Azure Cosmos DB Blog

Most “AI agent” demos forget everything the moment the process exits. That’s fine for a toy project, but useless for anything real. An agent that helps you write, triage, or support needs two things a language model alone can’t give it: durable state and the ability to recall the right context by meaning. This post The post Building on Vercel’s eve + Azure Cosmos DB: An Agent That Remembers appeared first on Azure Cosmos DB Blog.

Design patterns are where good data modeling lives or dies. In a NoSQL database like Azure Cosmos DB, the difference between a schema that scales to millions of operations per second and one that fights you at every turn usually comes down to a handful of well‑understood patterns: how you partition, how you version, how The post See our new Azure Cosmos DB Design Patterns appeared first on Azure Cosmos DB Blog.

Once you create a container, its partition key is fixed at creation, and you can’t change it in place. However, if your original key starts causing problems like cross-partition queries or hot partitions, you need to consider your options for changing it. This post explains the mechanics of changing a partition key, and the tradeoffs between The post Need a different partition key in Azure Cosmos DB? Pick the right approach appeared first on Azure Cosmos DB Blog.

The wait is over. Spring AI 2.0 is generally available, and Azure Cosmos DB is right there with it. With this release, Spring AI graduates into a mature, production-ready framework for building AI applications in Java, and Azure Cosmos DB ships dedicated, vendor-maintained integrations that plug straight into the Spring AI ecosystem. The Spring AI 2.0 GA announcement The post Spring AI 2.0 is GA: Vector Search, Memory, and Agents on Azure Cosmos DB appeared first on Azure Cosmos DB Blog.

In the previous post in the series, we covered the security decisions you make on day one. In this part, we will talk about how to give your app access to Cosmos DB data, using roles and a managed identity instead of keys. The situation You’ve built your app. It works locally. Now you’re ready The post Which Azure Cosmos DB Role Does My App Need? appeared first on Azure Cosmos DB Blog.

Deep Agents is an agent harness built on LangGraph, for agents that need to work through a task over many steps instead of a single LLM call. The agent runs tools, looks at the results, and uses that to pick the next one, keeping a todo list as it goes. On top of that loop The post How to Use Deep Agents with Azure Cosmos DB – Plan, act, and verify against operational data appeared first on Azure Cosmos DB Blog.

Azure Backup for Azure Cosmos DB Public Preview Adds Immutable Backups and Long-Term Retention Picture the first few hours after a serious data incident. A production application is down. Security teams are still trying to understand what happened. Application owners need to know which recovery points are usable, which ones are protected from tampering, and The post Azure Backup for Azure Cosmos DB Public Preview Adds Immutable Backups and Long-Term Retention appeared first on Azure Cosmos DB Blog.

Today, we’re excited to announce the general availability of the Azure Cosmos DB built-in connector for Azure Logic Apps Standard. This connector gives you a native, high-performance way to integrate Azure Cosmos DB into your Standard logic app workflows, with better throughput, lower latency, and richer functionality than the managed connector. That includes real-time change The post Announcing General Availability of the Azure Cosmos DB Built-in Connector for Logic Apps Standard appeared first on Azure Cosmos DB Blog.

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 The post Announcing the Public Preview of Integrated Embeddings in Azure Cosmos DB: Build AI Apps With Embeddings That Stay in Sync appeared first on Azure Cosmos DB Blog.

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, and writing them back to The post Introducing OmniVec: An Open-Source Embedding Platform for AI Apps on Azure appeared first on Azure Cosmos DB Blog.