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."],[[["The document outlines the `ExecutionTemplate.Types.ScaleTier` enum within the Google Cloud Notebooks v1 API, detailing various scaling tiers for AI Platform Notebooks."],["There are seven defined scale tiers: `Basic`, `BasicGpu`, `BasicTpu`, `Custom`, `Premium1`, `Standard1`, and `Unspecified`, each with specific characteristics related to worker and parameter server configurations."],["The `Custom` tier allows for user-defined cluster specifications, requiring the `ExecutionTemplate.masterType` to be set."],["Version history for the enum is available, ranging from version 1.0.0-beta04 to 2.5.0 (latest), offering various assembly versions and providing links to each."]]],[]]
