This post is part 2 of a two-part series about how organizations use Azure Cosmos DB to meet real world needs, and the difference it’s making to them. In part 1, we explored the challenges that led the Microsoft Office Licensing Service team to move from Azure Table storage to Azure Cosmos DB, and how it migrated its production workload to the new service. In part 2, we examine the outcomes resulting from the team’s efforts.
Strong benefits with minimal effort
The Microsoft Office Licensing Service (OLS) team’s migration from Azure Table storage to Azure Cosmos DB was simple and straightforward, enabling the team to meet all its needs with minimal effort.
An easy migration
In moving to Azure Cosmos DB, thanks to its Table API, the OLS team was able to reuse most of its data access code, and the migration engine they wrote to avoid any downtime was fast and easy to build.
Danny Cheng, a software engineer at Microsoft, who leads the OLS development team explains:
“The migration engine was the only real ‘new code’ we had to write. And the code samples for all three parts are publicly available, so it’s not like we had to
This post is part 1 of a two-part series about how organizations use Azure Cosmos DB to meet real world needs, and the difference it’s making to them. In part 1, we explore the challenges that led the Microsoft Office Licensing Service team to move from Azure Table storage to Azure Cosmos DB, and how it migrated its production workload to the new service. In part 2, we examine the outcomes resulting from the team’s efforts.
The challenge: Limited throughput and other capabilities
At Microsoft, the Office Licensing Service (OLS) supports activation of the Microsoft Office client on millions of devices around the world—including Windows, Mac, tablets, and mobile. It stores information such as machine ID, product ID, activation count, expiration date, and more. OLS is accessed by the Office client more than more than 240 million times per day by users around the world, with the first call coming from the client upon license activation and then every 2-3 days thereafter as the client checks to make sure the license is still valid.
Until recently, OLS relied on Azure Table storage for its backend data store, which contained about 5 TB of data spread across 18 tables—with separate tables
This post is part 1 of a two-part series about how organizations use Azure Cosmos DB to meet real world needs and the difference it’s making to them. In part 1, we explore the challenges that led service developers for Minecraft Earth to choose Azure Cosmos DB and how they’re using it to capture almost every action taken by every player around the globe—with ultra-low latency. In part 2, we examine the solution’s workload and how Minecraft Earth service developers have benefited from building it on Azure Cosmos DB.
Extending the world of Minecraft into our real world
You’ve probably heard of the game Minecraft, even if you haven’t played it yourself. It’s the best-selling video game of all time, having sold more than 176 million copies since 2011. Today, Minecraft has more than 112 million monthly players, who can discover and collect raw materials, craft tools, and build structures or earthworks in the game’s immersive, procedurally generated 3D world. Depending on game mode, players can also fight computer-controlled foes and cooperate with—or compete against—other players.
In May 2019, Microsoft announced the upcoming release of Minecraft Earth, which began its worldwide rollout in December 2019. Unlike preceding games in the
This post is part 2 of a two-part series about out how organizations are using Azure Cosmos DB to meet real world needs and the difference it’s making to them. In part 1, we explored the challenges that led service developers for Minecraft Earth to choose Azure Cosmos DB and how they’re using it to capture almost every action taken by every player around the globe—with ultra-low latency. In part 2 we examine the solution’s workload and how Minecraft Earth service developers have benefited from building it on Azure Cosmos DB.
Geographic distribution and multi-region writes
Minecraft Earth service developers used the turnkey geographic distribution feature in Azure Cosmos DB to achieve three goals: fault tolerance, disaster recovery, and minimal latency—the latter achieved by also using the multi-master capabilities of Azure Cosmos DB to enable multi-region writes. Each supported geography has at least two service instances. For example, in North America, the Minecraft Earth service runs in the West US and East US Azure regions, with other components of Azure used to determine which is closer to the user and route traffic accordingly.
Nathan Sosnovske, a Senior Software Engineer on the Minecraft Earth services development team explains:
“With Azure available
Processing Big data in real-time is an operational necessity for many businesses. Azure Stream Analytics is Microsoft’s serverless real-time analytics offering for complex event processing.
We are excited and humbled to announce that Microsoft has been named a leader in The Forrester Wave™: Streaming Analytics, Q3 2019. Microsoft believes this report truly reflects the market momentum of Azure Stream Analytics, satisfied customers, a growing partner ecosystem and the overall strength of our Azure cloud platform. You can access the full report here.
The Forrester Wave™: Streaming Analytics, Q3 2019
Forrester Wave™: Streaming Analytics, Q3 2019 report evaluated streaming analytics offerings from 11 different solution providers and we are honored to share that that Forrester has recognized Microsoft as a Leader in this category. Azure Stream Analytics received the highest possible score in 12 different categories including Ability to execute, Administration, Deployment, Solution Roadmap, Customer adoption and many more.
The report states, “Microsoft Azure Stream Analytics has strengths in scalability, high availability, deployment, and applications. Azure Stream Analytics is an easy on-ramp for developers who already know SQL. Zero-code integration with over 15 other Azure services makes it easy to try and therefore adopt, making the product the
Today, businesses are forced to maintain two types of analytical systems, data warehouses and data lakes. Data warehouses provide critical insights on business health. Data lakes can uncover important signals on customers, products, employees, and processes. Both are critical, yet operate independently of one another, which can lead to uninformed decisions. At the same time, businesses need to unlock insights from all their data to stay competitive and fuel innovation with purpose. Can a single cloud analytics service bridge this gap and enable the agility that businesses demand?
Azure Synapse Analytics
Today, we are announcing Azure Synapse Analytics, a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs.
Simply put, Azure Synapse is the next evolution of Azure SQL Data Warehouse. We have taken the same industry-leading data warehouse to a whole new level of performance and capabilities. In fact, it’s the first and only analytics system to have
Azure Stream Analytics is a fully managed Platform as a Service (PaaS) that supports thousands of mission-critical customer applications powered by real-time insights. Out-of-the-box integration with numerous other Azure services enables developers and data engineers to build high-performance, hot-path data pipelines within minutes. The key tenets of Stream Analytics include Ease of use, Developer productivity, and Enterprise readiness. Today, we’re announcing several new features that further enhance these key tenets. Let’s take a closer look at these features:
Rollout of these preview features begins November 4th, 2019. Worldwide availability to follow in the weeks after.
In the past, changing Streaming Units (SUs) allocated for a Stream Analytics job required users to stop and restart. This resulted in extra overhead and latency, even though it was done without any data loss.
With online scaling capability, users will no longer be required to stop their job if they need to change the SU allocation. Users can increase or decrease the SU capacity of a running job without having to stop it. This builds on the customer promise of long-running mission-critical pipelines that Stream Analytics offers today.
Change SUs on a Stream Analytics job while it is running.
A data-driven culture is critical for businesses to thrive in today’s environment. In fact, a brand-new Harvard Business Review Analytic Services survey found that companies who embrace a data-driven culture experience a 4x improvement in revenue performance and better customer satisfaction.
Foundational to this culture is the ability to deliver timely insights to everyone in your organization across all your data. At our core, that is exactly what we aim to deliver with Azure Analytics and Power BI, and our work is paying off in value for our customers. According to a recent commissioned Forrester Consulting Total Economic Impact™ study, Azure Analytics and Power BI deliver incredible value to customers with a 271 percent ROI, while increasing satisfaction by 60 percent.
Our position in the leaders quadrant in Gartner’s 2019 Magic Quadrant for Analytics & Power BI, coupled with our undisputed performance in analytics provides you with the foundation you need to implement a data-driven culture.
But what are three key attributes needed to establish a data-driven culture?
First, it is vital to get the best performance from your analytics solution across all your data, at the best possible price.
Second, it is critical that your data is accurate and
Today Microsoft published an independent security assessment of 113 Microsoft Azure services for their suitability to handle official and PROTECTED Australian government information. This assessment, carried out under the Information Security Registered Assessor Program (IRAP), is now available for customers and partners to review and use as they plan for increasing the use of cloud in government.
This milestone significantly expands the ability of the Australian government to leverage Microsoft Azure to drive digital transformation. The expanded scope of this IRAP assessment includes cognitive services, machine learning, IoT, advanced cybersecurity, open source database management, and serverless and application development technologies. This enables the full range of innovation within Azure Australia to be utilized for government applications, further reinforcing our commitment to achieving the broadest range of accreditations and assurances to meet the needs of government customers.
This assurance is critical for customers such as the Victorian Government, using ICT shared services provider Cenitex in partnership with Canberra-based OOBE to deploy VicCloud Protect, a ground-breaking and highly secure service that enables its government customers to safely manage applications and data rated up to PROTECTED level.
“VicCloud Protect is a first for the Victorian Government and our customers can now confidently
The tech world is fast-paced, and cloud services like Azure Cosmos DB get frequent updates with new features, capabilities, and improvements. It’s important—but also challenging—to keep up with the latest performance and security updates and assess whether they apply to your applications. To make it easier, we’ve introduced automatic and tailored recommendations for all Azure Cosmos DB users. A large spectrum of personalized recommendations now show up in the Azure portal when you browse your Azure Cosmos DB accounts.
Some of the recommendations we’re currently dispatching cover the following topics
SDK upgrades: When we detect the usage of an old version of our SDKs, we recommend upgrading to a newer version to benefit from our latest bug fixes and performance improvements. Fixed to partitioned collections: To fully leverage Azure Cosmos DB’s massive scalability, we encourage users of legacy, fixed-sized containers that are approaching the limit of their storage quota to migrate these containers to partitioned ones. Query page size: We recommend using a query page size of -1 for users that define a specific value instead. Composite indexes: Composite indexes can dramatically improve the performance and RU consumption of some queries, so we suggest their usage whenever our telemetry detects