Microsoft Fabric - Multi-Tenant Architecture
Fabric Multi-Tenant Architecture (updated version - August 24) Organization often faces challenges in managing data for multiple tenants in a secure manner while keeping costs low. Traditional solutions may prove costly for scenarios with more than 100 tenants, especially with the common ISV scenario where the volume of trial and free tenants is much larger than the volume of paying tenants. The motivation for ISVs to use Fabric is that it brings together experiences such as Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Analytics, and Power BI onto a shared SaaS foundation. In this article, we will explore the Workspace per tenant-based architecture, which is a cost-effective solution for managing data for all tenants in Microsoft Fabric, including ETL and reporting.End-to-end TLS with AKS, Azure Front Door, Azure Private Link Service, and NGINX Ingress Controller
This article shows how Azure Front Door Premium can be set to use a Private Link Service to expose an AKS-hosted workload via NGINX Ingress Controller configured to use a private IP address on the internal load balancer.Implementing MLOps for Training Custom Models with Azure AI Document Intelligence
Addressing the challenges of effectively maintaining custom models in Azure AI Document Intelligence, this article explores adapting the concepts of MLOps into your delivery strategy. The goal is to provide guidance on how to ensure that custom document analysis models are not only accurate but remain effective for users throughout their lifecycle.Relational Data Synchronization between environments
There are business and/or technical cases where relational data should be duplicated to another environment. Since the demands of those business and/or technical cases are not the same, there are multiple technical solutions to achieve the goal. In this article, I will discuss of the various solutions according to difference business needs, with deep dive into one family of solutions – sync solutions that is based on the database engine (DB engine). The content is Azure oriented, but the same concepts are true for other clouds as well. I would expect that anyone that needs to sync relational data between environment can find here a good guideline.Graph API integration for SaaS developers
Many applications integrate with Microsoft Graph APIs to enrich their functionality with user data or provide additional features on top of Office 365 or Azure services. Some best practices can be leveraged to efficiently consume data from Microsoft Graph. This sample showcases how to use delta tokens to retrieve a change set, in combination with subscriptions/webhooks, to get notified when a delta token should be used to get the latest changes without pulling the whole set of data each time.Identifying drift in ML models: Best practices for generating consistent, reliable responses
Addressing the challenges of model drift is crucial for successful deployments of reliable, production-ready machine learning models. Explore insights into monitoring and mitigating model drift, with strategic recommendations to enhance the accuracy and longevity of machine learning models in real-world applications.
