After the recent general availability for Storage Explorer, we also added new features in the latest 1.1 release to align with Azure Storage platform:
Azurite cross-platform emulator Access tiers that efficiently consumes resources based on how frequently a blob is accessed The removal of SAS URL start time to avoid datacenter synchronization issues
Storage Explorer is a great tool for managing contents of your Azure storage account. You can upload, download, and manage blobs, files, queues, and Cosmos DB entities. Additionally, you may gain easy access to manage your Virtual Machine disks, work with either Azure Resource Manager or classic storage accounts, plus manage and configure cross-origin resource sharing (CORS) rules. Storage Explorer also works on public Azure, Sovereign Azure Cloud, as well as Azure Stack.
Let’s go through some example scenarios where Storage Explorer helps with your daily job.
Sign-in to your Azure Cloud from Storage Explorer
To get started using Storage Explorer, sign in to your Azure account and stay connected to your subscriptions. If you have an account for Azure, Azure Sovereign Cloud, or Azure Stack, you can easily sign-in to your account from Storage Explorer Add an Account dialog.
In addition, now Storage Explorer shares the
This post is authored by Gopi Kumar, Principal Program Manager at Microsoft.
The Data Science Virtual Machine (DSVM), a popular VM image on the Azure marketplace, is a purpose-built cloud-based environment with a host of preconfigured data and AI tools. It enables data scientists and AI developers to iterate on developing high quality predictive models and deep learning architectures and helps them become much more productive when developing their AI applications. DSVM has been offered for over two years now and, during that time, it has seen a wide range of users, from small startups to enterprises with large data science teams who use DSVM as their core cloud development and experimentation environment for building production applications and models.
Deploying AI infrastructure at scale can be quite challenging for large enterprise teams. However, Azure Infrastructure provides several services supporting enterprise IT needs, such as around security, scaling, reliability, availability, performance and collaboration. The Data Science VM can readily leverage these services in Azure to support the deployment of large scale enterprise team -based Data Science and AI environments. We have assembled guidance for an initial list of common enterprise scenarios in a new DSVM documentation section dedicated to enterprise
This post is by Ye Xing, Senior Data Scientist, Tao Wu, Principle Data Scientist Manager, and Patrick Buehler, Senior Data Scientist, at Microsoft.
The advancement of medical imaging, as in many other scientific disciplines, relies heavily on the latest advances in tools and methodologies that make rapid iterations possible. We recently witnessed this first-hand when we developed a deep learning model on the newly released Azure Machine Learning Package for Computer Vision (AML-CVP) and were able to improve upon a state-of-the-art algorithm in screening blinding retinal diseases. Our pipeline, based on AML-CVP, reduced misclassification by over 90% (from 3.9% down to 0.3%) without any parameter tuning. The deep learning model training was completed in 10 minutes over 83,484 images on the Azure Deep Learning Virtual Machine equipped with a single NVIDIA V100 GPU. This pipeline can be constructed quickly, with less than 20 lines of Python code, thanks to the benefit of the high-level Python AML-CVP API.
Our work was inspired by the paper “Identifying Medical Diagnosis and Treatable Diseases by Image-Based Deep learning“, published on Cell, a leading medical journal, in February 2018. The paper developed a deep learning AI system to identify two vision-threatening retinal diseases – choroidal
Azure the cloud for all – highlights from Microsoft BUILD 2018 – In this final recap of Microsoft Build 2018, Julia White, Corporate Vice President, Microsoft Azure pulled together some key highlights and top sessions to watch. This post summarizes what’s new across tools, containers+serverless, IoT, and Data+AI.
“Hey! You! Get on my cloud.” Corey Sanders at Build 2018.
Now in preview
Public preview: Query across applications in log alerts – You can use Azure Application Insights to monitor a distributed modern cloud application. In the same spirit, log alerts enable you to combine data across various apps. Cross-app query support in log alerts is currently in preview.
Now generally available
Protect virtual machines across different subscriptions with Azure Security Center – Azure Security Center’s Cross-Subscription Workspace Selection enables you to collect and monitor data in one location from virtual machines that run in different workspaces, subscriptions, and run queries across them.
Announcing SQL Advanced Threat Protection (ATP) and SQL Vulnerability Assessment general availability – SQL Vulnerability Assessment (VA) provides you a one-stop-shop to discover, track and remediate potential database vulnerabilities. It helps give you visibility into your security state, and includes actionable steps to investigate, manage and resolve
Azure Cloud Shell provides browser-based authenticated shell access to Azure from virtually anywhere. Cloud Shell gives the users a rich environment with common tools that is updated and maintained by Microsoft.
Bash in Cloud Shell that runs Bash shell on Ubuntu Linux, which was made generally available in November 2017
PowerShell in Cloud Shell that runs Windows PowerShell 5.1 on Windows Server Core and has been in preview since September 2017
In this post, we are listing the key upcoming changes to the PowerShell experience in Azure Cloud Shell, namely:
Faster startup time PowerShell Core 6 as the default experience Running on a Linux container Persistent Tool Settings Faster Startup Time
We are well-aware that the startup time of PowerShell in Azure Cloud Shell is well below the user’s expectation. For past couple of months, the team has been working hard to make significant improvements in this area. We expect to deliver multi-fold improvements in the startup time for PowerShell experience (and also make Bash experience faster).
Last week, we released an update to the Azure IoT Reference Architecture Guide. Our focus for the update was to bring the document forward to the latest Azure IoT cloud native recommended architecture and latest technology implementation recommendations. The updated guide includes an overview of the IoT space, recommended subsystem factoring for solutions, and prescriptive technology recommendations per subsystem. Technical content added includes coverage of topics such as microservices, containers, orchestrators (e.g. Kubernetes and Service Fabric), serverless usage, Azure Stream Analytics, and Edge devices. Major updates were made to the Stream Processing and Storage subsystem sections of the document covering rules processing and storage technology options on Azure across differing types of IoT solutions.
The IoT Architecture Guide aims to accelerate customers building IoT Solutions on Azure by providing a proven production ready architecture, with proven technology implementation choices, and with links to Solution Accelerator reference architecture implementations such as Remote Monitoring and Connected Factory. The document offers an overview of the IoT space, recommended subsystem factoring for scalable IoT solutions, prescriptive technology recommendations per subsystems, and detailed sections per subsystem that explore use cases and technology alternatives.
Future updates – please provide feedback and ask questions
https://powerbi.microsoft.com/en-us/blog/help-improve-power-bi/Source: https://powerbi.microsoft.com/en-us/blog/help-improve-power-bi/ We love hearing feedback from the Power BI community and today we have another quarterly survey to keep improving Power BI with your feedback.
Last week, the Microsoft Build conference brought developers lots of innovation and was action packed with in-depth sessions. During the event, my discussions in the halls ranged from containers to dev tools, IoT to Azure Cosmos DB, and of course, AI. The pace of innovation available to developers is amazing. And, in case there was simply too much for you to digest, I wanted to pull together some key highlights and top sessions to watch, starting with a great video playlist with highlights from the keynotes.
Empowering developers through the best tools
Build is for devs, and all innovation in our industry starts with code! So, let’s start with dev tools. Day one of Build marked the introduction of .NET Core 2.1 release candidate. .NET Core 2.1 improves on previous releases with performance gains and many new features. Check out all the details in the release blog and this great session from Build showing what you can use today:
.NET Overview & Roadmap: In this session, Scott Hanselman and Scott Hunter talked about all things .NET, including new .NET Core 2.1 features made available at Build.
Scott Hanselman and Scott Hunter sharing new .NET Core 2.1.
With AI being top
Azure Network Watcher provides you the ability to monitor, diagnose, and gain insights into your network in Azure.
Among its suite of capabilities, Network Watcher offers the ability to log network traffic through Network Security Group (NSG) Flow Logging. When NSG Flow Logging is enabled, you gain access to Network flow-level data that has endless applications in security, compliance, and traffic monitoring use cases. Deeper analysis of this NSG flow data is available in Network Watcher using Traffic Analytics, which is currently in preview.
Since Azure Network Watcher’s inception, we have continuously partnered with leaders in the SIEM and Log Management industry to provide a rich ecosystem of tools that seamlessly integrate and understand your network in Azure. I would like to highlight two of the most recent partners, offering customers additional choice and value through integration with Azure. On top of our growing ecosystem, we have now enabled the option to send NSG Flow Log data across subscriptions which greatly enhances log management in larger environments.
McAfee Cloud Workload Security integration
Recently, McAfee announced the general availability of the Cloud Workload Security (CWS) Platform in Azure including integration with Network Watcher. CWS automates the discovery and defense of elastic workloads
We are delighted to announce the general availability of SQL Vulnerability Assessment for Azure SQL Database! SQL Vulnerability Assessment (VA) provides you a one-stop-shop to discover, track and remediate potential database vulnerabilities. It helps give you visibility into your security state, and includes actionable steps to investigate, manage and resolve security issues, and enhance your database fortifications. VA is available for Azure SQL Database customers as well as for on-premises SQL Server customers via SSMS.
If you have data privacy requirements or need to comply with data protection regulations like the European Union General Data Protection Regulation (EU GDPR), then VA is your built-in solution to simplify these processes and monitor your database protection status. For dynamic database environments where changes are frequent and hard to track, VA is invaluable in detecting the settings that can leave your database vulnerable to attack.
New SQL Advanced Threat Protection (ATP)
VA is being released to general availability (GA) as part of a new security package for your Azure SQL Database, called SQL Advanced Threat Protection (ATP). ATP provides a single go-to location for discovering, classifying and protecting sensitive data, managing your database vulnerabilities, and detecting anomalous activities that could indicate a