Abstract: Azure SQL DB offers disaggregated storage architecture called Hyperscale. While this architecture provides storage scale out, it comes at the cost of performance of I/O from remote storage.

Amid the AI-heavy headlines at Microsoft's annual conference, several behind-the-scenes updates landed that could have a major impact on how IT teams build, run and scale core infrastructure in Azure.

Enterprises need data, and data needs to be stored, with a flexible, portable environment that scales from developers’ laptops to global clouds. That storage also needs to be able to run on any OS and ...

With the official release of Microsoft's latest database offering, let's see what was improved and what still needs some work. Today, at Ignite, Microsoft announced the general availability of SQL ...

Horrifying footage has captured the moment a six-meter python dragged a tour guide underwater, just moments before coiling around his neck. Experienced snake catcher, Heru, was traveling down a river ...

NOTE: This article was published yesterday (30/10/2025), but due to some technical issues it went offline. Microsoft has officially added Python 3.14 to Azure App Service for Linux. Developers can now ...

Microsoft Azure experienced a global outage on October 29. Microsoft customer-facing services were affected. Recovery came later that same day, but some problems linger. Last week, Amazon Web Services ...

Microsoft released Azure Cosmos DB Python SDK version 4.14.0, a stable update designed to support advanced AI workloads and enhance performance for data-driven applications. The release includes new ...

OpenAI restructures, removing restriction on capital raise Microsoft holds 27% stake in OpenAI Group PBC Deal removes constraint on OpenAI's ability to raise capital Microsoft market value once again ...

Managing SQL Server across hybrid and multi-cloud environments has long posed a challenge for database administrators. With data sprawled across on-premises infrastructure, cloud platforms, and edge ...

Hello guys, I am working on creating a Monitoring using Azure ML mainly for checking the Data Quality signal (Quality of the baseline and production data) and Data Drift signal (Change in distribution ...

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