How do I set up ShedLock with Spring Boot and Redis?

Add the shedlock-spring and shedlock-provider-redis-spring dependencies, configure a RedisLockProvider bean with your RedisConnectionFactory, and annotate scheduled methods with @SchedulerLock. The README provides code snippets for exact configuration steps.

ShedLock vs db-scheduler: which is better for job scheduling?

ShedLock is best for simple at-most-once execution in existing scheduled tasks, while db-scheduler is a full distributed scheduler with job persistence, retries, and dependencies. Choose ShedLock if you only need locking; otherwise, opt for a scheduler like db-scheduler or JobRunr.

What happens if a task runs longer than lockAtMostFor in ShedLock?

The lock expires, and another instance might acquire it, leading to duplicate execution. The README warns to set lockAtMostFor significantly longer than the maximum execution time and treats it as a safety net for node failures.

Can ShedLock handle clock skew in Kubernetes clusters?

Yes, but you must mitigate it by using lock providers with database time (e.g., JdbcTemplate with usingDbTime()) to rely on the DB server's clock, and set lockAtLeastFor to account for minor differences, as recommended in the README.

Is ShedLock suitable for very short-running tasks?

Yes, but use lockAtLeastFor to prevent rapid successive executions due to clock differences or short durations. The README's troubleshooting section suggests this for tasks that finish quickly.

How do I test ShedLock without an external database?

Use the InMemoryLockProvider in tests by adding shedlock-provider-inmemory as a test dependency and configuring it as a bean. The README shows an example with scope set to test for isolation.

Does ShedLock support reactive programming with Spring WebFlux?

Yes, via reactive lock providers like ReactiveRedisLockProvider or R2DBC, but the README notes that R2DBC support is experimental and limited, so use with caution in production.

shedlock — Distributed Lock for Scheduled Tasks

What is shedlock?

ShedLock is a Java library that provides distributed locking for scheduled tasks, ensuring they execute at most once across multiple nodes in a cluster. It solves the problem of duplicate task execution in horizontally scaled applications by using an external store (like a database or Redis) to coordinate locks. Tasks are annotated with `@SchedulerLock`, and if a lock is held by one node, other nodes skip execution rather than waiting.

Target Audience

Java developers building Spring Boot, Micronaut, or Quarkus applications with scheduled tasks (e.g., cron jobs) that need to run reliably in clustered or cloud environments. It's especially useful for teams deploying microservices where multiple instances might trigger the same scheduled logic.

Value Proposition

Developers choose ShedLock for its simplicity, robust integration with popular frameworks, and support for numerous lock providers. Unlike full distributed schedulers, it focuses solely on preventing concurrent execution, making it lightweight and easy to adopt without overhauling existing scheduling setups.

Distributed lock for your scheduled tasks

Use Cases

Best For

Ensuring cron jobs run once per cluster in Kubernetes deployments
Preventing duplicate processing in Spring Boot scheduled tasks
Coordinating batch jobs across multiple application instances
Safeguarding idempotent but non-parallelizable tasks (e.g., data aggregation)
Adding distributed locking to legacy scheduled tasks with minimal code changes
Building fault-tolerant scheduled tasks with auto-expiring locks

Not Ideal For

Teams needing a full-featured distributed scheduler with job dependencies, retries, or dynamic scheduling
Applications where tasks must block and wait for locks rather than skip execution
Environments with significant clock drift between nodes, as time-based locks assume synchronization
Projects requiring high-reliability locks with cache-based providers (e.g., Memcached warns of premature eviction)

Pros & Cons

Pros

Extensive Lock Provider Support

Supports over 30 backends including JDBC, Redis, Mongo, and cloud services, making it adaptable to diverse infrastructures without vendor lock-in.

Framework-Agnostic Integration

Works seamlessly with Spring, Micronaut, CDI (Quarkus), and standalone Java, minimizing framework dependencies and easing adoption.

At-Most-Once Execution

Ensures scheduled tasks run at most once per cluster using distributed locks, preventing duplicate processing in scaled deployments.

Simple Annotation-Based Setup

Just annotate methods with @SchedulerLock and configure a lock provider, requiring minimal code changes to existing scheduled tasks.

Cons

Not a Full Scheduler

Lacks job orchestration features like retries, dependencies, or dynamic scheduling; the README explicitly states it's just a lock, not a scheduler.

Time-Based Lock Risks

Duplicate execution can occur if tasks exceed lockAtMostFor or clocks are unsynchronized, as noted in the caveats section, requiring careful configuration.

External Storage Overhead

Requires setting up and maintaining an external store (e.g., database tables for JDBC), adding operational complexity compared to in-memory solutions.

Provider-Specific Limitations

Some lock providers have reliability issues; for example, the README warns that Memcached may release locks prematurely, and R2DBC support is experimental.

Frequently Asked Questions

What is shedlock?

Target Audience

Value Proposition

Use Cases

Best For

Ensuring cron jobs run once per cluster in Kubernetes deployments
Preventing duplicate processing in Spring Boot scheduled tasks
Coordinating batch jobs across multiple application instances
Safeguarding idempotent but non-parallelizable tasks (e.g., data aggregation)
Adding distributed locking to legacy scheduled tasks with minimal code changes
Building fault-tolerant scheduled tasks with auto-expiring locks

Not Ideal For

Teams needing a full-featured distributed scheduler with job dependencies, retries, or dynamic scheduling
Applications where tasks must block and wait for locks rather than skip execution
Environments with significant clock drift between nodes, as time-based locks assume synchronization
Projects requiring high-reliability locks with cache-based providers (e.g., Memcached warns of premature eviction)

Pros & Cons

Pros

Extensive Lock Provider Support

Supports over 30 backends including JDBC, Redis, Mongo, and cloud services, making it adaptable to diverse infrastructures without vendor lock-in.

Framework-Agnostic Integration

Works seamlessly with Spring, Micronaut, CDI (Quarkus), and standalone Java, minimizing framework dependencies and easing adoption.

At-Most-Once Execution

Ensures scheduled tasks run at most once per cluster using distributed locks, preventing duplicate processing in scaled deployments.

Simple Annotation-Based Setup

Just annotate methods with @SchedulerLock and configure a lock provider, requiring minimal code changes to existing scheduled tasks.

Cons

Not a Full Scheduler

Lacks job orchestration features like retries, dependencies, or dynamic scheduling; the README explicitly states it's just a lock, not a scheduler.

Time-Based Lock Risks

Duplicate execution can occur if tasks exceed lockAtMostFor or clocks are unsynchronized, as noted in the caveats section, requiring careful configuration.

External Storage Overhead

Requires setting up and maintaining an external store (e.g., database tables for JDBC), adding operational complexity compared to in-memory solutions.

Provider-Specific Limitations

Some lock providers have reliability issues; for example, the README warns that Memcached may release locks prematurely, and R2DBC support is experimental.

Frequently Asked Questions

shedlock

What is shedlock?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

shedlock

What is shedlock?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?