Project CRaC: Revolutionizing Java Application Startup Times

Master Spring Ter
3 min readDec 22, 2024

Project CRaC (Coordinated Restore at Checkpoint) is shaking up the Java world — especially for Spring Boot apps. It can drastically cut startup times by taking a snapshot (“checkpoint”) of a running app and restoring it nearly instantly.

What Is CRaC?

CRaC isn’t yet mainstream in OpenJDK; you usually need an incubator or early-access JDK build. The idea is simple:

  • You start your Java app once.
  • You checkpoint it, saving its running state.
  • Next time, you restore that snapshot instead of starting from scratch.

The Startup-Time Problem

Traditional Java apps (like standard Spring Boot) often take a few seconds to start, due to:

  • Class loading
  • Bean initialization
  • Database connection setup

Those seconds add up in microservices or serverless settings.

Using CRaC with Spring Boot

Simple Integration

import org.crac.*;

@SpringBootApplication
public class CraCEnabledApplication implements Resource {
public static void main(String[] args) {
SpringApplication.run(CraCEnabledApplication.class, args);
// Register this class as a CRaC resource
Core.getGlobalContext().register(new CraCEnabledApplication());
}
@Override
public void beforeCheckpoint(Context<? extends Resource> context) {
System.out.println("Preparing for checkpoint...");
}
@Override
public void afterRestore(Context<? extends Resource> context) {
System.out.println("Restored from checkpoint!");
}
}

Handling Stateful Components

Some libraries may need explicit hooks. For example, close database connections before the checkpoint and reopen them after restore:

@Component
public class DatabaseConnectionManager implements Resource {
private final DataSource dataSource;

public DatabaseConnectionManager(DataSource dataSource) {
this.dataSource = dataSource;
Core.getGlobalContext().register(this);
}
@Override
public void beforeCheckpoint(Context<? extends Resource> context) throws Exception {
if (dataSource instanceof HikariDataSource) {
((HikariDataSource) dataSource).close();
}
}
@Override
public void afterRestore(Context<? extends Resource> context) throws Exception {
if (dataSource instanceof HikariDataSource) {
((HikariDataSource) dataSource).getConnection(); // triggers pool init
}
}
}

Best Practices

  1. Resource Management
    Handle anything that can’t be paused safely, like sockets or file handles.
  2. State Management
    Clear out or reinit any transient/sensitive data before checkpoint and after restore.

Performance Gains

In tests, you might see:

  • Traditional startup: 5–15 seconds
  • CRaC restore: 0.1–0.5 seconds

Big difference if you’re scaling frequently.

Production Tips

Docker Integration

You need a CRaC-enabled JDK in your Docker image — just apt-get install openjdk-21-jdk usually won’t include it by default. You might do something like:

FROM my-custom-crac-jdk:latest
COPY target/*.jar app.jar
COPY checkpoint.sh /checkpoint.sh
RUN chmod +x /checkpoint.sh
ENTRYPOINT ["/checkpoint.sh"]

Kubernetes

Mount a persistent volume for storing checkpoints:

apiVersion: apps/v1
kind: Deployment
metadata:
name: crac-enabled-app
spec:
template:
spec:
containers:
- name: app
image: crac-enabled-app:latest
volumeMounts:
- name: checkpoint-volume
mountPath: /checkpoint
volumes:
- name: checkpoint-volume
persistentVolumeClaim:
claimName: checkpoint-pvc

Monitoring CRaC

Track checkpoint/restore events. You could integrate with Micrometer, Prometheus, or whichever monitoring system you prefer:

@Configuration
public class CraCMetricsConfig {

@Bean
public MeterRegistry meterRegistry() {
return new SimpleMeterRegistry();
}

@Bean
public CraCMetrics cracMetrics(MeterRegistry registry) {
return new CraCMetrics(registry);
}
}

class CraCMetrics {
private final Timer checkpointTimer;
private final Timer restoreTimer;
public CraCMetrics(MeterRegistry registry) {
this.checkpointTimer = registry.timer("crac.checkpoint");
this.restoreTimer = registry.timer("crac.restore");
}
}

Conclusion & Future

CRaC is a big leap forward for Java performance. Near-instant startup, lower resource usage, and improved resiliency can be huge in cloud environments. We’ll likely see better tooling, more library compatibility, and broader adoption as CRaC continues to evolve.

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Master Spring Ter
Master Spring Ter

Written by Master Spring Ter

https://chatgpt.com/g/g-dHq8Bxx92-master-spring-ter Specialized ChatGPT expert in Spring Boot, offering insights and guidance for developers.

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