diff --git a/.dockerignore b/.dockerignore
new file mode 100644
index 0000000..df5e60b
--- /dev/null
+++ b/.dockerignore
@@ -0,0 +1,8 @@
+__pycache__/
+*.py[cod]
+*.log
+.env
+.git
+.gitignore
+.notebooks
+.ipynb_checkpoints/
diff --git a/.github/workflows/build-docker.yml b/.github/workflows/build-docker.yml
new file mode 100644
index 0000000..8e89a71
--- /dev/null
+++ b/.github/workflows/build-docker.yml
@@ -0,0 +1,32 @@
+name: Build Streamlit image
+
+on:
+  push:
+    branches: ["main"]
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  packages: write
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Log in to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: Dockerfile.streamlit
+          push: true
+          tags: ghcr.io/${{ github.repository_owner }}/btc-tools-dashboard:latest
diff --git a/Dockerfile.streamlit b/Dockerfile.streamlit
new file mode 100644
index 0000000..4f6696d
--- /dev/null
+++ b/Dockerfile.streamlit
@@ -0,0 +1,16 @@
+# syntax=docker/dockerfile:1
+FROM python:3.11-slim AS base
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 8501
+
+CMD ["streamlit", "run", "dashboard/app.py", "--server.port=8501", "--server.address=0.0.0.0"]
diff --git a/README.md b/README.md
index 09c4625..dac615f 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,33 @@
-# btc-tools
\ No newline at end of file
+# btc-tools
+
+BTC Tools provides a Streamlit dashboard and supporting utilities for tracking
+Bitcoin technical indicators using Kraken market data via `ccxt`.
+
+## Quickstart
+
+```bash
+pip install -r requirements.txt
+streamlit run dashboard/app.py
+```
+
+## Run with Docker
+
+Build and start the dashboard in a self-contained container:
+
+```bash
+docker compose up --build
+```
+
+This uses the provided `Dockerfile.streamlit` and maps the service to
+<http://localhost:8501>. The container is configured to restart automatically,
+matching always-on hosts like project hubs.
+
+## Permanent hosting
+
+- Deploy the Docker image automatically with the provided GitHub Actions workflow
+  (publishes to GitHub Container Registry as
+  `ghcr.io/<owner>/btc-tools-dashboard:latest`).
+- Or follow the deployment guide for Streamlit Community Cloud, Hugging Face
+  Spaces, and other hosting targets.
+
+See [docs/deployment.md](docs/deployment.md) for detailed instructions.
diff --git a/compose.yaml b/compose.yaml
new file mode 100644
index 0000000..700dd5a
--- /dev/null
+++ b/compose.yaml
@@ -0,0 +1,11 @@
+services:
+  streamlit:
+    build:
+      context: .
+      dockerfile: Dockerfile.streamlit
+    ports:
+      - "8501:8501"
+    restart: unless-stopped
+    environment:
+      - STREAMLIT_SERVER_PORT=8501
+      - STREAMLIT_SERVER_ADDRESS=0.0.0.0
diff --git a/docs/deployment.md b/docs/deployment.md
new file mode 100644
index 0000000..1b0f519
--- /dev/null
+++ b/docs/deployment.md
@@ -0,0 +1,86 @@
+# Deployment Guide
+
+This project ships with a Streamlit dashboard located at `dashboard/app.py`. The
+sections below walk through a few zero-cost and low-maintenance options for
+keeping the site running continuously, similar to other AI project hubs.
+
+## Option 1 – Streamlit Community Cloud (recommended)
+
+The [Streamlit Community Cloud](https://streamlit.io/cloud) offers free hosting
+for public Streamlit applications and automatically keeps the service alive.
+
+1. **Prepare your repository**
+   - Push this project to a public GitHub repository (forking it is fine).
+   - Ensure the repo contains `dashboard/app.py` and `requirements.txt` at the
+     root (already present in this project).
+2. **Create the app on Streamlit Cloud**
+   - Sign in at <https://streamlit.io/cloud> using your GitHub account.
+   - Click **New app**, pick the repository, select the default branch, and set
+     the main file path to `dashboard/app.py`.
+   - The build system will auto-install dependencies from `requirements.txt` and
+     start the app. The site receives a stable public URL that stays active as
+     long as it has occasional traffic (Streamlit periodically wakes the app).
+3. **Optional: configure secrets / settings**
+   - If you need to override the timeframe or other values, edit
+     `conf/settings.yml` in your repository.
+   - If you later add credentials or API keys, open the Streamlit Cloud app,
+     navigate to **Settings → Secrets**, and paste the key/value pairs in TOML
+     format.
+
+The app will restart automatically whenever you push new commits to the selected
+branch, so keeping it updated is just a matter of pushing to GitHub.
+
+## Option 2 – GitHub Actions + GitHub Container Registry
+
+The repository now includes a workflow at
+`.github/workflows/build-docker.yml` that continuously builds the production
+image using `Dockerfile.streamlit`.
+
+1. Enable GitHub Packages for your account/organization (Settings → Packages).
+2. Push this repository to GitHub and ensure the `main` branch is your default.
+3. On each push to `main`, the workflow builds `ghcr.io/<owner>/btc-tools-dashboard:latest`
+   using the checked-in Dockerfile and publishes it to GHCR. You can also start a
+   manual build from the **Actions** tab via the **Run workflow** button.
+4. Deploy the published image to any container host (Fly.io, Render, Railway,
+   Google Cloud Run, a VPS, etc.) and configure it to restart on failure. The
+   container automatically exposes Streamlit on port 8501 and binds to
+   `0.0.0.0`, so no additional entrypoint work is required.
+
+## Option 3 – Hugging Face Spaces
+
+[Hugging Face Spaces](https://huggingface.co/spaces) can also host Streamlit apps
+permanently with minimal configuration.
+
+1. Create a new **Space** and choose the **Streamlit** template.
+2. Set the `App file` to `dashboard/app.py` and upload the project files (or
+   connect the Space to your GitHub repo via the **Files and versions** tab).
+3. Spaces automatically install the packages from `requirements.txt` and expose
+   the application at `https://<space-name>.hf.space`.
+4. Enable **Hardware → Keep alive** if you want the project to stay running even
+   without visitors (requires HF Pro).
+
+## Option 4 – Self-host with Docker Compose
+
+If you prefer to run the dashboard yourself, use the included Docker artifacts.
+
+```bash
+docker compose up --build -d
+```
+
+The `compose.yaml` file wraps the `Dockerfile.streamlit` image and maps the
+service to port 8501. The container is set to `restart: unless-stopped` so it
+automatically comes back online if the host reboots.
+
+## Keeping the app healthy
+
+Regardless of the hosting option you choose:
+
+- Monitor logs for connectivity limits imposed by the Kraken API (ccxt handles
+  rate limiting, but external providers may throttle sustained heavy use).
+- Schedule occasional visits or use the hosting provider’s “keep warm” toggle to
+  prevent free tiers from sleeping the app.
+- When updating dependencies, test locally with `streamlit run dashboard/app.py`
+  (or `docker compose up --build`) before pushing to production.
+
+With the managed options above—or your own container host—you can achieve an
+always-on experience similar to other AI dashboards hosted on project hubs.