Konstantinos Passadis

Solutions Architect – Microsoft Azure MVP

Speaker's Bio

Konstantinos is a passionate IT professional and Microsoft Certified Trainer with over two decades of experience in crafting and deploying comprehensive IT solutions. His expertise lies in Microsoft technologies, evident in his Microsoft Azure MVP status. As a Cloud Solutions Architect, he specializes in designing enterprise architectures for cloud environments, including Azure, M365, and hybrid/multi-cloud solutions. Konstantinos is a lifelong learner, continually expanding his knowledge and certifications across various vendors, primarily Microsoft.
He is a dedicated community leader and advocate, spearheading knowledge-sharing initiatives through his Microsoft Tech Group, live sessions, and blog posts.

Konstantinos is a passionate IT professional and Microsoft Certified Trainer with over two decades of experience in crafting and deploying comprehensive IT solutions. His expertise lies in Microsoft technologies, evident in his Microsoft Azure MVP status. As a Cloud Solutions Architect, he specializes in designing enterprise architectures for cloud environments, including Azure, M365, and hybrid/multi-cloud solutions. Konstantinos is a lifelong learner, continually expanding his knowledge and certifications across various vendors, primarily Microsoft.
He is a dedicated community leader and advocate, spearheading knowledge-sharing initiatives through his Microsoft Tech Group, live sessions, and blog posts.

In this demonstration, we delve into building an Azure Container Apps stack. This innovative approach allows us to deploy a Web App that facilitates interaction with three powerful models: GPT-4, Deepseek, and PHI-3. Users can select from these models for Chat Completions, gaining invaluable insights into their actual performance, token consumption, and overall efficiency through real-time metrics.
This deployment not only showcases the versatility and robustness of Azure AI Foundry but also provides a practical framework for businesses to observe and measure AI effectiveness, paving the way for data-driven decision-making and optimized AI solutions.