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.
Once upon a time there lived a monolith application named Mono (creative ah!).
Most serious applications (and distributed microservices style architectures) will require to provide a log aggregation & analysis feature to its dev & operations teams. Reviewing log entires from 10s or 100s of server instances is not something to take lightly. Whether you choose to use a commercial product or an open source offering – that does not matter; just make sure you have one available.
Recently I have been deploying applications using AWS Beanstalk. You can definitely configure CloudWatch Logs to send log streams over to AWS ElasticSearch service. Log messages can be routed to a Lambda function which would break the log messages into individual attributes suitable for indexing. I wanted to try a slightly different route where I depend less on CloudWatch Logs and more on open source tools. Enter filebeat on Beanstalk.
Notes on getting Docker Swarm cluster running on two Raspberry Pi 3 devices. We will then deploy a simple nodejs app container on the new cluster.
Updated one of my previous Spring Boot sample service to run within a Docker container – https://github.com/thomasma/quote-service-docker. You can run it locally w/o Docker as a regular Spring Boot app and next run it inside a Docker container. Make sure that you have Docker setup correctly and tested prior to running this app.
It is hard not to be affected by the constant chatter on Microservices Architecture and Container technology. Both are leading the discussions nowadays and they combine to provide new ways to Architect distributed systems and provide agility in delivering business value. While they do bring in big benefits when implemented successfully, the path to success for most enterprises (other than startups/product/tech firms) is going to be difficult and having a level of measured caution would be good.
To discuss Serverless Architecture we need to understand how we got here. From using physical machines we moved to virtual machines (somewhere in between a few brave folks also used linux/solaris containers). The current trend is container technologies such as Docker or CoreOS RKT which allow even more efficient use of resources. Regardless of which you use, we are often required to plan our application infrastructure needs upfront and permanently keep the “servers” running.
In the tech world one cannot stay a day away from hearing the words API or Microservices. For those who work in startups or tech firms (google type) these are well understood. But once you walk into large non-tech firms, these words are not as well understood.