Alex Soto

Serverless-Native Java with Quarkus

Java is now a first-class citizen for serverless. See how Quarkus delivers millisecond startup times and a tiny memory footprint, finally solving the cold start problem.

Serverless-Native Java with Quarkus
#1about 2 minutes

Understanding the core principles of serverless computing

Serverless computing abstracts away server management and scales applications based on exact demand, including scaling to zero to reduce costs.

#2about 3 minutes

Choosing between microservices and serverless architectures

Compare microservices for long-lived, developer-controlled processes against serverless for short-lived, cloud-managed, event-driven functions.

#3about 3 minutes

Implementing serverless workloads on Kubernetes with Knative

Knative enables serverless, container-based workloads on Kubernetes by using standard primitives to manage scaling, revisions, and traffic.

#4about 2 minutes

Solving Java's serverless challenges with Quarkus

Quarkus overcomes traditional Java performance issues in serverless environments by offering sub-second startup times and a minimal memory footprint.

#5about 4 minutes

Generating a new Quarkus project for serverless development

Use the code.quarkus.io starter to quickly generate a new project with dependencies for JAX-RS, Spring Web, or AWS Lambda.

#6about 5 minutes

Deploying a Quarkus app and demonstrating scale to zero

A live demo shows a native-compiled Quarkus application starting in milliseconds and automatically scaling down to zero pods after a period of inactivity.

#7about 3 minutes

Comparing Quarkus and Spring Boot startup performance

A side-by-side comparison demonstrates that a native Quarkus application starts in milliseconds while a similar Spring Boot application takes several seconds.

#8about 3 minutes

Implementing blue-green deployments with Knative revisions

Knative's revision system allows for safe deployment strategies like blue-green by managing traffic splitting between different versions of a service.

#9about 4 minutes

Auto-scaling Knative services based on traffic load

Configure a Knative service to automatically scale up the number of pods based on a target number of concurrent requests.

#10about 3 minutes

Using Knative eventing for asynchronous workloads with Kafka

Knative Eventing can consume messages from a Kafka topic and automatically trigger and scale services to process events asynchronously.

#11about 5 minutes

Debugging serverless applications in a production environment

Use tools like Telepresence or adjust the scale-to-zero timeout to connect a local debugger to a running service in a Kubernetes cluster.

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Andrew Comp

Andrew Comp
Berlin, Germany

Intermediate
Java
JavaScript

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