Platform Transition Update - NDT Dataset, Tables, & Views

If you’ve been following our blog over the last few months, you know M-Lab has been working toward a complete server platform upgrade. As of November 20, 2019, all M-Lab servers are now managed by Kubernetes, running Docker container services for all experiments. This transition has greatly improved our platform management, this post addresses the short term impact on downstream data users and applications, and outlines a temporary solution and our longer term for new NDT tables/views.

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Naming BQ Datasets after M-Lab Measurement Services & Data Types

Earlier this year, M-Lab published blog post outlining our new ETL pipeline and transition to new BigQuery tables. That post also outlined where we’ve saved our datasets, tables, and views in BigQuery historically, and recommended tables and views for most researchers to use. At that time we also implemented semantic versioning to new dataset and table releases at that time, and began publishing BigQuery views that unify our NDT data across multiple schema iterations and migrations.

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