Viewing Run History and Analytics
Last updated
Last updated
Bolt provides comprehensive tools for monitoring and analyzing your dbt™ schedules. This guide will walk you through viewing run logs, understanding the Bolt Schedules list, and exploring detailed analytics for your schedules.
Estimated completion time: 15 minutes
Access to the Bolt application in Paradime
At least one configured Bolt schedule
In this guide, you'll learn how to:
The Bolt home screen displays a summarized analysis of all your configured schedules, both UI-based and YAML-based. Here's what you can see at a glance:
The Bolt Schedule Detail View provides in-depth insights into individual dbt™ schedules, including configuration, run history, logs, and artifacts.
How to to access:
Schedules Overview: Navigate to the main page displaying all your configured schedules.
Schedule Selection: Click on a specific schedule name to view its detailed information and run history.
In the Run History section, you can view all executions of a specific scheduled run:
Every time a dbt™ command executes in a Bolt schedule, dbt Core™ generates a set of artifacts like manifest.json, catalog.json, run_results.json, and sources.json. These tools help analyze, troubleshoot, and optimize your Bolt schedules.
How to access:
Click on a specific run from a Bolt schedule's Run History
Scroll down to Logs and Artifacts section
Let's explore the key components:
By clicking on a specific command executed in your bolt schedule (e.g., dbt run) you'll have access to various run logs:
When your Bolt Schedule contains the command 'dbt source freshness', Paradime will provide the state of each of your sources. This helps you determine the status of your source data and whether it aligns with your SLAs.
During a Bolt schedule execution, dbt™ generates various files including run SQL files, compiled SQL files, manifest files, and JSON files. These artifacts provide insights into what was executed and how, enabling you to analyze the output of your dbt runs in detail.
Viewing Bolt Schedule Output
You've learned how to navigate the Bolt Schedules overview, access detailed information about specific schedules, and interpret run history, logs, and artifacts. This knowledge will help you effectively monitor and analyze your dbt™ schedules, enabling you to optimize your data workflows and quickly troubleshoot any issues.
Next, we'll explore how to set up notifications for your Bolt schedules, ensuring you stay informed about the status of your data pipelines.
| Field | Description | Example |
|---|---|---|
| Field | Description | Example |
|---|---|---|
| Run Log Type | Description | Use Case |
|---|---|---|
Name
Name of the schedule
hourly scheduled run
Status
Current status of the schedule
Success
Owner
The schedule's owner (if configured)
john@acme.com
Cron Description
Human-readable description of the schedule's run time (UTC)
At 00:00, every day (UTC)
Cron Configuration
The cron syntax for the scheduled run
@daily
Last Run
Date and time of the most recent execution
August 22, 2024 at 5:00 PM PDT
Next Run
Anticipated date and time for the next execution
August 23, 2024 at 5:00 PM PDT
Until Next Run
Time remaining until the next scheduled runT
20 hours, 38 minutes, 52 seconds
Trigger Type
How the schedule is triggered (On schedule, On Run Completion)
standard
On Completion Configuration
Details of On Run Completion configuration (if applicable)
schedule base run in workspace irishtrooper on status passed, failed
Status
Status of the specific runID
Success
Trigger
If the runID was manually triggered manually or automatically
Manual from john@acme.com
Branch and commit
The branch name and commit SHA used when running the schedule
main #ce34f
Last Run
Date and time of when the runID was executed
last month
Duration
How long the run took to complete
25 seconds
RunID
Unique identifier of the run
13403
Summary Logs
DinoAI-generated overview of dbt command execution, including warnings and potential fixes
Quick assessment of run health and identification of common issues
Console Logs
Detailed, chronological record of all operations
Detailed troubleshooting and understanding of the execution process
Debug Logs
Extensive details including system-level operations and dbt™ internals
In-depth problem solving and performance tuning for complex issues
