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# Serverless-Native Java with Quarkus

Java's notorious cold starts no longer dictate your serverless architecture. Discover how Quarkus slashes boot times to four milliseconds, unlocking true scale-to-zero operations without vendor lock-in.

- **Speakers:** [Alex Soto](https://www.wearedevelopers.com/@alex-soto)
- **Event:** WeAreDevelopers LIVE
- **Published:** September 1, 2021
- **Duration:** 41:04
- **URL:** https://www.wearedevelopers.com/videos/243-serverless-native-java-with-quarkus

## Summary

The paradigm of serverless computing introduces a shift from long-lived microservices to event-driven architectures that scale computing resources precisely to match system demand. While "serverless doesn't mean that there is no servers," it liberates engineers from infrastructure management, load balancer configuration, and DNS routing. However, deploying serverless workloads typically forces reliance on proprietary cloud functions, establishing rigid vendor lock-in. Knative resolves this friction by extending standard Kubernetes primitives with container-based serverless capabilities. This approach empowers developers to implement load-based autoscaling, execute dynamic traffic splitting for canary releases, and establish scale-to-zero pod states across any cloud platform seamlessly.

Despite Knative's architectural advantages, the conventional Java virtual machine struggles natively in scale-to-zero operations due to massive memory footprints and multi-second execution delays. Making Java a practical match for ephemeral serverless workloads requires effectively eliminating these notorious cold starts. Quarkus tackles this constraint head-on by utilizing GraalVM to compile services into highly optimized native executables. By reducing boot times from four seconds to roughly four milliseconds and dramatically slashing default memory consumption, Quarkus actively overcomes Java's historical performance bottlenecks.

Combining Knative's dynamic orchestration with the native speed of Quarkus unlocks high-performance, cost-efficient eventing workflows. Developers can utilize tools like Kafka topic pipelines or basic HTTP requests to trigger lightweight containers that immediately span multiple instances during extreme traffic spikes before gracefully terminating to zero when idle. By uniting infrastructure agnosticism with optimized application runtimes, engineering teams can sidestep expensive idle-time billing ceilings without compromising on language familiarity, Kubernetes telemetry, or deployment flexibility.

**Keywords:** serverless architecture, microservices vs serverless, kubernetes workloads, knative deployments, scale-to-zero autoscaling, quarkus framework, graalvm native compilation, java cold start optimization, container-based functions, vendor lock-in prevention, blue-green deployments, canary release routing, memory footprint reduction, event-driven autoscaling, kafka event streaming

## Chapters

1. **Defining serverless computing capabilities and execution environments** (01:35) — Core principles of serverless architectures including eliminating server management and executing precise workload scaling.
1. **Comparing microservices and serverless architectural deployment models** (03:57) — How to choose between long-lived microservices and event-driven, short-lived serverless architectural approaches.
1. **Deploying serverless workloads on Kubernetes with Knative** (06:44) — Utilizing container-based Knative capabilities to provision and manage serverless infrastructure directly within Kubernetes.
1. **Overcoming Java cold starts using the Quarkus framework** (10:00) — How Quarkus provides millisecond boot times and a minimal memory footprint to make Java viable for serverless deployments.
1. **Creating and configuring a basic native Quarkus application** (12:21) — Generating a new Quarkus project with Spring Web extensions and compiling it to a native executable utilizing GraalVM.
1. **Deploying native Quarkus applications to a Knative cluster** (16:41) — Scaling Java pods automatically from zero based on traffic and comparing startup latency metrics against traditional Spring Boot configurations.
1. **Routing traffic natively between Knative service revisions** (25:02) — Configuring traffic splitting percentages between multiple application versions to enable blue-green processes and canary deployments.
1. **Auto-scaling Knative pods automatically based on traffic spikes** (28:12) — Defining concurrency targets to automatically spin up additional Kubernetes pods during high concurrent request loads.
1. **Processing IoT event streams with Knative and Kafka** (31:45) — Connecting Knative eventing systems directly to Kafka brokers to scale workloads automatically depending on incoming IoT message volumes.
1. **Debugging serverless container applications in Kubernetes production environments** (35:47) — Using specialized routing tools like Telepresence to intercept and inspect functional production Knative service traffic safely.
1. **Addressing pod scaling speeds and event failure handling** (37:20) — Optimizing container spin-up latency via images caching and managing automatic error retries smoothly between messaging brokers and scalable endpoints.

## Related Moments

- [Demonstrating event-driven auto-scaling with native Quarkus and Kafka](https://www.wearedevelopers.com/videos/1008-serverless-java-in-action-cloud-agnostic-design-patterns-and-tips) (from "Serverless Java in Action: Cloud Agnostic Design Patterns and Tips")
- [Utilizing Quarkus for Kubernetes native Java](https://www.wearedevelopers.com/videos/123-get-started-with-securing-your-cloud-native-java-microservices-applications) (from "Get started with securing your cloud-native Java microservices applications")
- [Optimizing container workloads with Quarkus and lightweight JVMs](https://www.wearedevelopers.com/videos/89-development-of-reactive-applications-with-quarkus) (from "Development of reactive applications with Quarkus")
- [Optimizing Java startup processes for fast serverless workloads](https://www.wearedevelopers.com/videos/1008-serverless-java-in-action-cloud-agnostic-design-patterns-and-tips) (from "Serverless Java in Action: Cloud Agnostic Design Patterns and Tips")
- [Technology stack for building robust microservices applications](https://www.wearedevelopers.com/videos/89-development-of-reactive-applications-with-quarkus) (from "Development of reactive applications with Quarkus")
- [Modifying classical application deployments with the Quarkus runtime](https://www.wearedevelopers.com/videos/102-2021-familiar-apis-on-kickass-runtimes-slideless) (from "2021: Familiar APIs on Kickass Runtimes #slideless")

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