A single worker instance. This tier is suitable for learning how to use
Cloud ML, and for experimenting with new models using small datasets.
BasicGpu
A single worker instance with a K80 GPU.
BasicTpu
A single worker instance with a Cloud TPU.
Custom
The CUSTOM tier is not a set tier, but rather enables you to use your
own cluster specification. When you use this tier, set values to
configure your processing cluster according to these guidelines:
You must set ExecutionTemplate.masterType to specify the type
of machine to use for your master node. This is the only required
setting.
Premium1
A large number of workers with many parameter servers.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-03-21 UTC."],[[["This page provides reference documentation for the `ScaleTier` enum within the Google Cloud Notebooks v1 API, specifically for the `ExecutionTemplate.Types` class."],["The `ScaleTier` enum is used to specify machine types and the number of replicas for workers and parameter servers in AI Platform Notebooks."],["Available scale tiers include `Basic`, `BasicGpu`, `BasicTpu`, `Custom`, `Premium1`, `Standard1`, and `Unspecified`, each with a distinct configuration and intended use case."],["The `Custom` tier allows for user-defined cluster specifications, requiring the `ExecutionTemplate.masterType` to be set."],["The latest version of the API for `ScaleTier` is 2.5.0, with prior versions 2.4.0, 2.3.0, 2.2.0, 2.1.0, 2.0.0, and 1.0.0-beta04 also documented."]]],[]]
