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Automated Azure cost optimisation tools are useful — but they don’t tell the whole story. Especially if you’re building and running your own applications in Azure. Real savings often sit at the architecture and code level, where experience and application insight outperform generic automation.
AI adoption often stalls between endless strategy and fragmented experimentation. Instead of choosing one, organisations can evolve both in parallel — building clearer objectives, growing confidence and delivering measurable value along the way.
AI creates real competitive advantage when it’s embedded in core business decisions and workflows – not just support functions. Here’s why leaders must rethink where AI is applied to unlock meaningful value.
Discover the newest additions to our blog—fresh insights, real-world case studies, and practical strategies from our team and contributors. These articles build on the ideas introduced above, offering deeper dives into the topics that matter most. Whether it's emerging technologies, proven business practices, or thought-provoking commentary, you'll find content designed to inform, challenge, and inspire.
When you use Azure Websites you can do continuous deployment using Git, but with cloud services you can only do it from TFS. Luckily, it is quite easy to set up a Powershell script to deploy to Cloud Services. In this post I will share a sample script that can be used to deploy to multiple different environments, such as a UAT and a Live environment.
In this post I will show how to set up an Azure Web Job to automatically reboot a worker role at certain times. It's just an example, you can schedule pretty much any Azure operation in this way, including shutting down VMs at the end of the day etc.
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