The activities data table associated with your workspace logs record enrolments, node executions, and success/failure outcomes across all your tools and plays.
These logs provide real-time visibility into how your workflows are performing—helping you identify bottlenecks, debug errors, and discover optimization opportunities.
You can query activities data from your data warehouse’s query editor, a
Cargo data model, or the Sandbox query editor in the System of Record
section of your workspace settings.
- Adapt query syntax for your database (BigQuery or Snowflake) - If using your
own data warehouse, the dataset name matches the Dataset name from your
System of Record configuration - If using Cargo’s managed Snowflake, contact
the Cargo team for connection details
Understanding the activities table
The activities data is stored in the compute__activities table with the following structure:
| Column | Description |
|---|
_id | Unique identifier for each activity |
_time | Timestamp when the activity occurred |
kind | Type of activity (see below) |
model_uuid | Reference to the data model (if applicable) |
workflow_uuid | Reference to the workflow |
play_uuid | Reference to the play (if applicable) |
tool_uuid | Reference to the tool (if applicable) |
segment_uuid | Reference to the segment (for segment activities) |
context | JSON object containing detailed activity information |
Activity types
| Kind | Description |
|---|
workflowNodeExecuted | A specific node in a workflow completed execution |
workflowEntered | A record entered a workflow |
workflowLeft | A record exited a workflow |
segmentEntered | A record entered a segment |
segmentLeft | A record left a segment |
Example: Track workflow node executions
Query all node executions for a specific workflow, including their status and any error messages:
SELECT
_time,
JSON_VALUE(context, '$.nodeSlug') AS node_name,
JSON_VALUE(context, '$.nodeKind') AS node_type,
JSON_VALUE(context, '$.nodeStatus') AS status,
JSON_VALUE(context, '$.nodeErrorMessage') AS error_message
FROM [DATASET].compute__activities
WHERE kind = 'workflowNodeExecuted'
AND JSON_VALUE(context, '$.workflowUuid') = 'your-workflow-uuid-here'
ORDER BY _time DESC;
SELECT
_time,
context:nodeSlug AS node_name,
context:nodeKind AS node_type,
context:nodeStatus AS status,
context:nodeErrorMessage AS error_message
FROM [DATABASE]._compute.activities
WHERE kind = 'workflowNodeExecuted'
AND context:workflowUuid = 'your-workflow-uuid-here'
ORDER BY _time DESC;
Example: Track workflow throughput
Monitor how many records enter and exit your workflows over time:
SELECT
DATE(_time) AS date,
kind,
COUNT(*) AS count
FROM [DATASET].compute__activities
WHERE kind IN ('workflowEntered', 'workflowLeft')
AND workflow_uuid = 'your-workflow-uuid-here'
GROUP BY date, kind
ORDER BY date DESC;
SELECT
DATE(_time) AS date,
kind,
COUNT(*) AS count
FROM [DATABASE]._compute.activities
WHERE kind IN ('workflowEntered', 'workflowLeft')
AND workflow_uuid = 'your-workflow-uuid-here'
GROUP BY date, kind
ORDER BY date DESC;
Example: Identify failing nodes
Find nodes with the highest error rates:
SELECT
JSON_VALUE(context, '$.nodeSlug') AS node_name,
COUNT(*) AS total_executions,
COUNTIF(JSON_VALUE(context, '$.nodeStatus') = 'failed') AS failures,
ROUND(
COUNTIF(JSON_VALUE(context, '$.nodeStatus') = 'failed') * 100.0 / COUNT(*),
2
) AS failure_rate
FROM [DATASET].compute__activities
WHERE kind = 'workflowNodeExecuted'
AND _time >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
GROUP BY node_name
HAVING failures > 0
ORDER BY failure_rate DESC;
SELECT
context:nodeSlug AS node_name,
COUNT(*) AS total_executions,
COUNT_IF(context:nodeStatus = 'failed') AS failures,
ROUND(COUNT_IF(context:nodeStatus = 'failed') * 100.0 / COUNT(*), 2) AS failure_rate
FROM [DATABASE]._compute.activities
WHERE kind = 'workflowNodeExecuted'
AND _time >= DATEADD(DAY, -7, CURRENT_TIMESTAMP())
GROUP BY node_name
HAVING failures > 0
ORDER BY failure_rate DESC;
Table naming conventions
Depending on your System of Record scope, use the appropriate table reference:
| Scope | Table reference |
|---|
| BigQuery project-level | [PROJECT_ID].[DATASET].compute__activities |
| BigQuery dataset-level | [DATASET].compute__activities |
| Snowflake database-level | [DATABASE]._compute.activities |
| Snowflake schema-level | [DATABASE].[SCHEMA]._compute__activities |
Replace bracketed values (e.g., [PROJECT_ID], [DATASET]) with your actual
configuration values from the System of Record settings.
