We are excited to announce the general availability of the StorSimple Data Manager. This feature allows you to transform data from StorSimple format into the native format in Azure blobs or Azure Files. Once your data is transformed, you can use services like Azure Media Services, Azure Machine Learning, HDInsight, Azure Search, and more.
StorSimple devices use the cloud as a tier of storage and sends data to the cloud in a highly efficient and secure manner. Data is stored in the cloud tier in this deduped, compressed, and encrypted format. A side effect of this is that this data is not readily consumable by cloud services that you might want to use. Azure offers a rich bouquet of services and our goal is to let you use the service of your choice on your data to unleash its potential.
Using this service, you can transform data stored in your 8000 series StorSimple devices into Azure blobs or Azure Files. All the file data that you store on-premises on your StorSimple device will show up as individual blobs or files in Azure. You can use the Azure portal, .NET applications, or Azure Automation to trigger these transformations. You can
https://powerbi.microsoft.com/en-us/blog/gartner-recognizes-microsoft-as-a-leader-in-analytics-and-bi-platforms-for-11-consecutive-years/Source: https://powerbi.microsoft.com/en-us/blog/gartner-recognizes-microsoft-as-a-leader-in-analytics-and-bi-platforms-for-11-consecutive-years/ Today we’re thrilled to announce that for the 11th consecutive year, Microsoft has been positioned as a leader in Gartner’s 2018 Magic Quadrant for Analytics and Business Intelligence Platforms.* And for the third READ MORE
Now is a great time to learn more about Azure Cosmos DB through seven-part technical training series that started rolling out recently. The first part provides a technical overiew, and the second part on how to create a more intelligent and responsive globally distributed serverless application. Both are available now for on-demand viewing. You can join Part 3 live for an overview of both Graph API and Table API on Tuesday this week (10:00-11:00 AM Pacific Time, UTC-8). Subsequent parts are rolling out weekly through the end of March. Learn more and register for all of them here: Azure Cosmos DB Technical Training Series.
Now in preview
Monitor network connectivity to applications with NPM’s Service Endpoint Monitor – public preview – Network Performance Monitor (NPM) introduces Service Endpoint Monitor in preview, which integrates the monitoring and visualization of the performance of your internally hosted & cloud applications with the end-to-end network performance. You can create HTTP, HTTPS, TCP and ICMP based tests from key points in your network to your applications, allowing you to quickly identify whether the problem is due to the network or the application.
Introducing backup for Azure file shares – Azure Backup now enables a native
We are thrilled to announce the availability of B-series VM’s, burstable VM’s in Azure Container Service (AKS).
Burstable VM’s (B-series) are significantly cheaper compared to standard and optimal recommended VM’s like Standard_DS2_V2. B-series VM’s are particularly suited for development and test environments where performance requirements are bursts rather than consistent. In fact, B-Series provides the cheapest cost with bursts CPU usage and thus reduces development and test environment costs significantly. We hope that this addition will significantly reduce the cost of learning Kubernetes AKS, building proof of concepts on Azure Container Service (AKS), running dev/test workloads, etc.
The following configurations are available today.
SKU Type VCPUS GB Ram Data Disks Max IOPS Local SSD B1s Standard 1 1 2 800 2GB B1ms Standard 1 2 2 1600 4GB B2s Standard 2 4 4 3200 8GB B2ms Standard 2 8 4 4800 16GB B4ms Standard 4 16 8 7200 32GB B8ms Standard 8 32 16 10800 64GB
In comparison, a Standard_DS2_V2 node costs greater than five times the B1/B2 SKU’s today. Check the latest VM pricing.
To get started log on to the Azure portal and search for Container Service (managed). As you follow the AKS create cluster workflow, you will
We are happy to share that Azure Service Bus is now able to send events to Azure Event Grid. The key scenario this feature enables is for Service Bus queues, topics, or subscriptions with low message volumes to not require a receiver to be polling for messages at all times. Service Bus will now send events to Azure Event Grid when there are messages in a queue if no receivers are present. You can create Azure Event Grid subscriptions for your Service Bus namespaces, listen to these events, and react to the events by starting a receiver. With this feature, Service Bus can be used in reactive programming models.
Today, Azure Service Bus sends events for two scenarios:
Active messages with no listeners available Deadletter messages available
Additionally, it uses the standard Azure Event Grid security and authentication mechanisms.
How often and how many events are emitted?
If you have multiple queues and topics/subscriptions in the namespace, you get at least one event per queue and subscription. The events are immediately emitted if there are no messages in the Service Bus entity and a new message arrives, or every two minutes unless Azure Service Bus detects an active receiver.
Azure recently introduced an advanced, more efficient Load Balancer platform. This platform adds a whole new set of abilities for customer workloads using the new Standard Load Balancer. One of the key additions the new Load Balancer platform brings, is a simplified, more predictable and efficient outbound port allocation algorithm.
While already integrated with Standard Load Balancer, we are now bringing this advantage to the rest of Azure.
Load Balancer and Source NAT
Azure deployments use one or more of three scenarios for outbound connectivity, depending on the customer’s deployment model and the resources utilized and configured. Azure uses Source Network Address Translation (SNAT) to enable these scenarios. When multiple private IP addresses or roles share the same public IP (public IP address assign to Load Balancer or automatically assigned public IP address for standalone VMs), Azure uses port masquerading SNAT (PAT) to translate private IP addresses to public IP addresses using the ephemeral ports of the public IP address. PAT does not apply when Instance Level Public IP addresses (ILPIP) are assigned.
For the cases where multiple instances share a public IP address, each instance behind an Azure Load Balancer VIP is pre-allocated a fixed number of ephemeral ports
https://blogs.msdn.microsoft.com/sql_server_team/sql-server-replication-enhancement-dynamic-reloading-of-agent-profile-parameters/Source: https://blogs.msdn.microsoft.com/sql_server_team/sql-server-replication-enhancement-dynamic-reloading-of-agent-profile-parameters/ With SQL Server 2017 Cumulative Update 3, we introduced an improvement to SQL Server Replication wherein, changes to the Replication agent parameters can be reloaded dynamically, without having to restart the agent. This improvement will be available READ MORE
https://powerbi.microsoft.com/en-us/blog/automatically-install-apps/Source: https://powerbi.microsoft.com/en-us/blog/automatically-install-apps/ I’m excited to announce the ability to automatically install apps for end users, making it easier to distribute the right apps to the right set of people. Apps deliver data that your end READ MORE
This post is the second in a three-part series by guest blogger, Adrian Rosebrock. Adrian writes at PyImageSearch.com about computer vision and deep learning using Python. He recently finished authoring a new book on deep learning for computer vision and image recognition.
A few weeks ago I wrote a blog post on deep learning and computer vision in the Microsoft Azure cloud that was meant to be a gentle introduction to Microsoft’s Data Science Virtual Machine (DSVM). Today we’re going to get a bit more hands-on and practical, beginning with an email I received from PyImageSearch reader, Kostas:
“Hey Adrian, I’m interested in competing in Kaggle competitions (in particular the computer vision ones). I have some experience in computer vision and machine learning/deep learning but not a lot. Is it even worth my time? Do I even stand a chance against other competitors?”
Great question, Kostas — and I’m sure you’re not alone feeling this way.
Let me answer your question with a story:
When I first set out to write my new book, Deep Learning for Computer Vision with Python, my goal was to create a book/self-study program that was accessible to both novices and experienced researchers
This post is the first part of two blog posts, describing how to setup a CI/CD pipeline using VSTS for deploying a dockerized custom WordPress website working with Azure WebApp for Containers and Azure Database for MySQL.
The main motivation for building a WordPress CI/CD pipeline is the fact that WordPress is limited in supporting dynamic configuration to allow easy modification between different environments. Some values are hardcoded in the WordPress MySQL database. This limitation causing a time consuming task which limits our ability to deploy fast and more frequently.
We will have four environments: local, dev, test and production. The local environment is for the developer that will run the docker images locally, commit the required changes, and will push the code to the master branch once they completed their work. The push action will initiate a CI process, which will build and push a new docker image to our Azure Container Registry. The base image of this docker image will be the WordPress image from the docker hub. As part of the dockerfile, a copy action will be executed for copying the new content into the new docker image.
After the CI process completion