A common challenge in building GenAI applications today is the slow performance of most LLMs (except ChatGPT 4-o and Groq). To minimize delays and enhance user experience, streaming the LLM response is a must. As such, we see a common pattern emerge in AppSync:
This workaround is necessary because AppSync could only invoke Lambda functions synchronously. To support response streaming, the first function has to hand off calling the LLM to something else. AppSync now supports async Lambda invocations.On May 30th, AppSync announced [1] support for invoking Lambda resolvers asynchronously. This works for both VTL and JavaScript resolvers. Setting the new invocationType attribute to Event will tell AppSync to invoke the Lambda resolver asynchronously. Here's how the VTL mapping template would look: And here's the JavaScript resolver: The response from an async invocation will always be null. The new architectureWith this change, we no longer need the background function.
This is a simple yet significant quality-of-life improvement from the AppSync team. It's not just for GenAI applications. The same pattern can be applied to any long-running task requiring more than AppSync's 30s limit. Links[1] AWS AppSync now supports long running events with asynchronous Lambda function invocations |
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I recently shared six event versioning strategies for event-driven architectures [1]. In response to this, Marty Pitt reached out and showed me how Orbital [2] and Taxi [3] use semantic tags to eliminate schema coupling in event-driven architectures and simplify the schema management. It's a novel way to manage schema evolution, and I want to share what I learnt with you. Problems with Schema Coupling In an event-driven architecture, event consumers are typically coupled to the schema of the...
Last week, we looked at 6 ways to version event schemas [1] and found the best solution is to avoid breaking changes and minimise the need for versioning. But how exactly do you do that? How can you prevent accidental breaking changes from creeping in? You can detect and stop breaking changes: At runtime, when the events are ingested; During development, when schema changes are made; Or a combination of both! Here are three approaches you should consider. 1. Consumer-Driven Contracts In...
Synchronous API integrations create temporal coupling [1] between two services based on their respective availability. This is a tighter form of coupling and often necessitates techniques such as retries, exponential delay and fallbacks to compensate. Event-driven architectures, on the other hand, encourage loose coupling. But we are still bound by lessor forms of coupling such as schema coupling. And here lies a question that many students and clients have asked me: “How do I version my...