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Get a Google support package
Google Cloud offers different support packages to meet different needs, such as
24/7 coverage, phone support, and access to a technical support manager. For
more information, see Cloud Customer Care.
Get support from the community
Ask a question on Google Cloud Community
Ask a question about Vertex AI on Google Cloud
Community.
Use the tag Vertex AI Platform for questions about
Vertex AI. This tag not only receives responses
from the community but also from Google engineers, who monitor the tag and
offer unofficial support.
Get support for machine learning frameworks
Vertex AI provides prebuilt containers with the following
machine learning (ML) frameworks: PyTorch, scikit-learn, TensorFlow, and
XGBoost. Use of these prebuilt containers in Vertex AI is fully
backed by the SLA and covered by the standard support options.
Vertex AI provides a managed service which implements the Kubeflow SDK:
Vertex AI Pipelines. Using Vertex AI Pipelines is fully backed by the SLA and covered
by the standard support options.
Open source Kubeflow running on a GKE cluster is not covered by the standard support options.
To get support for an ML framework, including for bugs and documentation issues
unrelated to Vertex AI, use that ML framework's support options:
Keep track of Vertex AI issues on the
issue tracker.
You can also submit product or documentation issues by clicking the
Send feedback button on a relevant documentation page.
This opens a feedback form. Your product feedback will be
reviewed by the Vertex AI team. Documentation feedback will be
reviewed by the Vertex AI documentation team.
[[["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 2025-08-25 UTC."],[],[],null,["# Get support\n\nGet a Google support package\n----------------------------\n\nGoogle Cloud offers different support packages to meet different needs, such as\n24/7 coverage, phone support, and access to a technical support manager. For\nmore information, see [Cloud Customer Care](/support).\n\nGet support from the community\n------------------------------\n\n### Ask a question on Google Cloud Community\n\nAsk a question about Vertex AI on [Google Cloud\nCommunity](https://www.googlecloudcommunity.com/gc/forums/filteredbylabelpage/board-id/cloud-ai-ml/label-name/vertex%20ai%20platform/).\nUse the tag `Vertex AI Platform` for questions about\nVertex AI. This tag not only receives responses\nfrom the community but also from Google engineers, who monitor the tag and\noffer unofficial support.\n\nGet support for machine learning frameworks\n-------------------------------------------\n\nVertex AI provides prebuilt containers with the following\nmachine learning (ML) frameworks: PyTorch, scikit-learn, TensorFlow, and\nXGBoost. Use of these prebuilt containers in Vertex AI is fully\nbacked by the SLA and covered by the standard support options.\n\nVertex AI provides a managed service which implements the Kubeflow SDK:\nVertex AI Pipelines. Using Vertex AI Pipelines is fully backed by the SLA and covered\nby the standard support options.\n\nOpen source Kubeflow running on a GKE cluster is **not** covered by the standard support options.\n\nTo get support for an ML framework, including for bugs and documentation issues\nunrelated to Vertex AI, use that ML framework's support options:\n\n- To get support for Pytorch, see the\n [PyTorch documentation](https://pytorch.org/docs/stable/index.html). To submit issues to PyTorch,\n see the [PyTorch issue tracker on GitHub](https://github.com/pytorch/pytorch/issues).\n\n- To get support for scikit-learn, see the\n [scikit-learn FAQ](https://scikit-learn.org/stable/faq.html). To submit issues to scikit-learn,\n see the [scikit-learn issue tracker on GitHub](https://github.com/scikit-learn/scikit-learn/issues).\n\n- To get support for TensorFlow, see the\n [TensorFlow documentation](https://www.tensorflow.org/). To submit issues to\n TensorFlow, see the\n [TensorFlow issue tracker on GitHub](https://github.com/tensorflow/tensorflow/issues).\n\n- To get support for XGBoost, see the [XGBoost FAQ](https://xgboost.readthedocs.io/en/latest/faq.html).\n To submit issues to XGBoost, see the\n [XGBoost issue tracker on GitHub](https://github.com/dmlc/xgboost/issues).\n\n- To get support for Kubeflow, see the [Kubeflow Docs](https://www.kubeflow.org/docs/).\n To submit issues to Kubeflow Pipelines, see the\n [Kubeflow issue tracker on GitHub](https://github.com/kubeflow/pipelines/issues).\n\nFile bugs or feature requests\n-----------------------------\n\nKeep track of Vertex AI issues on the\n[issue tracker](https://issuetracker.google.com/issues/new?component=1130925).\n\nYou can also submit product or documentation issues by clicking the\n**Send feedback** button on a relevant documentation page.\nThis opens a feedback form. Your product feedback will be\nreviewed by the Vertex AI team. Documentation feedback will be\nreviewed by the Vertex AI documentation team."]]
