Cloud and Datacenter Management Blog

Microsoft Hybrid Cloud blogsite about Management


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Don’t Miss this Awesome #Microsoft BUILD 2019 Event! #Azure #Cloud #MSBuild

Download the Mobile App here

Seattle May 6-8, 2019

Watch live as technology leaders from across industries share the latest breakthroughs and trends, and explore innovative ways to create solutions. After the keynotes, select Microsoft Build sessions will stream live—dive deep into what’s new and what’s next for developer tools and tech.

 

Watch the livestream here: https://www.microsoft.com/en-us/build

  • Discover and experience new ways to build, modernize, and migrate your applications. Get hands-on experiences with tools like Azure Kubernetes Service (AKS) that can help you dynamically scale your application infrastructure.
  • Quickly and easily build, train, and deploy your machine learning models using Azure Machine Learning, Azure Databricks, and ONNX. Uncover insights from all your content—documents, images, and media—with Azure Search and Cognitive Services.
  • Join Microsoft for hands-on learning to discover how tools like Visual Studio live share can help you collaborate with your peers instantly.
  • Come learn how to build an end-to-end continuous delivery pipeline that is fast and secure with Azure DevOps technologies. Spend less time maintaining your toolset and more time focusing on customer value.
  • Understand how frameworks like Xamarin and .NET can help you reach customers on all platforms. Learn how to use the same languages, APIs, and data structures across all mobile development platforms.
  • Learn how mixed reality helps you bring your work and data to life when you need it, and where you need it. Start building secure, collaborative mixed reality solutions today using intelligent services, best-in-class hardware, and cross-platform tools.
  • Learn to connect your devices to the cloud using flexible IoT solutions that integrate with your existing infrastructure. Collect untapped data and form valuable insights that help you create better customer experiences and generate new streams of revenue.

Book your Microsoft Build 2019 sessions via the BUILD Scheduler

Vision Keynote by CEO Satya Nadella

 

 

Windows Insider Program

Azure DevOps

Azure Monitor

Containers

Have a good look which sessions to follow because there are 431 sessions 👍🚀

JOIN Azure DevOps Community

https://www.linkedin.com/groups/12139259/ 

JOIN Containers in the Cloud Community

https://www.linkedin.com/groups/13539967/ 

JOIN Azure Monitor and Security Community https://www.linkedin.com/groups/13517115/ 


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#Microsoft Azure Sentinel (Preview) Overview #Azure #Sentinel #Security #Analytics #SIEM

 

Microsoft Azure Sentinel

Microsoft Azure Sentinel delivers intelligent security analytics and threat intelligence across the enterprise, providing a single solution for alert detection, threat visibility, proactive hunting, and threat response.

  • Collect data at cloud scale across all users, devices, applications, and infrastructure, both on-premises and in multiple clouds.
  • Detect previously undetected threats, and minimize false positives using Microsoft’s analytics and unparalleled threat intelligence.
  • Investigate threats with artificial intelligence, and hunt for suspicious activities at scale, tapping into years of cyber security work at Microsoft.
  • Respond to incidents rapidly with built-in orchestration and automation of common tasks.

In the following step-by-step guide you get a global overview of Azure Sentinel :

Search for Azure Sentinel in the Azure Portal.

Click on Create

Connect or add your Workspace.

Click on Add Azure Sentinel

Azure Sentinel is added to your workspace.

Azure Sentinel Overview

Security Analytics

Learn here more with Microsoft Azure Monitor analytics queries

Here you can play with Azure Log Analytics 😉

Here you can collect all your Security Cases

Azure Sentinel Build-In Dashboard Solutions

Azure AD Audit Logs

 

Linux Machines Security

When you have your Azure Sentinel Solutions in place with alerting rules and telemetry and analytics is coming to your workspace, Hunting is the next Threat management tool :

Azure sentinel Hunting

Working with Tags and Collaborate with Teammates

Launch Investigations and Bookmark

Working with Azure Notebooks for Azure Sentinel

Welcome to the Azure Sentinel repository! This repository contains out of the box detections, exploration queries, hunting queries, dashboards and playbooks to help you get ramped up with Azure Sentinel and provide you security content to secure your environment and hunt for threats. You can also submit any issues or feature requests as you onboard to Azure Sentinel. For questions and feedback, please contact AzureSentinel@microsoft.com

Azure Sentinel Notebooks on GitHub

 

Get started from here to Configure your Azure Sentinel Environment

Choose your Data Collections for Azure Sentinel Security

Lot of Choice already Build-in for you.

From here you can make your own Azure Sentinel Analytics Alert Rules.

Alert Rules

Create Alert rules with the right mappings, triggers, and scheduling, response automation.

Add your own playbooks for your Security

Unlock the power of AI for security with Machine Learning

Machine Learning in Azure Sentinel is built-in right from the beginning. We have thoughtfully designed the system with ML innovations aimed to make security analysts, security data scientists and engineers productive. One such innovation is Azure Sentinel Fusion built especially to reduce alert fatigue.

Building your Full Screen Dashboard for Monitoring

More information about Azure Sentinel Intelligent Security :

Start here free with Azure Sentinel Preview

Microsoft azure Sentinel Docs

Microsoft Azure Sentinel on GitHub

Join Microsoft Azure Monitor & Security for Hybrid IT Community

 


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#Microsoft Hololens 2 Overview Videos #MWC2019 #Hololens #Azure #VR with @satyanadella

Microsoft Keynote HoloLens 2 at Mobile World Congress (MWC) 2019

HoloLens 2

Microsoft HoloLens 2: Partner Spotlight with Philips

Microsoft HoloLens 2: Partner Spotlight with Bentley

Conclusion:

I see Awesome possibilities for Maintenance in Smart Cities and Smart Buildings with Intelligent Cloud and Intelligent Edge together with the Microsoft Hololens 2 and Microsoft Azure. Intelligent Dashboards in your Hololens 2 hybrid with your Azure App for example. Great for Manufacturers, Healthcare, Architects, Maintenance Companies but also for Teachers and Students doing innovative Education 🙂

Here you find more information about Microsoft Hololens 2 and Business Ready Apps


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#Azure IoT Pipeline with Microsoft #AzureDevOps Project #IoT #Code #Apps #SmartCities

Azure IoT Edge – Hub with Azure DevOps Pipeline

Configure continuous integration (CI) and continuous delivery (CD) for your IoT Edge application with DevOps Projects. DevOps Projects simplifies the initial configuration of a build and release pipeline in Azure Pipelines.

In the following steps you can see how easy it is to build your Continuous integration and continuous deployment to Azure IoT Edge with DevOps Project :

Select Simple IoT

Click on Next.

From here you set your Azure DevOps organization to your Azure IoT Hub. Click on additional settings

In additional settings you can set :

  • Azure Resource Group
  • Location ( region)
  • Container Registry
  • Container Registry name
  • Container registry SKU
  • Container Location
  • IoT Hub of Edge Devices
  • IoT Hub Location

Select Container Registry Plan

Azure Container Registry allows you to store images for all types of container deployments including DC/OS, Docker Swarm, Kubernetes, and Azure services such as App Service, Batch, Service Fabric, and others. Your DevOps team can manage the configuration of apps isolated from the configuration of the hosting environment.
More information about Azure Container Registry and pricing

Azure DevOps Project will do the rest of the deployment.

Of course Infrastructure as Code (IaC) is possible by ARM JSON Template.

Save the template for later.

here you got your ARM Templates.

Later you will see when you complete the deployment, that your JSON ARM template is in Azure DevOps Repo.
You can connect your Azure DevOps Repo via the portal but also via Visual Studio and Visual Studio Code.

The resources coming into myiotpipeline-rg

MyIOTPipeline-IoTHub is created.

MyIOTPipelineACR Container Registry is created.

MyIOTPipeline with Azure DevOps is created 🙂

Your Continuous integration and continuous deployment to Azure IoT Edge is deployed and active. Now you have your Azure Pipeline in place to continuously update your IoT Device App. From here you can go to Azure DevOps Project Homepage.

Via Agent phase you can see all the jobs of the deployment.

Azure DevOps Pipeline Release

here we have Azure DevOps Repos

Azure DevOps Services includes free unlimited private Git repos, so Azure Repos is easy to try out. Git is the most commonly used version control system today and is quickly becoming the standard for version control. Git is a distributed version control system, meaning that your local copy of code is a complete version control repository. These fully functional local repositories make it easy to work offline or remotely. You commit your work locally, and then sync your copy of the repository with the copy on the server.
Git in Azure Repos is standard Git. You can use the clients and tools of your choice, such as Git for Windows, Mac, partners’ Git services, and tools such as Visual Studio and Visual Studio Code.

All the Azure Resources for the IoT Edge Pipeline with Azure DevOps.

When you have your Azure DevOps Pipeline with IoT Edge devices running, you can monitor your pipeline with Analytics inside Azure DevOps.

Click Next.

Click on Install Analytics.

Select the right Azure DevOps Organization for your IoT Edge Pipeline.

Done !

 

Analytics is now active, you can make automated test plans in Azure DevOps and see the results via Analytics.

Azure DevOps Overview Dashboard.

There are a lot of predefined Analytics Views for you shared.

An Analytics view provides a simplified way to specify the filter criteria for a Power BI report based on the Analytics Service data store. The Analytics Service provides the reporting platform for Azure DevOps.
More information about Analytics in Azure DevOps here

Easy to start with Powerbi and Azure DevOps Connector.

Planned manual testing
Plan, execute, and track scripted tests with actionable defects and end-to-end traceability. Assess quality throughout the development lifecycle by testing your desktop or web applications.

More information about making your testplan for your IoT Edge Devices Azure DevOps Pipeline

Conclusion :

When you connect Microsoft Azure IoT Edge – HUB with your Internet of Things Devices and combine it with Microsoft Azure DevOps Team to develop your Azure IoT Pipeline, then you are in fully control of Continuous integration and continuous deployment to Azure IoT Edge. From here you can make your innovations and Intelligent Cloud & Edge with Artificial Intelligence and Machine Learning to your Devices. You will see that this combination will be Awesome for HealthCare, Smart Cities, Smart Buildings, Infrastructure, and the Tech Industry.

In this Microsoft article, you learn how to use the built-in Azure IoT Edge tasks for Azure Pipelines to create two pipelines for your IoT Edge solution. The first takes your code and builds the solution, pushing your module images to your container registry and creating a deployment manifest. The second deploys your modules to targeted IoT Edge devices.

Join the Azure DevOps Community on LinkedIn

Join Containers in the Cloud Community on LinkedIn

Join Microsoft Azure Monitor & Security for Hybrid IT Community on LinkedIn


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Getting started with #Microsoft Azure Cognitive Services in #Containers #Azure #AI #AKS #Docker

Microsoft Visual Studio Code Tools for AI

With container support, customers can use Azure’s intelligent Cognitive Services capabilities, wherever the data resides. This means customers can perform facial recognition, OCR, or text analytics operations without sending their content to the cloud. Their intelligent apps are portable and scale with greater consistency whether they run on the edge or in Azure.

Bringing AI to the Edge via  Corporate Vice President, Azure AI Eric Boyd

Get started with these Azure Cognitive Services Containers

Building solutions with machine learning often requires a data scientist. Azure Cognitive Services enable organizations to take advantage of AI with developers, without requiring a data scientist. We do this by taking the machine learning models and the pipelines and the infrastructure needed to build a model and packaging it up into a Cognitive Service for vision, speech, search, text processing, language understanding, and more. This makes it possible for anyone who can write a program, to now use machine learning to improve an application. However, many enterprises still face challenges building large-scale AI systems. Today Microsoft announced container support for Cognitive Services, making it significantly easier for developers to build ML-driven solutions.

Microsoft got the following Containers :

  • Text Analytics Containers
  • Face Container
  • Recognize Text Container

More information from Director of Program Management Applied AI Lance Olson here

Start with Installing and running Containers

Request access to the private container registry

You must first complete and submit the Cognitive Services Vision Containers Request form to request access to the Face container. The form requests information about you, your company, and the user scenario for which you’ll use the container. Once submitted, the Azure Cognitive Services team reviews the form to ensure that you meet the criteria for access to the private container registry.

Important !

You must use an email address associated with either a Microsoft Account (MSA) or Azure Active Directory (Azure AD) account in the form. If your request is approved, you then receive an email with instructions describing how to obtain your credentials and access the private container registry.

Read more about installing the Containers here

The Face container uses a common configuration framework, so that you can easily configure and manage storage, logging and telemetry, and security settings for your containers.
Configuration settings
Configuration settings in the Face container are hierarchical, and all containers use a shared hierarchy, based on the following top-level structure:

  • ApiKey
  • ApplicationInsights
  • Authentication
  • Billing
  • CloudAI
  • Eula
  • Fluentd
  • Logging
  • Mounts

Read more here about Configuring the Containers

Follow Containers in the Cloud Community Group

 


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#Microsoft SQL Server 2019 Preview Overview #SQL #SQL2019 #Linux #Containers #MSIgnite

Microsoft SQL Server 2019 Preview

What’s New in Microsoft SQL Server 2019 Preview

• Big Data Clusters
o Deploy a Big Data cluster with SQL and Spark Linux containers on Kubernetes
o Access your big data from HDFS
o Run Advanced analytics and machine learning with Spark
o Use Spark streaming to data to SQL data pools
o Use Azure Data Studio to run Query books that provide a notebook experience

• Database engine
o UTF-8 support
o Resumable online index create allows index create to resume after interruption
o Clustered columnstore online index build and rebuild
o Always Encrypted with secure enclaves
o Intelligent query processing
o Java language programmability extension
o SQL Graph features
o Database scoped configuration setting for online and resumable DDL operations
o Always On Availability Groups – secondary replica connection redirection
o Data discovery and classification – natively built into SQL Server
o Expanded support for persistent memory devices
o Support for columnstore statistics in DBCC CLONEDATABASE
o New options added to sp_estimate_data_compression_savings
o SQL Server Machine Learning Services failover clusters
o Lightweight query profiling infrastructure enabled by default
o New Polybase connectors
o New sys.dm_db_page_info system function returns page information

• SQL Server on Linux
o Replication support
o Support for the Microsoft Distributed Transaction Coordinator (MSDTC)
o Always On Availability Group on Docker containers with Kubernetes
o OpenLDAP support for third-party AD providers
o Machine Learning on Linux
o New container registry
o New RHEL-based container images
o Memory pressure notification

• Master Data Services
o Silverlight controls replaced

• Security
o Certificate management in SQL Server Configuration Manager

• Tools
o SQL Server Management Studio (SSMS) 18.0 (preview)
o Azure Data Studio

Introducing Microsoft SQL Server 2019 Big Data Clusters

SQL Server 2019 big data clusters make it easier for big data sets to be joined to the dimensional data typically stored in the enterprise relational database, enabling people and apps that use SQL Server to query big data more easily. The value of the big data greatly increases when it is not just in the hands of the data scientists and big data engineers but is also included in reports, dashboards, and applications. At the same time, the data scientists can continue to use big data ecosystem tools while also utilizing easy, real-time access to the high-value data in SQL Server because it is all part of one integrated, complete system.

Read the complete Awesome blogpost from Travis Wright about SQL Server 2019 Big Data Cluster here

Starting in SQL Server 2017 with support for Linux and containers, Microsoft has been on a journey of platform and operating system choice. With SQL Server 2019 preview, we are making it easier to adopt SQL Server in containers by enabling new HA scenarios and adding supported Red Hat Enterprise Linux container images. Today we are happy to announce the availability of SQL Server 2019 preview Linux-based container images on Microsoft Container Registry, Red Hat-Certified Container Images, and the SQL Server operator for Kubernetes, which makes it easy to deploy an Availability Group.

SQL Server 2019 preview containers now available

Microsoft Azure Data Studio

Azure Data Studio is a new cross-platform desktop environment for data professionals using the family of on-premises and cloud data platforms on Windows, MacOS, and Linux. Previously released under the preview name SQL Operations Studio, Azure Data Studio offers a modern editor experience with lightning fast IntelliSense, code snippets, source control integration, and an integrated terminal. It is engineered with the data platform user in mind, with built-in charting of query resultsets and customizable dashboards.

Read the Complete Blogpost About Microsoft Azure Data Studio for SQL Server here

SQL Server 2019: Celebrating 25 years of SQL Server Database Engine and the path forward

Awesome work Microsoft SQL Team and Congrats on your 25th Anniversary !


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Enhancing Microsoft #Security using Artificial Intelligence E-book #AI #Azure #MachineLearning

At the Center of intelligent security management is the concept of working smarter, not harder. However, this is a significant undertaking when you consider the ever-evolving landscape of threats and security challenges, combined with the myriad of devices, apps, and user scenarios. In this e-book, learn how you can intelligently detect, protect, and respond to threats by leveraging the strong integration between Microsoft security solutions and our partners.
Read the full e-book to learn how Microsoft is using artificial intelligence (AI) in security features like:

  • Windows Hello
  • Azure Active Directory
  • Azure Advanced Threat Protection
  • Windows Defender SmartScreen
  • Windows Defender Network Protection
  • Exchange Online Protection and more…

You can download Enhancing Microsoft Security using Artificial Intelligence E-book here