telemetry docs

docs/user-guide/configurations.md

@@ -101,7 +101,7 @@ DATU_ENABLE_MCP=true
 ##### MCP Servers Configuration
 Define your MCP servers in a JSON config file (e.g. mcp_config.json):
 
-```sh
+```json
 {
   "mcpServers": {
     "sql_generator": {
@@ -113,3 +113,12 @@ Define your MCP servers in a JSON config file (e.g. mcp_config.json):
 }
 ```
 
+#### Telemetry related configuration
+
+##### Product telemetry
+
+Product telemetry is enabled by default and you can disable it by
+
+```sh
+DATU_ENABLE_ANONYMIZED_TELEMETRY=false
+```

docs/user-guide/deploy/deploy_as_container_service.md

@@ -6,7 +6,7 @@ Use below recommended method to run Datu application as container service.
 
 To deploy your Datu, you need to containerize it using Podman or Docker. The Dockerfile defines how your application is packaged and run. Below is an example Docker file that installs all needed dependencies, the application, and configures the FastAPI server to run via unicorn dockerfile.
 
-```sh
+```dockerfile
 FROM python:3.11-slim
 SHELL ["/bin/bash", "-c"]
 
@@ -18,15 +18,15 @@ RUN apt-get update && \
     rm -rf /var/lib/apt/lists/* && \
     pip install --upgrade pip
 
-RUN curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add -
-RUN curl https://packages.microsoft.com/config/debian/11/prod.list > /etc/apt/sources.list.d/mssql-release.list
+RUN curl https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > /etc/apt/trusted.gpg.d/microsoft.gpg \
+&& curl https://packages.microsoft.com/config/debian/11/prod.list -o /etc/apt/sources.list.d/mssql-release.list
 
 RUN apt-get update
 RUN env ACCEPT_EULA=Y apt-get install -y msodbcsql18
 WORKDIR /app
+COPY . .
 RUN pip install "datu-core[postgres,sqldb]"
-ENTRYPOINT [] 
-CMD ["uvicorn", "datu.main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]
+CMD ["datu"]
 ```
 
 ## Infrastructure

docs/user-guide/telemetry/product.md

@@ -0,0 +1,48 @@
+# Telemetry in Datu Server
+
+Datu Server comes with a built-in **telemetry system** that gathers **anonymous usage information**.  
+This data helps the maintainers understand how the software is being used and guides ongoing improvements.
+
+---
+
+## Why Telemetry?
+
+Telemetry provides valuable feedback without exposing personal or sensitive information.  
+It allows the team to:
+
+- Measure how features are being adopted.
+- Detect common usage patterns and performance bottlenecks.
+- Prioritize enhancements that have the greatest impact.
+- Ensure the system evolves in line with real-world needs.
+
+---
+
+## What Data Is Collected?
+
+The telemetry system only collects **non-identifiable, aggregated data** such as:
+
+- Basic environment details (e.g., version, operating system).
+- Which features or APIs are being exercised.
+- MCP server names.
+- General performance metrics.
+
+No private data, user content, or identifiers are captured such as: usernames, hostnames, file names, environment variables, or hostnames of systems being tested.
+
+---
+
+## Where is telemetry information stored?
+
+We use [Posthog](https://posthog.com/) to store and visualize telemetry data.
+
+<div style="border: 1px solid #ccc; padding: 12px; border-radius: 6px; background-color: #f9f9f9;">
+  <strong>PostHog</strong> is an open source platform for product analytics.  
+  Learn more at <a href="https://posthog.com">posthog.com</a> or <a href="https://github.com/posthog">github.com/posthog</a>.
+</div>
+
+## Turning Telemetry Off
+
+If you prefer not to share anonymous usage data, you can disable telemetry with an environment variable:
+
+```sh
+export DATU_ENABLE_ANONYMIZED_TELEMETRY=false
+```

mkdocs.yml

@@ -57,7 +57,9 @@ nav:
     - Deploy:
       - Container service: user-guide/deploy/deploy_as_container_service.md
     - MCP:
-        - user-guide/MCP/mcp_connectivity.md
+        - user-guide/mcp/mcp_connectivity.md
+    - Telemetry:
+        - user-guide/telemetry/product.md
   - Architecture:
     - Overview: architecture/README.md
   - Contribute ❤️: https://github.com/Datuanalytics/datu-core/blob/main/CONTRIBUTING.md