Viewing Run History and Analytics

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

Prerequisites

Access to the Bolt application in Paradime
At least one configured Bolt schedule

What you’ll learn

In this guide, you’ll learn how to:

1. Bolt Schedules Overview

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:

Field	Description	Example
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`

2. Bolt Schedule Detail Views

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.

2.1: Run History

In the Run History section, you can view all executions of a specific scheduled run:

Field	Description	Example
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`

2.2: Logs and Artifacts

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:

2.3: Run Logs

By clicking on a specific command executed in your bolt schedule (e.g., dbt run) you’ll have access to various run logs:

Run Log Type	Description	Use Case
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

2.4: Source Freshness

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.

2.5: Artifacts

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.

Related Documentation

Summary

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.

​What you’ll learn

​1. Bolt Schedules Overview

​2. Bolt Schedule Detail Views

​2.1: Run History

​2.2: Logs and Artifacts

​2.3: Run Logs

​2.4: Source Freshness

​2.5: Artifacts

​Summary

What you’ll learn

1. Bolt Schedules Overview

2. Bolt Schedule Detail Views

2.1: Run History

2.2: Logs and Artifacts

2.3: Run Logs

2.4: Source Freshness

2.5: Artifacts

Summary