This week I’m highlighting a set of articles on Azure SQL Database Serverless, data virtualization with PolyBase, Azure Kubernetes Service and Azure Stream Analytics. Also, a very interesting podcast on cloud scaling from Carl and Richard on .NET Rocks. Enjoy!

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Podcasts

.NET Rocks

Episode 1816: Cloud Scaling from the Trenches with Meg Gotshall
Ready for a story of cloud scaling from the trenches? While at NDC Oslo, Carl and Richard talked with Meg Gotshall about her experiences scaling the Fotoware service with her team. Meg talks about the limits of auto-scaling, where all the services are scaled up, but the bottlenecks exist in only one place – and how dashboards help to provide more visibility into the problem. But even when you sense the problem, how do you fix it? The conversation digs into breaking services into their containers and AppService plans so they can be scaled independently – initially for diagnostics but ultimately for production!

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Data Virtualization

Introducing data virtualization with PolyBase
PolyBase enables your SQL Server instance to query data with T-SQL directly from SQL Server, Oracle, Teradata, MongoDB, Hadoop clusters, Cosmos DB, and S3-compatible object storage without separately installing client connection software. You can also use the generic ODBC connector to connect to additional providers using third-party ODBC drivers. PolyBase allows T-SQL queries to join the data from external sources to relational tables in an instance of SQL Server.

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Azure SQL

Azure SQL Database serverless
Serverless is a compute tier for single databases in Azure SQL Database that automatically scales compute based on workload demand and bills for the amount of compute used per second. The serverless compute tier also automatically pauses databases during inactive periods when only storage is billed and automatically resumes databases when activity returns.

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Azure Kubernetes Service

AKS, the elephant in the hub & spoke room, deep dive
AKS is not a service like others, it has a vast ecosystem and a different approach to networking. An AKS cluster is typically meant to host more than a single application, and you can’t afford to “simply” rely on the Hub & Spoke to manage network traffic. Kubernetes is aimed at abstracting away infrastructure components such as nodes, load balancers etc. Most K8s solutions are based on dynamic  rules and programmable networks…this is light years away from the rather static approach of NSGs and NVAs. A single AKS cluster might host hundreds of applications…That is why I consider AKS as the elephant in the Hub & Spoke room here. Somehow, AKS “breaks” the hub & spoke model, at least for East-West traffic. South-North traffic remains more controllable using traditional techniques, as it involves the cluster boundaries (IN and OUT).

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Azure Stream Analytics

Microsoft Releases Stream Analytics No-Code Editor into General Availability
During the Ignite Conference, Microsoft released Azure Stream Analytics no-code editor, a drag-and-drop canvas for developing jobs for stream processing scenarios such as streaming ETL, ingestion, and materializing data to data into general availability. The no-code editor is hosted in the company’s big-data streaming platform and event ingestion service, Azure Event Hubs.

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Other News

All 123 things we announced at Google Cloud Next ‘22
We loved hosting Google Cloud Next ‘22 this week in cities around the world and are excited to share our favorite moments and announcements. We kicked off our 24-hour livestream broadcast with an opening keynote in New York City, then moved west to share our “Top 10 Cloud Predictions” developer keynote from the Google Cloud headquarters in Sunnyvale, California. Next ‘22 then crossed the Pacific to Tokyo, Japan, then down to Bengaluru, India, and finished out in Munich, Germany. Here’s a full recap of all 123 (!) announcements we made this week, all in one place.

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Have an awesome week!

Photo by Vincent van Zalinge on Unsplash