Dynamics 365 is a set of intelligent SaaS business applications that helps companies of all sizes, from all industries, to run their entire business and deliver greater results through predictive, AI-driven insights. Dynamics 365 applications are built on top of Microsoft Power Platform that provides a scalable foundation for running not just. Power Platform (also offering services like Power Apps, Power Automate, Power Virtual Agents and PowerBI) is based on Microsoft Azure services, like Azure SQL Database, which offer scalable and reliable underlying compute, data, management and security services that power the entire stack.
Many thanks to our colleagues Mahesh Sreenivas, Pranab Mazumdar, Karthick Pakirisamy Krishnamurthy, Mayank Mehta and Shovan Kar from Microsoft Dynamics team for their contribution to this article.
Dynamics 365 is a set of intelligent SaaS business applications that helps companies of all sizes, from all industries, to run their entire business and deliver greater results through predictive, AI-driven insights. Dynamics 365 applications are built on top of a Microsoft Power Platform that provides a scalable foundation for running not just Dynamics apps themselves, but also to let customers, system integrators and ISVs to create customizations for specific verticals, and connect their business processes to other solutions and systems leveraging hundreds of pre-existing connectors with a no-code / low-code approach.
Microsoft Power Platform (also offering services like Power Apps, Power Automate, Power Virtual Agents and PowerBI) has been built on top of Microsoft Azure services, like Azure SQL Database, which offer scalable and reliable underlying compute, data, management and security services that power the entire stack represented in the picture above.
Microsoft Dynamics 365 has its roots in a suite of packaged business solutions, like Dynamics AX, NAV and CRM, running on several releases of Windows Server and SQL Server on customers’ datacenters around the world.
When Software as a Service paradigm emerged to dominate business applications’ industry, Dynamics CRM led the pack becoming one of the first Microsoft’s online services. At the beginning of the SaaS journey, Dynamics services ran on of bare-metal servers in Microsoft’s on-premises datacenters. With usage growing every day, into millions of active users, the effort required to deploy and operate all those servers, manage capacity demands, and respond promptly to issues of continuously growing customer data volumes (with database size distribution from 100 MB up to more than 4 TB for the largest tenants) would eventually become unmanageable.
Dynamics was one of the first adopters of Microsoft SQL Server 2012 AlwaysOn to achieve business continuity, but also to provide a flexible way to move customer databases to new clusters by creating additional replicas to rebalance utilization.
Managing so many databases at scale was clearly a complex task, involving the entire database lifecycle from initial provisioning to monitoring, patching and operating this large fleet while guaranteeing availability, and team learned how to deal with issues like quorum losses and replicas not in a failover-ready state. From a performance perspective, database instances running on shared underlying nodes, made it hard to isolate performance issues and provided limited options to scale up or accommodate workload burst other than moving individual instances to new nodes.
As end customers can run multiple versions of (highly-customized) applications in their environments, generating significantly different workloads, it is no surprise to hear from Mahesh Sreenivas, Partner Group Engineering Manager on the Common Data Service team, that to manage and maintain all this on a traditional platform was “painful for both engineers and end customers”.
Dynamics 365 team decided to move their platform to Microsoft Azure to solve these management and operational challenges while meeting customer requirements, ensuring platform fundamentals like availability and reliability, and letting the engineering team to focus on adding innovative new features.
Engineering effort from initial designs to production took a couple of years, including migration of the customers to the new Azure based platform, moving from a monolithic code base running on-premises into a world-class planet scale service running on Azure.
The first key decision was to transition from a suite of heterogeneous applications, each one with its own history and technical peculiarities, to a common underlying platform where Dynamics applications were going to be regular applications just like what other ISV companies could build and run: hence Microsoft Power Platform and its Common Data Service layer was introduced. Essentially, a new no-code, low-code platform built on top of underlying Azure capabilities like Compute, Storage, Network and other specialized services like Azure SQL Database was a way to abstract Dynamics applications from underlying platform, letting Dynamics developers to focus on transitioning to the platform without managing individual resources like database instances.
The same platform today is also hosting other services like PowerApps, Power Automate, Power Virtual Agents or PowerBI, and it is available for other companies to build their own SaaS applications on top of, from no-code simple solutions to full-code specialized ISV apps that don’t need to worry about how to manage underlying resources like compute and various storage facilities.
By moving to Azure a platform that is managing around 1M database instances (as of July 2020), Dynamics team learned a lot about how underlying services are working, but also provided enormous feedback to other Microsoft teams to make their services better in a mutually beneficial relationship.
From an architectural perspective, Common Data Service is organized in logical stamps (or scale groups) that have two tiers, compute and data, where the relational data store is built on Azure SQL Database given team’s previous familiarity with SQL Server 2012 and 2016 on premises. This provides out of the box, pre-configured high availability with a 3 (or more) nines SLA, depending on selected service tiers. Business Continuity is also guaranteed through features like Geo-restore, Active Geo-replication and Auto Failover Groups.
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
In this video, see how to configure your Azure SQL connectivity leveraging the Azure CLI and PowerShell notebooks in Azure Data Studio. For the full Azure SQ...
Azure SQL is composed of Azure SQL Database, Azure SQL Managed Instance, and SQL Server in Azure VM. Learn about the key differentiators between them. For th...
In this article, we will go through the different database services that are provided by Microsoft Azure to help you in selecting the proper service that can serve your SQL workload when migrating it to Microsoft Azure
Are you interested in learning how to translate your existing SQL Server expertise to Azure SQL including Azure SQL Database and Azure SQL Managed Instance? In this episode, Bob Ward, Anna Hoffman, and Marisa Brasile announce all-new content on YouTube, Github, and Microsoft Learn to help you become an Azure SQL professional.