Spring AI boosts developer’s productivity by providing seamless integration with a variety of AI models. This post explores enriching the generic model with additional data coming from custom functions. This technique known as function calling allows to elegantly tap into a variety of external data sources. However, it comes with its own challenges and considerations.
Webhooks offer a robust integration with third-party services, facilitating complex and time-consuming processes asynchronously. Yet, they present a high risk of missed events due to high latency or performance issues. In this blog post, I’ll guide you through a reliable and scalable solution for handling webhooks. The toolkit consists of Spring Boot, WebFlux, Kotlin coroutines, and Apache Kafka. I’ll show you how to build a system that efficiently enqueues incoming requests into an internal queue for background processing. So let’s delve into it!
Kotlin coroutines are a powerful tool that propels efficiency in dealing with concurrent programming. They enable to treat asynchronous code as if it was synchronous, making it easier to manage and understand. In this blog post, I explore some of the core principles of coroutines and compare their performance against conventional blocking calls.