One post tagged with "Distributing"

Introduction​

🚀 Say Goodbye to Duplicate Tasks & Scaling Headaches!
In modern distributed systems, ensuring that scheduled tasks run once and only once across multiple instances is a critical challenge. Traditional cron jobs fall short in clustered environments, risking task duplication, resource contention, and operational chaos. Enter Spring Boot + ShedLock + Redis – but with a twist. Let’s explore how our new @DistributedScheduled annotation simplifies bulletproof scheduling!

🔑 Why Distributed Scheduling Matters​

• Avoid Duplicate Execution: Prevent multiple instances from running the same task simultaneously.
• Dynamic Scaling: Safely scale your microservices without manual cron job coordination.
• Fault Tolerance: Handle node failures gracefully with lock timeouts and retries.

🛠 Introducing the Ultimate Annotation: @DistributedScheduled​

We’ve supercharged Spring’s @Scheduled and ShedLock into one sleek, declarative annotation:

@DistributedScheduled(
    cron = "${order.sync.cron}", 
    name = "ORDER_SYNC_TASK",
    lockAtMostFor = "30m"
)
public void syncOrders() {
    // Your mission-critical task
}

Key Features:​

1. Unified Configuration: Combine cron expressions, lock names, and timeouts in one place.
2. Redis-Powered Locks: Leverage Redis for distributed lock coordination (no more JDBC hassle!).
3. Thread Pool Control: Dedicated defaultScheduler with configurable pool size.
4. Production-Ready Defaults: 15-minute max lock duration, 10-minute minimum ownership.

⚡ How It Works Under the Hood​

1. Redis Lock Provider:

   @Bean
   public LockProvider lockProvider(RedisConnectionFactory factory) {
       return new RedisLockProvider(factory, "shedlock"); // Namespaced keys
   }
   

   Why Redis? Blazing speed, atomic operations, and TTL support make it perfect for locks.

2. Smart Thread Pooling:

   @Bean(name = "defaultScheduler")
   public TaskScheduler defaultScheduler() {
       ThreadPoolTaskScheduler scheduler = new ThreadPoolTaskScheduler();
       scheduler.setPoolSize(5); // Scale based on workload
       scheduler.setThreadNamePrefix("scheduler-default-");
       return scheduler;
   }
   

   Avoid thread starvation with dedicated scheduling threads.

3. Annotation Magic:

   • Inherits @Scheduled’s cron flexibility.
   • Enforces ShedLock’s safety net with alias-driven overrides.

🏆 Why Choose This Over Vanilla ShedLock?​

🚨 Pro Tips for Production​

• Lock Duration: Set lockAtMostFor longer than your worst-case task runtime.
• Monitor Redis: Watch for lock contention with Redis CLI (KEYS shedlock:*).
• Dynamic Cron: Use cron = "${...}" to externalize schedules.

🌟 Real-World Use Case​

Problem: A payment reconciliation job ran twice daily, but duplicates caused $200K in over-refunds.
Solution:

@DistributedScheduled(
    cron = "0 0 2,14 * * *", 
    name = "PAYMENT_RECON",
    lockAtMostFor = "2h"
)
public void reconcilePayments() {
    // Safely process $1M/hour transactions
}

Result: Zero duplicates, effortless scaling to 10 service instances. 💸

🔮 Future-Proof Your Scheduling​

Our framework isn’t just code – it’s a philosophy:

1. Embrace Declarative Programming
2. Design for Idempotency
3. Assume Distributed Everything

🚀 Get Started Today!
Clone our GitHub or add the annotation to your Spring Boot app. Transform your cron jobs from liability to asset in 10 lines of code.

Because in distributed systems, timing isn’t just everything – it’s the only thing. 💫

💬 Let’s Discuss!
How are YOU handling distributed scheduling? Share your war stories on https://github.com/jingsewu/open-wes/issues