Author : All posts by ilikesql

04

Jan

Asynchronous refresh with the REST API for Azure Analysis Services

Azure Analysis Services unlocks datasets with potentially billions of rows for non-technical business users to perform interactive analysis. Such large datasets can benefit from features such as asynchronous refresh.

We are pleased to introduce the REST API for Azure Analysis Services. Using any programming language that supports REST calls, you can now perform asynchronous data-refresh operations. This includes synchronization of read-only replicas for query scale out. Please see the blog post Introducing query replica scale-out for Azure Analysis Services for more information on query scale out.

Data-refresh operations can take some time depending on various factors, including data volume and level of optimization using partitions. These operations have traditionally been invoked with existing methods such as using TOM (Tabular Object Model), PowerShell cmdlets for Analysis Services, or TMSL (Tabular Model Scripting Language). The traditional methods may require long-running HTTP connections. A lot of work has been done to ensure the stability of these methods, but given the nature of HTTP, it may be more reliable to avoid long-running HTTP connections from client applications.

The REST API for Azure Analysis Services enables data-refresh operations to be carried out asynchronously. It therefore does not require long-running HTTP connections from client applications. Additionally,

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03

Jan

Hello 2018 | Recap of “Top 10” Posts of 2017
Hello 2018  |  Recap of “Top 10” Posts of 2017

As we ring in the new year, we’d like to kick things off in our usual fashion – with a quick recap of our most popular posts from the year just concluded. So here are our “Top 10” posts from 2017, sorted in increasing order of readership – enjoy!

10. Quick-Start Guide to the Data Science Bowl Lung Cancer Detection Challenge, Using Deep Learning, Microsoft Cognitive Toolkit and Azure GPU VMs

Lung cancer – which is the leading cancer when it comes to mortality in both women and men in the US – suffers from a low rate of early diagnosis. The Data Science Bowl competition aimed to help by having participants use machine learning to determine whether CT scans of the lung have cancerous lesions or not. Success in the competition required that data scientists get started quickly and iterate rapidly. Through this post, we showed how to compute features of scanned images with a pre-trained Convolutional Neural Network (CNN), and use these features to classify scans as cancerous or not using a boosted tree – all within one hour.

9. Machine Learning for Developers – How to Build Intelligent Apps & Services

Traditionally, developers would build rules-based engines

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03

Jan

Securing Azure customers from CPU vulnerability
Securing Azure customers from CPU vulnerability

An industry-wide, hardware-based security vulnerability was disclosed today. Keeping customers secure is always our top priority and we are taking active steps to ensure that no Azure customer is exposed to these vulnerabilities. At the time of this blog post, Microsoft has not received any information to indicate that these vulnerabilities have been used to attack Azure customers.

The majority of Azure infrastructure has already been updated to address this vulnerability. Some aspects of Azure are still being updated and require a reboot of customer VMs for the security update to take effect. Many of you have received notification in recent weeks of a planned maintenance on Azure and have already rebooted your VMs to apply the fix, and no further action by you is required.

With the public disclosure of the security vulnerability today, we are accelerating the planned maintenance timing and will begin automatically rebooting the remaining impacted VMs starting at 3:30pm PST on January 3, 2018. The self-service maintenance window that was available for some customers has now ended, in order to begin this accelerated update.

During this update, we will maintain our SLA commitments of Availability Sets, VM Scale Sets, and Cloud Services. This reduces impact

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03

Jan

Year in Review Contest: Jan. 3-Jan. 31
Year in Review Contest: Jan. 3-Jan. 31

https://powerbi.microsoft.com/en-us/blog/year-in-review-contest/Source: https://powerbi.microsoft.com/en-us/blog/year-in-review-contest/           Happy New Year! What better way to kick off 2018 than by entering this contest for a chance to win a fabulous prize? Read the full blog post for details and the link READ MORE

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03

Jan

Designing, building, and operating microservices on Azure
Designing, building, and operating microservices on Azure

I’m excited to announce that the AzureCAT patterns and practices team has published new guidance about microservices titled Designing, building, and operating microservices on Azure.

Microservices have become a popular architectural style for building cloud applications that are resilient, highly scalable, and able to evolve quickly. To be more than just a buzzword, however, microservices require a different approach to designing and building applications.

In this set of articles, we explore how to build and run a microservices architecture on Azure, using Kubernetes as a container orchestrator. Future articles will include Service Fabric. Topics include:

Using Domain Driven Design (DDD) to design a microservices architecture. Choosing the right Azure technologies for compute, storage, messaging, and other elements of the design. Understanding microservices design patterns. Designing for resiliency, scalability, and performance. Building a CI/CD pipeline.

Throughout, we focus on an end-to-end scenario for a drone delivery service that lets customers schedule packages to be picked up and delivered via drone. A reference implementation for this project is available on GitHub.

The reference implementation includes a number of different Azure and open source technologies:

Azure Container Service (Kubernetes) to run frontend and backend services. Azure Functions to run event driven services. Linkerd

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03

Jan

Build richer apps with your time series data
Build richer apps with your time series data

Today, we are pleased to announce the release of new TSI developer tools, including an Azure Resource Manager (ARM) template, API code samples, and easy-to-follow documentation for developers. TSI’s developer tools will shorten the time it takes to get started developing. Using these developer tools, customers can more easily embed TSI’s platform into custom applications to power charts/graphs, compare data from different points in time, and dynamically explore trends and correlations in their data.

As organizations transition their go-to-market and business models from selling devices to selling services, they are developing companion applications that provide operational insights and analytics to their customers.  Much of the data required to power these applications is time series, but large volumes of time series data can be very challenging to store and query. Time Series Insights (TSI) takes the burden of time series data management away from these organizations, and TSI’s platform capabilities enable developers to build applications that provide valuable insights to their customers.

Why time series data is difficult to embed in applications today

Time series data at IoT-scale can lead to high latency and long rendering times when querying traditional databases. Many customers have told us that it’s easy to hang

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03

Jan

Azure Data Lake tools integrates with VSCode Data Lake Explorer and Azure Account

If you are a data scientist and want to explore the data and understand what is being saved and what the hierarchy of the folder is, please try Data Lake Explorer in VSCode ADL Tools. If you are a developer and look for easier navigation inside the ADLS, please use Data Lake Explorer in VSCode ADL Tools. The VSCode Data Lake Explorer enhances your Azure login experiences, empowers you to manage your ADLA metadata in a tree like hierarchical way and enables easier file exploration for ADLS resources under your Azure subscriptions. You can also preview, delete, download, and upload files through contextual menu. With the integration of VSCode explorer, you can choose your preferred way to manage your U-SQL databases and your ADLS storage accounts in addition to the existing ADLA and ADLS commands.

If you have difficulties to login to Azure and look for simpler sign in processes, the Azure Data Lake Tools integration with VSCode Azure account enables auto sign in and greatly enhance the integration with Azure experiences. If you are an Azure multi-tenant user, the integration with Azure account unblocks you and empowers you to navigate your Azure subscription resources across tenants.

If your source

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03

Jan

Year in Review Contest: Jan. 3-Jan. 31
Year in Review Contest: Jan. 3-Jan. 31

https://powerbi.microsoft.com/en-us/blog/year-in-review-contest-jan-3-jan-31/Source: https://powerbi.microsoft.com/en-us/blog/year-in-review-contest-jan-3-jan-31/           Happy New Year! What better way to kick off 2018 than by entering this contest for a chance to win a fabulous prize? Read the full blog post for details and the link READ MORE

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03

Jan

Azure Analysis Services features on Azure Friday
Azure Analysis Services features on Azure Friday

Built on the proven analytics engine in Microsoft SQL Server Analysis Services, Azure Analysis Services delivers enterprise-grade BI semantic modeling capabilities with the scale, flexibility, and management benefits of the cloud. The success of any modern data-driven organization requires that information is available at the fingertips of every business user, not just IT professionals and data scientists, to guide their day-to-day decisions. Azure Analysis Services helps you transform complex data into actionable insights. Users in your organization can then connect to your data models using tools like Excel, Power BI, and many others to create reports and perform ad-hoc interactive analysis.

I joined Scott on Azure Friday to talk about some new features in Azure Analysis Services. Query scale out and diagnostic logging were announced at the SQL PASS Summit 2017 and both lend themselves particularly well to the cloud.

Query scale out for Azure Analysis Services allows client queries to be distributed among multiple query replicas in a query pool, reducing response times during high query workloads. You can also separate processing from the query pool, ensuring client queries are not adversely affected by processing operations. If you have ever set up scale out on premises, you might be

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03

Jan

Migration checklist when moving to Azure App Service
Migration checklist when moving to Azure App Service

I have been continuously getting requests from customers, colleagues and partners around what to consider when migrating applications to Azure PaaS service but more specifically to the App Service.

This post tries to cover the majority of those cases and aims to provide a checklist and ready reckoner for customers/partners intending to migrate their existing applications to Azure App Service.

To start, let’s have a look at various considerations before you consider migrating your applications to Azure App Service

Port Bindings – Azure App Service support port 80 for http and port 443 for HTTPS traffic. If you have sites using any other port after migration to Azure App Service, do remember that these are the only ports that will be used. Usage of assemblies in the GAC (Global Assembly Cache)- This is not supported. Consider bin placing the assemblies in the local bin. IIS5 Compatibility Mode– IIS5 Compatibility Mode is not supported. In Azure App Service each Web App and all the applications under it run in the same worker process with a specific set of application pool settings. IIS7+ Schema Compliance– One or more elements and/or attributes are being used which are not defined in Azure App Service

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