Understanding schedule types and triggers
Scheduling is a crucial part of managing your data workflows. Paradime offers flexible options to ensure your jobs run exactly when you need them and in the most efficient manner.
Estimated completion time: 10 minutes
Prerequisites
Access to the Bolt application in Paradime
A Production Connection to your data warehouse (AKA Schedule Connection)
What You'll Learn
In this guide, you'll learn about:
Different types of Bolt schedules (Standard, Deferred, and Turbo CI) and when to use them
Various schedule triggers (Scheduled run, On Run Completion, On Merge, Bolt API) and when to use them)
Schedule statuses and their meanings
1. Schedule Types
Paradime supports three main schedule types, each designed for specific use cases:
| Type | Description | Best for |
|---|---|---|
Standard | Runs your dbt™ job directly in the production environment | Regular production runs, daily or hourly updates |
Deferred | Runs your job in a separate environment before merging changes to production | Testing changes before deploying to production, CI/CD workflows |
Turbo CI | Performs rapid, incremental runs of only changed models | Fast feedback on model changes, efficient CI processes |
For more details on setting up each type, refer to our advanced scheduling documentation.
2. Schedule Triggers
Paradime supports four main schedule triggers:
| Schedule Trigger | What it does | How it works | Best for |
|---|---|---|---|
Scheduled Run | Runs your job at specific times and frequencies | Uses cron syntax to set the schedule | Regular, time-based job execution (e.g., daily reports, weekly updates) |
On Run Completion | Triggers your job after another specified job finishes | You select a "parent" job, and this job will start once the parent completes | Creating dependencies between jobs (e.g., running a summary job after individual data updates) |
On Merge | Runs your job when a pull request is merged into a specified branch | Connects to your Git repository and triggers based on merge events. See Defer to Production documentation for details. | Continuous Deployment workflows, ensuring your data pipeline updates with your code changes |
Bolt API | Allows you to trigger jobs programmatically from your existing data pipelines | Provides API endpoints to start, stop, or check job status See Bolt API documentation for details. | Integrating Paradime jobs with external systems or custom workflows |
3. Schedule Statuses
As you manage multiple Bolt schedules, you'll encounter the following statuses:
| Status | Description |
|---|---|
✅ Success | The schedule has completed successfully |
🚫 Canceled | The schedule was manually canceled or stopped before completion |
❌ Error | The schedule encountered an error during execution (AKA the scheduled run "failed") |
⏸️ Paused | The schedule has been temporarily paused |
🕐 No runs | The schedule has yet to execute and/or it is not configured to execute. |
Summary
You've learned about the different types of Bolt schedules, various trigger methods, and schedule statuses. This knowledge will help you choose the right schedule type and trigger for your specific use cases, and understand the status of your running schedules.
Next, we'll explore how to view run history and analytics for your Bolt schedules, which will help you monitor and optimize your dbt™ workflows.
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