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6 changes: 5 additions & 1 deletion environment-setup/setup-guide.mdx
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---
title: "Setup Guide"
description: "Detailed walkthrough for deploying a tracebloc workspace — requirements, installer internals, GPU support, and verification."

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---

Everything the installer does, explained. This page walks through the full setup process — what each step does, what to expect, and how to verify it worked.

<Note>
The installer deploys a **single-node workspace on one machine** — a local Kubernetes cluster running inside Docker on that host. For multi-node or production deployments, see the [EKS deployment guide](/environment-setup/eks-client-deployment-guide).
</Note>

---

## Requirements

The installer runs on any modern machine. These are the minimum specs to run a workspace comfortably:
The installer runs on any modern machine (one host per workspace). These are the minimum specs to run a workspace comfortably:

| | Minimum | Recommended |
|---|---------|-------------|
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**Supported platforms:** macOS (Intel & Apple Silicon) · Linux (x86_64 & arm64) · Windows (x86_64 & arm64)

**Outbound access needed:** The installer downloads container images and connects to the tracebloc platform. Make sure your network allows traffic to `*.docker.io`, `*.tracebloc.io`, `github.com`, and `pypi.org`.

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---

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## 2. Register a Client

A **client** is your workspace's identity on the platform. It ties a specific machine to your account and controls what data and use cases are accessible from it.

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Open the [client page](https://ai.tracebloc.io/clients) and click **"+"**.

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**Step 2/4 — Set up secure compute environment**
Provisions a lightweight local Kubernetes cluster inside Docker. First run takes 1–2 minutes to download components.

**Step 3/4 — Install tracebloc client**

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Prompts for a **workspace name** (e.g. `berlin-team`, `vision-lab`, `ml-mardan`). This identifies the client on your machine and becomes the Kubernetes namespace.

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**Step 4/4 — Connect to tracebloc network**
Prompts for your **Client ID** and **password** from step 2 above. This links your secure local environment to the tracebloc platform so vendors can submit models for evaluation.

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When it finishes you'll see a summary like:

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| `mysql-...` | Local metadata store — tracks jobs, metrics, and configuration |
| `tracebloc-jobs-manager-...` | The client — executes training jobs and communicates with the platform |

Then open [ai.tracebloc.io](https://ai.tracebloc.io) and check that your client status shows **Online**. This confirms the client has established a secure connection to the tracebloc backend.

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<Tip>
Stuck on Offline? Check the [Troubleshooting](/environment-setup/troubleshooting) page — most issues resolve with a pod restart or credential check.
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