Review Summary
Users appreciate Microsoft Foundry for its seamless integration with the Microsoft ecosystem, robust AI tools, and u ...
Users appreciate Microsoft Foundry for its seamless integration with the Microsoft ecosystem, robust AI tools, and u ...
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The data perception and analytics speed is outstanding, allowing our engineering teams to watch complex asset trends update in near real-time without sluggishness. It handles system integration across different cloud databases and local storage layers smoothly, keeping our operational histories highly organized. The predictive dashboard layouts are easy to read, helping plant managers quickly evaluate daily asset health without needing deep technical data training.
Unified AI resource to manage models, endpoints and deploy applications. Model catalog is great and you have variety for choosing the best model that fits into each AI use case and control costs. Improving constantly the agents deployments and integration with OpenAI libraries when deploying a gateway.
The strongest point for me, and there are a host of things to explore, is the integration with Azure Databricks for feature store workflow. I have been able to build feature tables and Delta live tables in Databricks, and Foundry does relatively well with navigating them. In my own process, I had to move around from platform to platform a great deal, so I appreciate Foundry's ability to provide one unified place for data integrity and experimentation.
The initial configuration phase for linking non-standard, custom factory machinery to the platform can feel a bit overly complex and requires heavy manual scripting. While the core monitoring features are excellent, building highly specialized tabular reports outside their built-in templates can be somewhat rigid. The overall volume of continuous alerts during the baseline setup phase can be a bit loud, requiring a long process of fine-tuning filter rules to prevent fatigue.
Stability of the resource, Microsoft recently launched a new foundry with tons of bugs but with new features that legacy foundry was not offering. Since many features are very recent we are lacking the terraform provider implementation of some resources. Forces you to have App Insights (with high cost bill) to have a complete observability of the resource.
I'm not directly involved in these conversations, but it has been impressed upon me that cost management is imperative. We often have to consult with our tenant managers to ensure that spinning up resources in Databricks and Foundry is tracked with disciplined tagging or it can result in unexpected costs. It has certainly made me more diligent in documentation and the process of our internal workflow.