Build and operate the data processing systems behind analytics and ML on Google Cloud, including BigQuery, Dataflow, and Pub/Sub, and track your readiness for the Professional Data Engineer exam.
Advanced
Prepare and test your skills
Advanced
Prepare and test your skills
Google Cloud service
Colossus
Topic in 3 exam domains
Colossus · Service
Colossus · Concept
Core Google distributed storage infrastructure underlying Google SecOps.
Points to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
Bigtable depends on Colossus From the official documentation: “When you use Bigtable, your data is stored on Colossus, a Google-developed, highly durable file system, using storage devices in Google Cloud's data centers.”
Persistent Disk depends on Colossus From the official documentation: “Persistent Disk volumes use Colossus for the storage backend.”
Persistent Disk is part of Compute Engine From the official documentation: “Compute Engine offers different types of persistent disks.”
Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
Cloud Storage works with Compute Engine From the official documentation: “You can use a web browser, the Google Cloud CLI, or a programming language to transfer files between Cloud Storage and Compute Engine VMs.”
Compute Engine works with Persistent Disk From the official documentation: “Add a persistent disk to Compute Engine”
Bigtable is an alternative to Cloud Storage From the official documentation: “If the joining data is in the gigabyte or terabyte range, use either Bigtable or Cloud Storage to merge the joining data to the driving data, depending on the nature of the data.”
Bigtable works with Compute Engine From the official documentation: “The Compute Engine instances can connect to and manage the Bigtable instance.”
Bigtable works with Dataflow From the official documentation: “The Dataflow job then writes the transformed data to your Bigtable table.”
Dataflow depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
Dataflow depends on Compute Engine From the official documentation: “When you run your pipeline on the Dataflow service, Dataflow creates Compute Engine instances to run your pipeline code.”
Bigtable works with Cloud Storage From the official documentation: “Another way you can back up Bigtable is to use a managed data export to Cloud Storage.”
Cloud Storage is an alternative to Persistent Disk From the official documentation: “Both Persistent Disk and Cloud Storage can both be used to store files but are very different offerings.”
Dataflow works with Persistent Disk From the official documentation: “By default, Dataflow selects the machine type for the worker VMs that run your job, along with the size and type of Persistent Disk.”