OpenAI provides us the ability to invoke its features via RESTful APIs. This blog shows how to invoke the API using Spring Boot. There is nothing special here and no OpenAI Java libraries that I use. One can do the same in standard Java (non-spring) or even in more concise code with Nodejs. But here goes a sample with Spring Boot.
A simple Spring Boot sample to publish a message to a Redis queue, with a message subscriber that consumes the message Spring Data. See README in Github for how to set up a local Redis and run the code.
In the age of Serverless & Container architectures, there is once again chatter about Java being too fat (and dying). While I can understand the “too fat” observation, I will not put my money on the “java is dying/dead” chatter. That obituary has been written multiple times and the language lives on. It is true that Java was not born in the Container/Cloud era. Yes, it was born in a different age and time, but the language and framework ecosystem has evolved. In the Microservices cloud-native app world where horizontal scaling and fast startup times are expected, Java may (at times depending on the architecture) not be the fastest horse in town.
Capturing metrics from your system is critical to understanding its internal behavior and to tune its performance. Without this you are operating in the blind. In this post we will go through how you can gather metrics from a Spring Boot application using Prometheus, Grafana and Micrometer.