Kirill Gavrylyuk joins Scott Hanselman to go over two important updates to Azure Cosmos DB: Free Tier and Autopilot.

Free Tier enables you to run small applications using Azure Cosmos DB free of charge for as long as you like. Autopilot enables developers to only pay for the Azure Cosmos DB usage they need and not worry about predicting throughput.

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In this video, Jeremy Likness chats with software engineer Matías Quaranta about some of the lesser known features of the Cosmos DB SDK for .NET. Matias discusses some useful patterns for managing the lifetime of the client, implementing custom serializers and some other interesting features.

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Matías Quaranta (@ealsur) shows Donovan Brown (@donovanbrown) how to do bulk operations with the Azure Cosmos DB .NET SDK to maximize throughput, and how to use the new Transactional Batch support to create atomic groups of operations.

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Tim Sander joins Scott Hanselman to discuss composite indexes and correlated subqueries using the SQL API in Azure Cosmos DB.

A Request Unit, or RU, is the measure of throughput in Azure Cosmos DB. Learn how to optimize queries with a composite index to decrease the RUs needed for a given query.

They also showcase correlated subqueries and examples of how they can make it easier to query arrays in Azure Cosmos DB.

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              Watch this IoT Show to learn why Azure Cosmos DB (aka.ms/CosmosDB-IoT-Lab), Microsoft’s globally distributed multi-model database service, is frequently used in IoT scenarios.

              Cosmos DB can ingest semi-structured data at extremely high rates and serve indexed queries back out with extremely low latency.

              Andrew Liu, Program Manager, Cosmos DB team, steps through two popular IoT use cases and demos the four things IoT developers “must know” about Azure Cosmos DB. You will receive instructions on how to get started with a hands-on lab.

              Resources

              XTO Energy , a subsidiary of ExxonMobil, taps into IoT

              Kirill Gavrylyuk joins Scott Hanselman to show how to run Jupyter Notebook and Apache Spark in Azure Cosmos DB. Now you can use the interactive experience of Jupyter Notebook and analytics powered by Apache Spark with your operational data. Run analytics and ML on your operational data in real time without data movement, and without the need to split into transactional and analytical silos.

              [00:02:18] Jupyter Notebook demo

              [00:05:41] Jupyter Notebook + Apache Spark demo     

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              Deborah Chen joins Scott Hanselman to share some best practices on how to debug and optimize Azure Cosmos DB for better performance. Watch as they go through the common issues newcomers to Azure Cosmos DB run into with respect to performance and how to solve them by tuning Request Unit (RU) cost and choosing a good partition key.

              Links related to Debugging and Optimizing Azure Cosmos DB Performance

              Here’s an interesting blog blost co-authored by Shweta Mishra and Vinil Menon, both of CitiusTech. CitiusTech is a specialist provider of healthcare technology services which helps its customers to accelerate innovation in healthcare.  CitiusTech used Azure Cosmos DB to simplify the real-time collection and movement of healthcare data from variety of sources in a secured manner.

              With the proliferation of patient information from established and current sources, accompanied with scrupulous regulations, healthcare systems today are gradually shifting towards near real-time data integration. 

              The rise of Internet of Things (IoT) has enabled ordinary medical devices, wearables, traditional hospital deployed medical equipment to collect and share data. Within a wide area network (WAN), there are well defined standards and protocols, but with the ever increasing number of devices getting connected to the internet, there is a general lack of standards compliance and consistency of implementation. Moreover, data collation and generation from IoT enabled medical/mobile devices need specialized applications to cope with increasing volumes of data.