This tutorial explains how to optimize Java performance to run Serverless functions on Kubernetes using Quarkus. Achieve faster startup and a smaller memory footprint to run serverless functions on Kubernetes.
Achieve faster startup and a smaller memory footprint to run serverless functions on Kubernetes.
A faster startup and smaller memory footprint always matter in Kubernetes due to the expense of running thousands of application pods and the cost savings of doing it with fewer worker nodes and other resources. Memory is more important than throughput on containerized microservices on Kubernetes because:
This significantly impacts serverless function development and the Java deployment model. This is because many enterprise developers chose alternatives such as Go, Python, and Nodejs to overcome the performance bottleneck—until now, thanks to Quarkus, a new Kubernetes-native Java stack. This article explains how to optimize Java performance to run serverless functions on Kubernetes using Quarkus.
Our original Kubernetes tool list was so popular that we've curated another great list of tools to help you improve your functionality with the platform.
What is OpenJDK? OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE).
In this article, we will talk about the most important new feature introduced with Java 10, officially called local variable type inference. An extremely important function in java. You will regret skipping this article.
Essentially, it cost me nothing. This is possible because I chose a serverless implementation approach for this. This is running on AWS Lambda, using their serverless blog search Serverless Search for My Blog With Java, Quarkus & AWS Lambda. How you can implement serverless applications using Quarkus, Java.
Getting started with Java Serverless Functions using Quarkus and AWS Lambda. The serverless journey started with functions - small snippets of code running on-demand and a short period in Figure 1. AWS Lambda in the “1.0” phase made this paradigm very popular.