# tracebloc

## Docs

- [Define Use Case](https://docs.tracebloc.io/create-use-case/define.md): Create, configure, and publish an AI use case on tracebloc in four steps.
- [Evaluate models](https://docs.tracebloc.io/create-use-case/evaluate-models.md): Compare vendor models side by side on the leaderboard.
- [Prepare Data](https://docs.tracebloc.io/create-use-case/prepare-dataset.md): Learn how to prepare and ingest your datasets into tracebloc using containerized data ingestors. Complete guide for CSV, image, and text data with Kubernetes deployment steps.
- [Prerequisites](https://docs.tracebloc.io/create-use-case/prerequisites.md): Supported data types, tasks, and requirements for creating a use case on tracebloc.
- [Templates](https://docs.tracebloc.io/create-use-case/templates.md): Ready-made data ingestion templates for every supported task — clone, configure, deploy.
- [tracebloc CLI](https://docs.tracebloc.io/environment-setup/cli.md): Manage and operate your workspace from the command line — inspect the cluster, ingest and remove datasets, validate configs.
- [Configuration](https://docs.tracebloc.io/environment-setup/configuration.md): Customize your tracebloc workspace — environment variables, cluster management, GPU support, and manual Helm deployment.
- [Azure AKS](https://docs.tracebloc.io/environment-setup/deploy-aks.md): Deploy a tracebloc workspace on Azure Kubernetes Service.
- [Bare-metal](https://docs.tracebloc.io/environment-setup/deploy-bare-metal.md): Deploy a tracebloc workspace on your own on-prem Kubernetes cluster.
- [Local / k3d](https://docs.tracebloc.io/environment-setup/deploy-local.md): Run a tracebloc workspace on a single machine — laptop or on-prem server. Production-capable.
- [OpenShift](https://docs.tracebloc.io/environment-setup/deploy-openshift.md): Deploy a tracebloc workspace on Red Hat OpenShift or OKD.
- [Deployment environments](https://docs.tracebloc.io/environment-setup/deployment-environments.md): Run tracebloc anywhere — local, bare-metal, EKS, AKS, or OpenShift. Same chart, same steps, your choice of infrastructure.
- [Amazon EKS](https://docs.tracebloc.io/environment-setup/eks-client-deployment-guide.md): Deploy a tracebloc workspace on Amazon EKS using the AWS CLI — networking, GPU support, storage, and security for a production cluster.
- [Operations](https://docs.tracebloc.io/environment-setup/operations.md): Run, monitor, upgrade, and maintain a tracebloc workspace day to day.
- [Overview](https://docs.tracebloc.io/environment-setup/overview.md): How tracebloc runs on your infrastructure — and why your data never leaves it.
- [Quick Start](https://docs.tracebloc.io/environment-setup/quickstart.md): From zero to a running tracebloc workspace in about 10 minutes.
- [Security & data handling](https://docs.tracebloc.io/environment-setup/security.md): What stays on your infrastructure, what leaves, and how tracebloc enforces it — the page to share with your security team.
- [Setup Guide](https://docs.tracebloc.io/environment-setup/setup-guide.md): Detailed walkthrough for deploying a tracebloc workspace — requirements, installer internals, GPU support, and verification.
- [Troubleshooting](https://docs.tracebloc.io/environment-setup/troubleshooting.md): Common issues and debugging commands for your tracebloc workspace.
- [Explore Use Cases](https://docs.tracebloc.io/join-use-case/explore-use-case.md): Understand the use case page: leaderboard, description, EDA, training experiments, submissions and evaluation metrics.
- [How training works](https://docs.tracebloc.io/join-use-case/how-training-works.md): What the tracebloc client does to your data and model in each use case, so you can reproduce a run locally and compare results.
- [Hyperparameters](https://docs.tracebloc.io/join-use-case/hyperparameters.md): Configure your model's training behavior by setting hyperparameters, training parameters, and augmentation options.
- [Join](https://docs.tracebloc.io/join-use-case/join-use-case.md): Learn how to join a use case on the tracebloc platform.
- [Evaluate Model](https://docs.tracebloc.io/join-use-case/model-evaluation.md): Learn how to evaluate your model on the test data and submit it to the leaderboard.
- [Customize Models](https://docs.tracebloc.io/join-use-case/model-optimization.md): Learn the model format requirements, mandatory variables per framework and pre-trained weights for uploading and training models on the tracebloc workspace.
- [Overview](https://docs.tracebloc.io/join-use-case/overview.md): Learn how the tracebloc AI workspace works: explore use cases, train models on private data, and submit models to the leaderboard.
- [Start Training](https://docs.tracebloc.io/join-use-case/start-training.md): Step-by-step guide to training a model on the tracebloc platform.
- [tracebloc](https://docs.tracebloc.io/overview/tracebloc.md): Build better AI together. Without moving data.
- [Frequently Asked Questions](https://docs.tracebloc.io/tools-help/faqs.md): Common questions about running tracebloc — privacy, infrastructure, training, and getting help.
- [Key Terms](https://docs.tracebloc.io/tools-help/key-terms.md): Important terminology and concepts used in Tracebloc.
- [tracebloc Python SDK](https://docs.tracebloc.io/tools-help/tracebloc.md): Python library for uploading models, linking them with datasets, configuring training parameters, and launching training runs on the tracebloc platform.

## Optional

- [Website](https://tracebloc.io)
- [Blog](https://tracebloc.io/blog)
- [Platform](https://ai.tracebloc.io)