AI applications built on Azure Cosmos DB depend on embeddings for grounded results. Keeping them in sync with your data is the hard part: it means building and operating a separate data pipeline to track changes, call an embedding model, and write the results back to Azure Cosmos DB. In practice, that pipeline also has to handle failures and retrie...

Today we are open-sourcing OmniVec, a platform for building and operating the embedding pipelines that keep the vector representation of your operational data in sync as it changes. You register data sources, embedding model(s), vector stores (destination), and OmniVec does the rest: initial backfill, change tracking, model invocation to geenrate, ...

The Azure Cosmos DB vNext emulator is generally available today. It ships as a Docker image that runs on Linux, macOS, and Windows, on both x64 and ARM64 architectures, giving you a local Cosmos DB instance you can develop and test against. Use it for inner-loop development on your laptop, in CI integration tests, and anywhere else you’d rather not...

A hands‑on walkthrough of building MCP servers that can plug AI applications into Azure Cosmos DB The Model Context Protocol (MCP) has established itself as the ubiquitous standard for connecting AI applications to external systems. Since its release, there have been implementations across various programming languages and frameworks, enab...

The Azure Cosmos DB Linux-based vNext emulator (preview) is a local version of the Azure Cosmos DB service that runs as a Docker container on Linux, macOS, and Windows. It provides a cost-effective way to develop and test applications locally without requiring an Azure subscription or network connectivity. The latest release brings improvements ...

Local large language models (LLMs) provide significant advantages for developers and organizations. Key benefits include enhanced data privacy, as sensitive information remains entirely within your own infrastructure, and offline functionality, enabling uninterrupted work even without internet access. While cloud-based LLM services are convenient, ...

Multi-tenant applications face a fundamental challenge: how to efficiently store and query data for tenants of vastly different sizes? Consider the typical scenario where your platform serves both enterprise clients with hundreds of thousands of users, as well as small businesses with just a handful. With traditional database partitioning strategie...

Integration testing has always presented a fundamental challenge: how do you test your application against real dependencies without the complexity of managing external services? Traditional approaches often involve either mocking dependencies (which can miss integration issues) or maintaining separate test environments (which can be expensive and ...

When building applications that interact with databases, developers frequently encounter scenarios where default SDK configurations don't align with their specific operational requirements. They need to customize SDK behavior to address real-world challenges like network instability, performance bottlenecks, debugging complexity, monitoring require...

The Go programming language is a great fit for building serverless applications. Go applications can be easily compiled to a single, statically linked binary, making deployment simple and reducing external dependencies. They start up quickly, which is ideal for serverless environments where functions are frequently invoked from a cold start. Go app...