Empower IT and developer productivity with Microsoft Azure with @scottgu
Microsoft Azure virtual machine infrastructure innovation and automation
Microsoft Azure Stack Development Kit and why it matters
Manage hybrid cloud and transform your workplace with PowerShell and Azure Automation
Thank you Microsoft and MVP’s for those Awesome sessions at Ignite 2017
Microsoft Azure Container Instances
Containers are quickly becoming the preferred way to package, deploy, and manage cloud applications. Azure Container Instances offers the fastest and simplest way to run a container in Azure, without having to provision any virtual machines and without having to adopt a higher-level service. Azure Container Instances is a great solution for any scenario that can operate in isolated containers, including simple applications, task automation, and build jobs. For scenarios where you need full container orchestration, including service discovery across multiple containers, automatic scaling, and coordinated application upgrades, I recommend the Azure Container Service.
Here you see a quick example of making a Microsoft Azure Container Instance :
You can create an Microsoft Azure Container Instance with the Azure Portal or with Azure Cloud Shell (CLI 2.0)
From the Azure portal, you will create the Azure Container Instance Name, Container Image, Resource Group and Location.
For this quick example I used the public Docker HUB Image WordPress ( https://hub.docker.com/r/library/wordpress/)
Here you set the configuration of the Azure Container Instance, like how many Cores and Memory for the Container.
and Public IP Address yes or no with the port settings.
When you are almost finished in 3 steps, don’t hit OK but have a look at Download Template and Parameters first.
From here you can :
- Download the Template for making Automation deployment scripts.
- Save the template to the Library
- And Deploy the script button.
Also have a look here !
It’s really powerful to work with Azure Resource Management Templates.
Deploying the Azure Container Instance with WordPress
Done, just click here to see the running Container Instance
When you go to the IP-Address of the Azure Container Instance with your browser, you will see the WordPress site config.
Of course you can do this installation also from the Azure Cloud Shell :
Here you find an Overview of Microsoft Azure Cloud Shell and the Activation
Azure Cloud Shell is a browser-based shell experience to manage and develop Azure resources. Cloud Shell offers a browser-accessible, pre-configured shell experience for managing Azure resources without the overhead of installing, versioning, and maintaining a machine yourself. Cloud Shell provisions machines on a per-request basis and as a result machine state will not persist across sessions. Since Cloud Shell is built for interactive sessions, shells automatically terminate after 20 minutes of shell inactivity.
Bash in Cloud Shell
|Linux shell interpreter||Bash
|Azure tools||Azure CLI 2.0 and 1.0
|Containers||Docker CLI/Docker Machine
Cloud Foundry CLI
|Python||2.7 and 3.5 (default)|
Secure automatic authentication
Cloud Shell securely and automatically authenticates account access for the Azure CLI 2.0.
Azure Files persistence
Since Cloud Shell is allocated on a per-request basis using a temporary machine, files outside of your $Home and machine state are not persisted across sessions. To persist files across sessions, Cloud Shell walks you through attaching an Azure file share on first launch. Once completed Cloud Shell will automatically attach your storage for all future sessions.
See here more information about Microsoft Azure Container Instances
Hope this is helpful for you to start with Containers, here you can follow the Cloud Container Community
The Microsoft Ignite 2017 App s available
Don’t miss this Great Microsoft Ignite 2017 Event in Orlando Florida September 25-29, 2017 and Register for the last passes here
Have a look at the session Catalog and Choose your favorite topics at Microsoft Ignite 2017 here
Have lot’s of Fun and Great sessions to LEARN from with Awesome new Microsoft Technology !
Follow Microsoft Ignite on Twitter => @MS_Ignite
Description: This is the updated release (v2.0) of “Inside the Microsoft Operations Management Suite”, an end-to-end deep dive into the full range of Microsoft Operations Management Suite (OMS) features and functionality, complete with downloadable sample scripts.
The chapter list in this edition is shown below:
- Chapter 1: Introduction and Onboarding
- Chapter 2: Searching and Presenting OMS Data
- Chapter 3: Process Automation
- Chapter 4: Configuration Management
- Chapter 5: Change & Update Management
- Chapter 6: Extending OMS Using Log Search
- Chapter 7: Alert Management
- Chapter 8: Log Management & Performance Data
- Chapter 9: Azure & Office 365 Solutions
- Chapter 10: Service Map & Wire Data
- Chapter 11: Network Performance Monitor
- Chapter 12: Other OMS Solutions
- Chapter 13: Assessment Solutions
- Chapter 14: Security & Compliance
- Chapter 15: Protection & Recovery
- Chapter 16: ITSM Integration
- Chapter 17: Custom OMS Solutions
Thank you all for this Great work !
Join and Register for this Awesome TechDays 2017 Event
RSVP : Thursday 12 and Friday 13 October in the RAI
The Microsoft Data Science Virtual Machine (DSVM) is a powerful data science development environment that enables you to perform various data exploration and modeling tasks. The environment comes already built and bundled with several popular data analytics tools that make it easy to get started quickly with your analysis for On-premises, Cloud or hybrid deployments. The DSVM works closely with many Azure services and is able to read and process data that is already stored on Azure, in Azure SQL Data Warehouse, Azure Data Lake, Azure Storage, or in Azure Cosmos DB. It can also leverage other analytics tools such as Azure Machine Learning and Azure Data Factory.
The ‘Data Science Virtual Machine (DSVM)’ is a ‘Windows Server 2016 with Containers’ VM & includes popular tools for data exploration, analysis, modeling & development.
- Microsoft R Server – Dev. Ed. (Scalable R)
- Anaconda Python
- SQL Server 2016 Dev. Ed. – With In-Database R analytics
- Microsoft Office 365 ProPlus BYOL – Shared Computer Activation
- Julia Pro + Juno Editor
- Jupyter notebooks
- Visual Studio Community Ed. + Python, R & node.js tools
- Power BI Desktop
- Deep learning tools e.g. Microsoft Cognitive Toolkit (CNTK 2.0), TensorFlow & mxnet
- ML algorithm libraries e.g. xgboost, Vowpal Wabbit
- Azure SDKs + libraries for various Azure Cloud offerings. Integration tools are included for:
Tools for ML model operationalization as web services in the cloud, using Azure ML or Microsoft R Server.
Creating the Azure DSVM with Windows Server 2016
I use this Azure DSVM for testing and I will enable Auto-Shutdown Scheduler
(to save money)
The following software is by default installed in the Azure DSVM :
My Azure Data Science Virtual Machine in the Cloud 😉
From here you can configure your Data Management Gateway.
Microsoft Data Management Gateway connects on-premises data sources to cloud services for consumption. With Microsoft cloud services, such as Power BI for Office 365 and Azure Data Factory you get benefits including fast deployment, low maintenance cost, and flexible billing model while keeping your enterprise data on-premises. With Data Management Gateway, you can connect on-premises data to cloud services in a secure and managed way, to respond more quickly to changing business needs with a flexible, hybrid cloud platform. You can benefit from Microsoft cloud services while you keep your business running with the on-premises data.
More information about the Data Management Gateway :
Running Azure Data Science VM
Portal Overview of the Azure DSVM
From the Microsoft Azure Portal you can add Resource Extensions to your Azure Data Science VM.
From here you can add the following Extensions :
Here you can find more Technical information about Microsoft Azure Data Science Virtual Machine :