Trigger.dev

Define and structure background jobs using TypeScript with type safety and IDE autocomplete support. Eliminates boilerplate code required by traditional queue systems by providing a declarative, code-first approach to job definition.

Automatically retry failed jobs with configurable exponential backoff strategies without manual implementation. Handles transient failures gracefully and reduces manual intervention for flaky operations.

Manually trigger jobs from the dashboard with custom payloads for testing and debugging purposes. Enables developers to test job logic without waiting for scheduled execution or external events.

Configure different job behaviors for development, staging, and production environments without code changes. Enables safe testing and gradual rollout of job changes.

Collect and analyze job execution metrics including duration, success rates, and failure patterns. Provides insights for optimization and capacity planning.

Trigger jobs via HTTP webhooks from external systems or custom applications. Enables integration with systems outside pre-built service integrations.

Visualize job execution status, performance metrics, and failure logs through a web-based dashboard without requiring external observability tools. Provides real-time insights into job queue health and individual job execution details.

Connect to popular services like Stripe, GitHub, and Slack through pre-built triggers that automatically execute jobs when specific events occur. Eliminates custom webhook parsing and event handling code.

Schedule jobs to run at specific times or intervals using standard cron syntax. Provides an alternative to managing separate cron services or scheduled tasks.

Define dependencies between jobs and orchestrate multi-step workflows where jobs trigger other jobs based on conditions or completion. Enables complex automation sequences without external workflow engines.

Capture failed jobs after retry exhaustion and route them to dead letter queues for manual inspection and recovery. Prevents data loss and enables debugging of persistent failures.

Control how many jobs execute simultaneously and limit execution rates to prevent overwhelming external services or databases. Prevents resource exhaustion and API rate limit violations.

Define and validate job payload schemas to ensure type safety and handle schema evolution as job definitions change. Prevents runtime errors from malformed job data.

Maintain complete execution history for all jobs including timestamps, payloads, results, and error messages. Enables debugging, compliance auditing, and performance analysis.