Azure Analysis Services new modeling and tooling features

Following the announcement a few weeks ago that 1400 models are now in Azure Analysis Services, we haven’t stopped there! We are pleased to announce the following further features for 1400 models in Azure.

Shared M expressions are shown in the SSDT Tabular Model Explorer, and can be maintained using the Query Editor.
Data Management View (DMV) improvements.
Opening an file with the .MSDAX extension in SSDT enables DAX non-model related IntelliSense.

Shared M expressions

Shared M expressions are shown in the Tabular Model Explorer! By right clicking the Expressions node, you can edit the expressions in the Query Editor. This should seem familiar to Power BI Desktop users.

DMV improvements

DMVs expose information about server operations and server health, settings and model structure. They are used for server monitoring, model documentation and various other reasons.

DISCOVER_CALC_DEPENDENCY

M expression dependencies are included in DISCOVER_CALC_DEPENDENCY. The following query returns the output shown below. M expressions and structured data sources are included for 1400 models.

SELECT * FROM $System.DISCOVER_CALC_DEPENDENCY

WHERE OBJECT_TYPE = 'PARTITION' OR OBJECT_TYPE = 'M_EXPRESSION';

 

The output represents the same information that is shown by the Query Dependencies visual, which is now available in SSDT from the Query Editor. This visual should seem familiar to Power BI Desktop users.

MDSCHEMA_MEASUREGROUP_DIMENSIONS

This release provides a fix for MDSCHEMA_MEASUREGROUP_DIMENSIONS. This DMV is used by various client tools to show measure dimensionality. For example, the Explore feature in Excel Pivot Tables allows the user to cross-drill to dimensions related to the selected measures.

Prior to this release, some rows were missing in the output for 1200 models, which meant the Explore feature did not work correctly. This is now fixed for 1200 and 1400 models.

DAX file editing

Opening a file with the .MSDAX extension allows DAX editing with non-model related IntelliSense such as highlighting, statement completion and parameter info. As you can imagine, we intend to use this for interesting features to be released in the future!

Try it Now!

To get started, simply create a 1400 model in SSDT and deploy it to Azure Analysis Services! See this post on how to create your first model. Be sure to keep an eye on this blog to stay up to date on Azure Analysis Services.
Quelle: Azure

Use SaaS patterns to accelerate SaaS app development on SQL Database

We’re delighted to announce availability of a sample SaaS application and a series of management scripts and tutorials that demonstrate a range of SaaS-focused design and management patterns that can accelerate SaaS application development on SQL Database. These patterns extend the benefits of SQL Database, making it the most effective and easy-to-manage data platform for a wide range of data-intensive multi-tenant SaaS applications.

Database-per-tenant model gives tenant isolation

The discussion around patterns starts with the consideration of what data model to use. Multi-tenant applications have traditionally been implemented using a multi-tenant database. While multi-tenant databases remain effective for some applications, particularly where the amount of data stored per tenant is small, many SaaS applications benefit from the isolation inherent in using a database per tenant. The fully-managed nature of SQL Database and the use of elastic pools have made managing massive numbers of databases practical. Many ISVs are now running SaaS applications on SQL Database with tens of thousands of tenant databases in elastic pools. MYOB, a leading Australian accounting ISV, is managing over 130,000 tenant databases without breaking a sweat! A database-per-tenant model allows these customers to achieve levels of tenant isolation not possible with a multi-tenant database, with improvements in data security, privacy, performance management, extensibility, and more.

Learning from customer experience

By working closely with many of these customers, and learning from their experience, we have harvested a set of design and management patterns applicable to any business domain that simplify the adoption of a database-per-tenant approach and its use at scale. Based on these patterns, a sample SaaS application and a set of management scripts, backed by easy-to-follow tutorials, is now available, with all code on GitHub and the tutorials online.

You can install the sample application in less than 5 minutes and explore the patterns first-hand by playing with the app and looking at how it’s built using the Azure portal, SQL Server Management Studio, and Visual Studio. By studying the app and management scripts, and working through the tutorials, you can jump start your own SaaS app project.

The sample app is a simple event listing and ticketing SaaS app, where each venue has its own database with events, ticket prices, customers, and ticket sales, all securely isolated from other venues’ data. The app uses a canonical SaaS app architecture for the data layer. Each tenant is mapped to its database using a catalog database, which is used for lookup and connectivity. Other databases are installed to enable other scenarios as you explore the various tutorials.

SaaS scenarios explored

The app and management scripts address many common SaaS-related scenarios, including:

Tenant registration, including database provisioning and initialization, and catalog registration
Routing and connection from the app to the correct tenant database
Database performance monitoring, alerting and management, including cross-pool monitoring and alerting
Schema management, including deployment of schema changes and reference data to all tenant databases
Distributed query across all tenant databases, allowing ad hoc real-time query and analysis
Extract of tenant data into an analytics database or data warehouse
Restoring a single tenant database to a point in time

A load generator simulates unpredictable tenant activity, allowing you to explore resource management scenarios, including scaling pools to handle daily or weekly workload patterns, load-balancing pools, and managing large variations in individual tenant workloads. A ticket-generator allows you to explore analytics scenarios with significant amounts of data.

The app also benefits from other SQL Database features that are especially relevant in a database-per-tenant context, including automatic intelligent index tuning, that optimizes tenant database performance based on each tenant’s actual workload profile.

Integrated with other Azure Services for an end-to-end SaaS scenario

Several other Azure services are also showcased as part of the app, including App Services and Traffic Manager in the app layer, Log Analytics (OMS) for monitoring and alerting at scale, SQL Data Warehouse for cross-tenant analytics, and Azure Resource Management (ARM) templates for deployment.

The app will be extended over time to include more scenarios, from additional management patterns to deeper integration with other Azure services, including Power BI, Azure Machine Learning, Azure Search, and Active Directory, to build out a complete E2E SaaS scenario. We also want to explore the same scenarios with a multi-tenant database model in due course.

These SaaS patterns are also informing planning for future improvements to the SQL Database service.

Get started

Get started by installing the app with one click from GitHub, where you can download the code and management scripts.  Learn more about the patterns and explore the tutorials. Let us know at saasfeedback@microsoft.com what you think of the sample and the patterns, and what you’d like to see added next.
Quelle: Azure

Recent blog posts – May 22nd

Here’s some of the recent blog posts from our community:

Some lessons an IT department can learn from OpenStack by jpena

I have spent a lot of my professional career working as an IT Consultant/Architect. In those positions, you talk to many customers with different backgrounds, and see companies that run their IT in many different ways. Back in 2014, I joined the OpenStack Engineering team at Red Hat, and started being involved with the OpenStack community. And guess what, I found yet another way of managing IT.

Read more at http://rdoproject.org/blog/2017/05/some-lessons-an-it-department-can-learn-from-openstack/

When is it not cool to add a new OpenStack configuration option? by assafmuller

Adding new configuration options has a cost, and makes already complex projects (Hi Neutron!) even more so. Double so when we speak of architecture choices, it means that we have to test and document all permutations. Of course, we don’t always do that, nor do we test all interactions between deployment options and other advanced features, leaving users with fun surprises. With some projects seeing an increased rotation of contributors, we’re seeing wastelands of unmaintained code behind left behind, increasing the importance of being strategic about introducing new complexity.

Read more at https://assafmuller.com/2017/05/19/when-is-not-cool-to-add-a-new-openstack-configuration-option/

Running (and recording) fully automated GUI tests in the cloud by Matthieu Huin

The problem Software Factory is a full-stack software development platform: it hosts repositories, a bug tracker and CI/CD pipelines. It is the engine behind RDO’s CI pipeline, but it is also very versatile and suited for all kinds of software projects. Also, I happen to be one of Software Factory’s main contributors. :)

Read more at http://rdoproject.org/blog/2017/05/running-and-recording-fully-automated-GUI-tests-in-the-cloud/
Quelle: RDO

We're all about the quality: Azure achieves ISO 9001:2015 certification

As part of our ongoing effort to deliver the broadest and deepest set of compliance offerings, Microsoft Azure is proud to announce that we obtained the ISO 9001:2015 certification, addressing Quality Management systems.

This international standard is based on seven quality management principles:

Customer focus
Leadership commitment to quality objectives
Employee engagement in the quality goals set by leadership
Process-driven approach to achieve quality objectives
Continuous Improvement
Evidence-based decision making
Customer and partner relationship management

ISO 9001:2015 provides guidance on implementing a quality management system focused on delivering quality products and maintaining a constant state of improvement to exceed customer expectations. This certification (our 5th in the ISO family of certifications) is in perfect alignment with our goal to enable customers by providing the leverage of our compliant and quality products across a broad range of regulated industries, markets, and regions.  Achieving this certification underscores our drive to provide the most quality product possible.

The ISO 9001:2015 certificate for Microsoft Azure can be downloaded from here . The certificate covers 52 services across the following offerings: Azure, Cloud App Security, Intune, PowerApps, Power BI, Flow, Genomics, Graph (detailed scope is listed on the certificate).

For more information on Microsoft Azure’s ISO 9001:2015 Certification and our vast compliance portfolio, please visit the Microsoft Trust Center.
Quelle: Azure