Status

View and manage Data Pipeline runs for your Project.

The Status page shows you all ongoing and previous DBNL Data Pipeline runs for your project.

These runs represent the entire Data Pipeline, including:

• Data ingestion from the specified Data Connection for the Project

• Log enrichment by appending Metrics using the Model Connection

• Analysis and publishing of Insights

You can view the current status of each run grouped by data date range, which time window DBNL was ingesting data for. If a Data Pipeline run has errored you can hover over the error status to view the exception and restart the run by clicking on the restart button in the actions column.

Expected Pipeline Duration

Typical pipeline run times depend on log volume and Model Connection latency:

Log Volume	Expected Duration	Notes
< 1,000 logs	3-7 minutes	Fast for testing/POC
1,000-10,000 logs	10-30 minutes	Typical small projects
10,000-100,000 logs	30-90 minutes	Standard production workload
> 100,000 logs	1-3 hours	Large-scale deployments

Pipeline stages and their typical durations:

1. Ingest (10-30 seconds): Upload and validate data

2. Enrich (60-80% of total time): Compute metrics using Model Connection

3. Analyze (10-20% of total time): Run unsupervised learning algorithms

4. Publish (30-60 seconds): Update dashboards and generate insights

Enrich is the slowest stage because it calls your Model Connection for each log. Faster Model Connections (local NVIDIA NIMs) will significantly reduce total pipeline time compared to external APIs.

The DBNL Data Pipeline contains many different tasks and can be complex to debug. Please reach out to us at [email protected] or distributional.com/contact and we would be happy to help.