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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

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via @MSAzureCAT Enterprise #Cloud Control Plane Planning #AzureDevOps #Pipelines

End-to-end Pipelines for Automating Microsoft Azure Deployments

 

Overview :

Imagine a fully automated, end-to-end pipeline for your cloud deployments—one that encompasses and automates everything:

• Source code repos.
• The build and release iterations.
• Agile processes supported by continuous integration and continuous deployment (CI/CD)
• Security and governance.
• Business unit chargebacks.
• Support and maintenance.

Azure services and infrastructure-as-code (IaC) make control plane automation very achievable. Many enterprise IT groups dream of creating or unifying their disparate automation processes and supporting a common, enterprise-wide datacenter control plane in the cloud that is integrated with their existing or new DevOps workflows. Their development environments may use Jenkins, Azure DevOps Services (formerly Visual Studio Team Services), Visual Studio Team Foundation Server (TFS), Atlassian, or other services. The challenge is to automate beyond the CI/CD pipeline to the management and policy layers. From a planning and architecture standpoint, it can seem like an overwhelming program of interdependent systems and processes. This guide outlines a planning process that you can use for automated support of your cloud deployments and DevOps workflows beyond the CI/CD pipeline. The Azure platform provides services you can use, or you can choose to work with third-party or open source options. The process is based on real-world examples that we have deployed with enterprise customers on Azure.

This whitepaper was authored by Tim Ehlen. It was edited by Nanette Ray. It was reviewed by AzureCAT.

Download the Awesome eBook here on the AzureCAT Team Blog

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Using #Azure Pipelines for your Open Source Project #AzureDevOps

Azure Pipelines for your Open Source Projects

Damian speaks to Edward Thomson about how to get started with Azure Pipelines – right from GitHub. The deep integration and GitHub Marketplace app for Azure Pipelines makes it incredibly easy to build your projects no matter what language you’re using. You can even use the builds as part of your PR checks!

https://github.com/marketplace/azure-pipelines

Edward shows us the incredible (free!) offers for open and closed source projects, and walks through creating and running a new Azure Pipelines build from scratch in only a few minutes.

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Microsoft #Azure Service Fabric Mesh for your #Microservices and #Container Apps in the #Cloud

Microsoft Service Fabric Mesh

Azure Service Fabric Mesh is a fully managed service that enables developers to deploy microservices applications without managing virtual machines, storage, or networking. Applications hosted on Service Fabric Mesh run and scale without you worrying about the infrastructure powering it. Service Fabric Mesh consists of clusters of thousands of machines. All cluster operations are hidden from the developer. Simply upload your code and specify resources you need, availability requirements, and resource limits. Service Fabric Mesh automatically allocates the infrastructure and handles infrastructure failures, making sure your applications are highly available. You only need to care about the health and responsiveness of your application-not the infrastructure.

With Service Fabric Mesh you can:

  • “Lift and shift” existing applications into containers to modernize and run your current applications at scale.
  • Build and deploy new microservices applications at scale in Azure. Integrate with other Azure services or existing applications running in containers. Each microservice is part of a secure, network isolated application with resource governance policies defined for CPU cores, memory, disk space, and more.
  • Integrate with and extend existing applications without making changes to those applications. Use your own virtual network to connect existing application to the new application.
  • Modernize your existing Cloud Services applications by migrating to Service Fabric Mesh.

Build high-availability into your application architecture by co-locating your compute, storage, networking, and data resources within a zone and replicating in other zones. Azure services that support Availability Zones fall into two categories:

  • Zonal services – you pin the resource to a specific zone (for example, virtual machines, managed disks, IP addresses)
  • Zone-redundant services – platform replicates automatically across zones (for example, zone-redundant storage, SQL Database).

To achieve comprehensive business continuity on Azure, build your application architecture using the combination of Availability Zones with Azure region pairs. You can synchronously replicate your applications and data using Availability Zones within an Azure region for high-availability and asynchronously replicate across Azure regions for disaster recovery protection.

Store state in an Azure Service Fabric Mesh application by mounting an Azure Files based volume inside the container

Twitter AMA on Service Fabric Mesh :

The Service Fabric team will be hosting an Ask Me Anything (AMA) (more like “ask us anything”!) session for Service Fabric Mesh on Twitter on Tuesday, October 30thfrom 9am to 10:30am PST. Tweet to @servicefabric or @AzureSupport using #SFMeshAMA with your questions on Mesh and Service Fabric. More information here

More information about Azure Service Fabric Mesh :

Microsoft Azure Service Fabric Mesh LAB on Github

Get started with Microsoft Azure Service Fabric for your Microservices and Container Apps

Service Fabric Microsoft Ignite 2018 sessions

JOIN Containers in the Cloud Community Group on LinkedIn here


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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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Watch the Live Stream Today of #Microsoft Ignite 2018 in Orlando 24 – 28 September #MSIgnite #Azure #Cloud #DevOps and More


Don’t miss the Live Stream of Microsoft Ignite 2018

Get the latest insights and skills from technology leaders and practitioners shaping the future of cloud, data, business intelligence, teamwork, and productivity. Immerse yourself with the latest tools, tech, and experiences that matter, and hear the latest updates and ideas directly from the experts.

Watch live https://www.microsoft.com/en-us/ignite as Microsoft CEO Satya Nadella lays out his vision for the future of tech, then watch other Microsoft leaders explore the most important tools and technologies coming in the next year. After the keynotes, select Microsoft Ignite sessions will stream live—take a deep dive into the future of your profession.


More then 700+ Sessions and 100+ Expert-led and self-paced workshops


#MSIgnite



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Upgrading Azure #Kubernetes Cluster and Set #Azure monitor Alerts on #AKS


Current version of Kubernetes on Microsoft Azure.

Upgrading Microsoft Azure Kubernetes Services

Azure Kubernetes Service (AKS) makes it simple to deploy a managed Kubernetes cluster in Azure. AKS reduces the complexity and operational overhead of managing Kubernetes by offloading much of that responsibility to Azure. As a hosted Kubernetes service, Azure handles critical tasks like health monitoring and maintenance for you. In addition, the service is free, you only pay for the agent nodes within your clusters, not for the masters.

AKS clusters support Role-Based Access Control (RBAC). An AKS cluster can also be configured to integrate with Azure Active Directory. In this configuration, Kubernetes access can be configured based on Azure Active Directory identity and group membership.
For more information, see, Integrate Azure Active Directory with AKS.

From here I will do a step-by-step Upgrade of a Microsoft Azure Kubernetes Cluster to a newer version and set Azure Monitor alert rule active for the future to get an Alert notification when a colleague is upgrading the AKS Services.

Here you see all the newer versions of Kubernetes.

Upgrading to version 1.11.1 of Kubernetes.

IMPORTANT NOTE :

When upgrading an AKS cluster, Kubernetes minor versions cannot be skipped. For example, upgrades between 1.8.x -> 1.9.x or 1.9.x -> 1.10.x are allowed, however 1.8 -> 1.10 is not. To upgrade, from 1.8 -> 1.10, you need to upgrade first from 1.8 -> 1.9 and then another do another upgrade from 1.9 -> 1.10

KubeCluster Activity Log

At the green arrow on this picture you can download the activities into CSV file. At the Red arrow you see the User ID who initiated the Upgrade of the Kubernetes Cluster. This is important information for Azure Alert monitoring.

10 minutes later Kubernetes Cluster is Upgraded to version 1.11.1

Upgrade is done.

We now do a minor Upgrade of Kubernetes from version 1.11.1 to 1.11.2 to get the newest version on Azure.
Click on 1.11.2 version and hit Save.

 

Microsoft Azure Monitoring Alerts

When you click on the second activity of the Upgrade you see at arrow 2 that you can add an Activity Log Alert by Azure monitoring.

Creating Rule Alerts.

  1. Define Alert condition is already set. We want an Alert notification on Upgrading KubeCluster.
  2. Define Alert details, must be set.
  3. Define Action Group, must be set to create the Alert Rule.

2. Define the Alert Details.

3. Define Action Group : Click on + New Action Group

Click on OK

Created Action Group name AKSAdmins

An action group is a collection of notification preferences defined by the user. Azure Monitor and Service Health alerts are configured to use a specific action group when the alert is triggered. Various alerts may use the same action group or different action groups depending on the user’s requirements.

More information on Creating and managing action groups in the Azure portal can be found here

For information on how to use Azure Resource Manager templates to configure action groups, see Action group Resource Manager templates.

 

From here you can Create the Alert Rule and make it Active.

Azure Monitor Alerts with one rule Enabled.

Here is our Active KubeCluster Alert Rule.

Now we will get a notification when a Colleague is Upgrading our KubeCluster in the Future 😉

KubeCluster is now running the latest available version of Kubernetes.

Kubernetes Cluster nodes are Healthy and running version 1.11.2

Here you see in the Kubernetes Dashboard the Node version of Kubernetes.

For Developers and DevOps it’s Great to work with Microsoft Visual Studio Code and the Azure Kubernetes Services (AKS) to work in a CI/CD Pipeline, to create continuous business applications in the Cloud.

Here is my Azure KubeCluster running in Visual Studio Code 🙂

And at last, most important thing is that my Application is running on my Azure Kubernetes Cluster for the Business My Test Site.

Hope this blogpost is useful for you and your business to manage your AKS Cluster in the Microsoft Cloud.

More information About Azure Kubernetes Service (AKS) :

 Upgrade an Azure Kubernetes Service (AKS) cluster via Azure CLI

Azure Kubernetes Service (AKS) Docs

Monitor Azure Kubernetes Service (AKS) container health (preview)

Microsoft Azure Kubernetes Services website Start Free here

Follow Containers in the Cloud Community Group on LinkedIn