Policy conflict errors.


• For devices without a TPM, set the Disable BitLocker on devices where TPM is incompatible option to Not configured.

More info and feedback

For further resources on this subject, please see the links below.
Enforcing BitLocker policies by using Intune known issues
Overview of BitLocker Device Encryption in Windows 10
BitLocker Group Policy settings (Windows 10)
BitLocker Use BitLocker Drive Encryption Tools to manage BitLocker (Windows 10)

This is the last post in this series. Catch up on the other blogs:

• Enabling BitLocker with Microsoft Endpoint Manager – Microsoft Intune


• Troubleshooting BitLocker from the Microsoft Endpoint Manager admin center


• Troubleshooting BitLocker policies from the client side


• Using BitLocker recovery keys with Microsoft Endpoint Manager – Microsoft Intune

Let us know if you have any additional questions by replying to this post or reaching out to @IntuneSuppTeam on Twitter.

Build and ship software better with GitHub and Microsoft Teams

by Contributed | Apr 26, 2021 | Technology

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

Millions of developers use GitHub daily to build, ship, and maintain their software – but software development isn’t performed in silos and require open communication and collaboration across teams. Microsoft Teams is one of the key tools that developers use for their collaboration needs, so it was important that the integration of our platforms provide a seamless, connected experience. Context switching is a drain on productivity and stifles the flow of work, which is why the GitHub integration in Teams is so important – as it gives you and your team full line of sight into your GitHub projects without having to leave Teams. Now, when you collaborate with your team, you can stay engaged in your channels and ideate, triage issues, and work together to move your projects forward.

GitHub has made tremendous updates refreshing the integration – with public preview last September and recently with general availability of the app last month. Many in the developer community have been looking forward to the updates in the new GitHub app, which they’ve experienced on other collaboration platforms, and so we’re excited to share some of new features and the existing capabilities you can experience today.

New support for personal app and scheduling reminders
Since the public preview launch of the GitHub app last September, we’ve made some great updates on a couple key areas. First, we’ve added support for the personal app experience and secondly, we’ve added capabilities to support scheduling reminders for pending pull requests.

Personal app experience
As part of personal app experience, you can now subscribe to your repositories and receive notifications for:

• issues


• pull requests


• commits

All the commands available in your channel are now available on your personal app experience with the GitHub app.

Image showing subscription experience within the personal app view

Schedule reminders
You can now schedule reminders for pending pull requests. With this feature you can now get periodic reminders of pending pull requests as part of your channel or personal chat. Scheduled reminders ensure your teammates are unblocking your workflows by providing reviews on your pull request. This will have an impact on business metrics like time-to-release for features or bug fixes.

Image showing user setting up scheduled reminders within the GitHub Teams app

From your Teams channel, you can run the following command to configure a reminder for pending pull requests on your Organization or Repository:

@github schedule organization/repository

This will create reminder for weekdays at 9.30 AM. However, if you want to configure the reminder for a different day or time, you can achieve that by passing day and time with the below command:

@github schedule organization/repository <Day format> <Time format>

Learn more about channel reminders.

You can also configure personal reminders in your personal chats, as well, using the below command:

@github schedule organization

Stay notified on updates that matter to you through subscriptions
Subscriptions allow you to customize the notifications you receive from the GitHub app for pull request and issues. You can use filters to create subscriptions that are helpful for your projects, without the noise of non-relevant updates – and you can create these in channels or in the personal app.

Subscribing and Unsubscribing
You can subscribe to get notifications for pull requests and issues for an Organization or Repository’s activity.

@github subscribe <organization>/<repository>

Image showing user subscribing to a specific organization and repository via GitHub app

To unsubscribe to notifications from a repository, use:

@github unsubscribe <organization>/<repository>

Customize notifications
You can customize your notifications by subscribing to activity that is relevant to your Teams channel and unsubscribing from activity that is less helpful to your project.

@github subscribe owner/repo

Learn more about subscription notifications on the GitHub app.

Use threading to synchronize comments between Teams and GitHub
Notifications for any pull request and issue are grouped under a parent card as replies. The parent card always shows the latest status of the pull request/issue along with other meta-data like description, assignees, reviewers, labels, and checks. Threading gives context and helps improve collaboration in the channel.

Image showing pull request card staying updated with latest comments and information

Make your conversations actionable
Stay in the flow of work by making the conversations you have with your teammates on GitHub actionable. You can use the app to create an issue, close or reopen an issue, or leave comments on issues and pull requests.

With the GitHub app, you can perform the following:

• Create issue


• Close an issue


• Reopen and issue


• Comment on issue


• Comment on pull request

You can perform these actions directly from the notification card in the channel by clicking on the buttons available in the parent card.

Image of a GitHub pull request notification on a card and the user from Teams commenting

More to come!
We’re excited for you to use these new and existing features as you continue to build world-class software and services – and we’re equally excited to see the growth and evolution of the app in the future. If you haven’t already installed the GitHub app for Teams, you can easily do so today to get started.

Happy coding!

Announcing Viva Learning public preview

by Contributed | Apr 26, 2021 | Technology

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

By John Mighell, Sr. Product Marketing Manager, Viva Learning Marketing Lead

Since we announced Microsoft Viva in February, we’ve heard consistently from customers, industry analysts, and our own internal users how important learning is to them. Everyday we hear examples of creative learning – not just as an important aspect of personal and professional growth – but also as an avenue for social engagement, helping people feel more connected in a largely virtual work environment. These scenarios are top of mind as we get closer to launching Viva Learning – a central hub for learning in Microsoft 365 where people can discover, share, recommend, and learn from best-in-class content libraries to help teams and individuals make learning a natural part of their day.

At Microsoft Ignite in March, we shared a new set of product features and admin capabilities, derived from our private preview customer feedback and internal use scenarios. With this feedback we’re continuing to build Viva Learning to seamlessly integrate learning into the tools you already use everyday – you can share learning via chat, pin learning content in existing Teams channels, recommend learning, see all your available learning sources in a personalized view, search across available sources, and so much more.

As we strive to build a product that facilitates an organization’s learning culture by bringing learning into the flow of work, we’re thrilled to announce today we’re ready to take the next step in that journey.

Viva Learning enters public preview today

There are a few items to keep in mind as we kick off public preview:

Eligibility
Viva Learning public preview is open to all organizations with paid subscription access to Microsoft Teams, with the exception of Education or Government customers. We’ll have additional information to share when Viva Learning is available to those audiences in the future.

Approval from your IT admin
Public preview onboarding requests should either come from your IT admin directly or have the support of your IT admin. In the Teams Admin Center, your IT admin will have the ability to configure who within your organization has access to the Viva Learning app in preview – this can range from the entire organization to just a small subset of users.

Onboarding timelines
We expect a high volume of public preview requests and will manage requests as they come in through a rolling onboarding process. Expect it to take a few weeks from request submission to tenant activation.

Product features in preview
As with any product in preview or beta stages, please be aware that we are still hard at work building the final version. The preview product will not initially include all the features that will be available at product general availability. We will roll out additional features to our preview customers continually as we lead up to general availability later this year.

Submitting feedback
As you start to use Viva Learning we want to hear your feedback! Please use the “Help” button in Teams (bottom of the left nav rail) and select either “Suggest a feature” or “Report a problem”

How to sign up for Viva Learning public preview

Once you’ve read through the 5 items above, you’re ready to get started. The public preview request process is simple and should only take you a few minutes:

1. Gather required information
To activate the Viva Learning preview for your Microsoft 365 tenant we need the tenant ID your organization uses to login to Teams (has AAD users associated), and the type of SKU your organization is currently licensed with. You will need that information to accurately fill out the form linked below.

2. Submit your request
Complete our onboarding request form with the required information. Completing this form should take about 5 minutes.

3. Next steps
After submitting your request, please stay tuned for a confirmation email within 24 business hours. Later, you will receive a notification email once your tenant is activated which will include setup and usage documentation. We will keep you posted using the vivalp@microsoft.com alias. Please add this alias to your Safe Senders list in Outlook (Home → Junk → Junk E-mail Options → Safe Senders). Please do not send emails directly to this alias. 

Looking ahead

We will have additional important updates, features, and news on Viva Learning in the coming weeks and months. Don’t forget to visit aka.ms/VivaLearning and click “sign up for updates” to receive the latest customer and partner updates as they become available.

Java Azure Tools Update April 2021: Connect to Azure Database for MySQL

by Contributed | Apr 26, 2021 | Technology

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

Welcome to the April update of Java Azure Tools! This blog series provide updates for all the Azure tooling support we are providing for Java users, covering Maven/Gradle plugins for Azure, Azure Toolkit for IntelliJ/Eclipse and Azure Extensions for VS Code. Follow us and you will get more exciting updates in the future blogs.

If you use Azure with Java apps deployed either on VM, on App Service, on AKS or on-premise, you probably store application data on Azure as well using data services like the Azure Database for MySQL. The Azure Toolkit for IntelliJ 3.50.0 release brings this brand new experience in IntelliJ on connecting your Java app with Azure Database for MySQL. We will also show you how to deploy the app seamlessly to Azure Web Apps with the database connection. 

In brief, the Azure Toolkit for IntelliJ can manage your Azure database credentials and supply them to your app automatically through:

• If running the app locally: Environment variables through a before launch task named “Connect Azure Resource”.


• If running the app on Azure Web Apps: App Setting deployed along with the artifact.

Check out the showcase GIF below and detail steps will be explained in later sections.

Create an Azure Database for MySQL

let’s start from creating an Azure Database for MySQL server instance. You can either follow the steps here right from your Azure Toolkit for IntelliJ plugin or with any other tools like Azure Portal.

1. Right-click on the Azure Database for MySQL node in the Azure Explore, select Create and then select More settings to open the wizard shown in image below.


2. (Optional) Customize the resource group name and server name.


3. Choose a location you prefer, here we use West US.


4. Specify admin username and password.


5. Select the two checkboxes in the Connection security section. This step will automatically add corresponding IP whitelist rules to the firewalls protecting your MySQL server.


6. Click OK.

The background operation can take a few minutes to complete. After that you can refresh the Azure Database for MySQL node in the Azure Explore, right-click on the server you just created and select Show Properties for some key information listed. If you are using IntelliJ IDEA Ultimate version, select Open by Database Tools will connect the MySQL server to the database tools embedded.

Connect with your local project

Here we use a sample Spring Boot project called PetClinic. You can also try this with your own project consuming MySQL.

1. Clone the project to your dev machine and import with IntelliJ IDEA.
   

   git clone https://github.com/spring-projects/spring-petclinic.git​



2. Enable MySQL profile by adding spring.profiles.active=mysql in the application.properties.


3. Connect to the MySQL server using MySQL Workbench or MySQL CLI for example:
   

    mysql -u <admin name>@<mysql server name> -h <mysql server name>.mysql.database.azure.com -P 3306 -p --ssl



4. Run the commend in resources/db/mysql/user.sql on the MySQL server to create the petclinic database and user.


5. In Azure Explorer, right-click on the MySQL server you created and select Connect to Project to open the wizard below. Select the petclinic database, specify password and select Until restart for to save the password for this IDE session. Then you can click Test Connection below to verify connection from your IDE. Then click OK.
   


6. Open application-mysql.properties, comment out the original spring.datasource.url/username/password. Type those properties again and accept the autocomplete suggestion with Connect to Azure Datasource. 
    
   

   # database init, supports mysql too
   database=mysql
   #spring.datasource.url=${MYSQL_URL:jdbc:mysql://localhost/petclinic}
   #spring.datasource.username=${MYSQL_USER:petclinic}
   #spring.datasource.password=${MYSQL_PASS:petclinic}
   
   spring.datasource.url=${AZURE_MYSQL_URL}
   spring.datasource.username=${AZURE_MYSQL_USERNAME}
   spring.datasource.password=${AZURE_MYSQL_PASSWORD}
   
   # SQL is written to be idempotent so this is safe
   spring.datasource.initialization-mode=always
   ​



7. Run the application by right-clicking on the PetClinicApplication main class and choosing Run ‘PetClinicApplication’. This will launch the app locally with the MySQL server on Azure connected.

Deploy the app seamlessly to Azure Web Apps

Once you have finished all the steps above, there is no extra steps to make the database connect also works on Azure Web Apps. Just follow the ordinary steps to deploy the app on Azure: Right-click on the project and select Azure->Deploy to Azure Web Apps. You can also see the before launch task “Connect Azure Resource” added here, which will upload your database credentials as App Settings to Azure. Therefore, after click Run and wait for the deployment to complete you will see the app working on Azure without any further configuration.

Try our tools

Please don’t hesitate to give it a try! Your feedback and suggestions are very important to us and will help shape our product in future.

• Learn more about Java on Azure


• Get started with Azure Web Apps using Maven/IntelliJ/VS Code


• Get started with Azure Functions using  Maven/Gradle/IntelliJ/VS Code


• Get started with Azure Spring Cloud using IntelliJ/VS Code