Implementing Distributed Locks with Redis and Redisson: Abstraction, Auto-Release, and Fault Tolerance

Distributed locks have many implementations such as Redis, Zookeeper, and databases; Redis is commonly used because it is already employed for caching.

Using Redisson, a lock can be obtained and used with simple code:

RLock lock = redisson.getLock("anyLock");
lock.lock();
run();
lock.unlock();

To improve extensibility, an abstract DistributedLock interface is introduced, allowing different implementations (e.g., Redis, database) to be swapped without changing service code.

Automatic release is desirable; instead of manually calling unlock(), the wrapper can accept a Supplier or Runnable and handle unlocking internally.

/**
 * Lock execution
 * @param key lock key
 * @param waitTime wait time (ms)
 * @param leaseTime lease time (ms)
 * @param success logic on success
 * @param fail logic on failure
 * @return result
 */
<T> T lock(String key, int waitTime, int leaseTime, Supplier<T> success, Supplier<T> fail);

Example usage:

String result = distributedLock.lock("1001", 1000, () -> {
    System.out.println("进来了。。。。");
    try {
        Thread.sleep(1000);
    } catch (InterruptedException e) {
        e.printStackTrace();
    }
    return "success";
}, () -> {
    System.out.println("加锁失败。。。。");
    return "fail";
});

When Redis becomes unavailable, the system can fall back to a database lock to maintain business continuity, and if all locks fail, the operation should fail to avoid unsafe concurrency.

Monitoring of lock‑related metrics (acquire time, release time, duration, concurrency, failures) across Redis, databases, and Zookeeper is essential for timely alerts and fault handling.