Pipeline Costs
Last updated
Last updated
Masthead's Cost Recommendations identify actionable optimizations to improve cloud spend and ROI for data products.
Masthead analyzes BigQuery compute resource consumption and provides recommendations based on the pipelines and resource usage patterns. These recommendations help leverage the most cost-effective BigQuery compute billing models (e.g. on-demand or capacity pay-as-you-go).
Compute Billing Models: BigQuery offers different compute billing models that impact costs. Masthead analyzes usage to determine the optimal model. More details in Google Cloud documentation.
Check recommendations on the dashboard.
Masthead analyzes and aggregates all compute resources used within a project to recommend the most cost-effective compute pricing model. We consider overall project usage patterns and potential savings by switching between On-Demand and Editions Standard models.
Check overall compute usage and see project level recommendation on Costs Insights page.
Masthead provides a granular view of compute costs, grouped by pipeline. This allows to optimize costs at the pipeline level by considering moving them under BigQuery Standard Editions model based on slot-consumption. Filter by labels to analyze specific workloads.
Recommendation: Review pipeline-specific recommendations on the Costs Insights page and consider adjusting pipeline compute configurations.
Read more about combining different compute billing models.
Check pipeline cost recommendations on Costs Insights page:
Masthead identifies tables with no downstream consumption, tagging them as "Dead-End Tables". This allows to analyze related pipelines and reclaim resources.
Recommendation:
Review compute usage associated with dead-end tables.
Verify the tables have no consumers downstream
Adjust or disable related pipelines to reduce unnecessary compute spend.
Check recommendations for pipelines with dead-end tables on Costs Insights page: