Log streams like Axiom and Datadog can be used to provide powerful querying and alerting on logs and errors from your Convex functions, helping with debugging issues when they come up and providing early insights to detect smaller issues before they become bigger. This article covers how to do the several common things with either Axiom or Datadog hooked up as a Convex log stream including filtering to a request, logging structured metadata, and visualizing usage.

Implementing application rate limiting when you have fast access to a database with strong ACID guarantees. Token bucket and fixed window, with fairness, burst accommodation and fire-and-forget support.

Online migrations in Convex using mutations. Including a helper to track migration state!

Implementing "work stealing" - a workload distribution strategy - using Convex's reactive database.

This year vector databases have sprung up like mushrooms to enable applications to retrieve context based on semantic search. A large portion of these applications have used the retrieved context to augment the ability of large language models (LLMs) in a pattern known as RAG. On November 7th OpenAI released its Assistants API, enabling the implementation of AI chat interfaces with context retrieval without needing a separate message store or vector database. Does this new API make vector databases obsolete?

On November 7th OpenAI released its Assistants API, enabling chat bot with context retrieval implementations without needing a messages or vector database. In this post, we’ll cover how to leverage this API to build a fully functioning AI chat interface.