Cloud Masters Episode #101
Demystifying Google BigQuery’s Autoscaler
Listen to learn how BigQuery’s autoscaler works, ideal use cases, and costly pitfalls to avoid.
Cloud Masters Episode #101

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Cloud Masters
Cloud Masters
Demystifying Google BigQuery’s Autoscaler
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Cloud Masters
Cloud Masters
Demystifying Google BigQuery’s Autoscaler
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Episode notes

If you’re using BigQuery Editions or considering it, understanding how the Autoscaler functions is critical. We take a deep dive into BigQuery’s autoscaler, dissecting how it works, which use cases it’s best suited for, and common pitfalls to avoid if you want to keep your BigQuery costs in check.

About the guests

Sayle Matthews
Sayle Matthews is a Senior Cloud Architect II at DoiT International focusing on data solutions. Sayle has a solid track record of designing and implementing efficient solutions to complex problems. Among a myriad of diverse technical knowledge, Sayle is currently acting as one of the leaders in advising customers on optimizing BigQuery for the recently launched Editions pricing models.
Matthew Richardson
Matthew Richardson is a Senior Cloud Architect at DoiT International specializing in the Data & Analytics space, with certifications across all major cloud providers — Google Cloud, AWS, Azure — as well as Snowflake, DBT, Python, Tableau and SAS. He has deep experience in the use of a variety of Data Engineering, ETL, BI reporting & programming tool sets including the above products plus Matillion, Talend, Cognos, Teradata and Business Objects in addition. Matthew currently works with customers in optimizing their Data Modelling strategies particularly in BigQuery, Redshift or Snowflake, ensuring customers are getting the most out of their data on a consistent basis.
Sayle Matthews is a Senior Cloud Architect II at DoiT International focusing on data solutions. Sayle has a solid track record of designing and implementing efficient solutions to complex problems. Among a myriad of diverse technical knowledge, Sayle is currently acting as one of the leaders in advising customers on optimizing BigQuery for the recently launched Editions pricing models.
Matthew Richardson is a Senior Cloud Architect at DoiT International specializing in the Data & Analytics space, with certifications across all major cloud providers — Google Cloud, AWS, Azure — as well as Snowflake, DBT, Python, Tableau and SAS. He has deep experience in the use of a variety of Data Engineering, ETL, BI reporting & programming tool sets including the above products plus Matillion, Talend, Cognos, Teradata and Business Objects in addition. Matthew currently works with customers in optimizing their Data Modelling strategies particularly in BigQuery, Redshift or Snowflake, ensuring customers are getting the most out of their data on a consistent basis.

Related content

BigQuery Editions and What You Need to Know
Important things to know about BigQuery Editions, its autoscaler, and pitfalls to avoid.
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BigQuery: Migration to Standard Edition from On-Demand in 5 Steps
A step-by-step guide for determining whether it’s cost-beneficial to switch from on-demand to Editions.
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