docs: clarify setup guide deploys single-node workspace

environment-setup/setup-guide.mdx

@@ -1,15 +1,19 @@
 ---
 title: "Setup Guide"
 description: "Detailed walkthrough for deploying a tracebloc workspace — requirements, installer internals, GPU support, and verification."
 ---
 
 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 |
 |---|---------|-------------|
@@ -19,7 +23,7 @@
 
 **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`.
 
 ---
 
@@ -29,7 +33,7 @@
 
 ## 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.
 
 Open the [client page](https://ai.tracebloc.io/clients) and click **"+"**.
 
@@ -93,11 +97,11 @@
 **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**
 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.
 
 **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.
 
 When it finishes you'll see a summary like:
 
@@ -138,7 +142,7 @@
 | `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.
 
 <Tip>
 Stuck on Offline? Check the [Troubleshooting](/environment-setup/troubleshooting) page — most issues resolve with a pod restart or credential check.