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.
Back to a teach-myself-something type of project, with setting up K8s Cluster on Raspberry Pi devices. I had a couple of older Raspberry Pi 3s and a recently purchased Pi 4 available for this. My old Pi3 devices had Docker Swarm (yes that one) from a couple of years back. This time around I want to get k8s on the 3 Pi devices.
The steps are fairly simple but it can be a bit of work. You should find blogs out there with decent enough directions. So here goes me adding to that library of blogs to make it easier for the next person trying to set this up.
This is an upgrade from my previous similar blog installing Docker Swarm on a two node Pi-3 cluster https://220.127.116.11/running-docker-swarm-raspberry-pi-3/
I am going to point you to a few resources to help you standup a hello world serverless app using AWS Lambda using AWS Serverless Application Model (SAM).
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.