A practical guide to high-performance serverless with GraalVM and Spring

"The Java Virtual Machine (JVM) is a marvel of engineering, optimized for long-running, high-performance applications. Its just-in-time (JIT) compiler analyzes code as it runs, making sophisticated optimizations to deliver incredible peak performance. But this strength becomes a weakness in a serverless model. When a Lambda function starts cold, the JVM must go through its entire initialization process: loading classes, verifying bytecode and beginning the slow warm-up of the JIT compiler. This can take several seconds - an eternity for a latency-sensitive workflow."

"AWS has attempted to address this with Lambda SnapStart, which works by caching a snapshot of an initialized microVM. It's a clever infrastructure-level mitigation, but for many enterprise needs, it comes with limitations and subtle risks related to state uniqueness and stale data. I realized that I needed a solution that didn't just mitigate the cold start but eliminated it at the application level."

Java's mature ecosystem excels for enterprise applications but faces cold-start latency in serverless due to JVM initialization and JIT warm-up overhead. Lambda cold starts require class loading, bytecode verification and JIT warm-up, causing several-second delays that harm latency-sensitive workflows. AWS Lambda SnapStart reduces cold starts by caching initialized microVM snapshots but introduces limitations and risks around state uniqueness and stale data. Eliminating cold starts at the application level requires ahead-of-time compilation and architectural changes. GraalVM Native Image provides an AOT transformation that fundamentally changes the deployed artifact, enabling faster startup and predictable latency when combined with modern tooling and patterns.

Read at InfoWorld