diff --git a/docs/user-guide/Configuration.md b/docs/user-guide/Configuration.md
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+
+# Configuring `pydase`
+
+## Do I Need to Configure My `pydase` Service?
+
+`pydase` services work out of the box without requiring any configuration. However, you
+might want to change some options, such as the web server port or logging level. To 
+accommodate such customizations, `pydase` allows configuration through environment 
+variables - avoiding hard-coded settings in your service code.
+
+Why should you avoid hard-coding configurations? Here are two reasons:
+
+1. **Security**:  
+    Protect sensitive information, such as usernames and passwords. By using environment
+    variables, your service code can remain public while keeping private information 
+    secure.
+
+2. **Reusability**:  
+    Services often need to be reused in different environments. For example, you might
+    deploy multiple instances of a service (e.g., for different sensors in a lab). By 
+    separating configuration from code, you can adapt the service to new requirements 
+    without modifying its codebase.
+
+Next, we’ll walk you through the environment variables `pydase` supports and provide an
+example of how to separate service code from configuration.
+
+## Configuring `pydase` Using Environment Variables
+
+`pydase` provides the following environment variables for customization:
+
+- **`ENVIRONMENT`**:  
+  Defines the operation mode (`"development"` or `"production"`), which influences 
+  behaviour such as logging (see [Logging in pydase](https://github.com/tiqi-group/pydase?tab=readme-ov-file#logging-in-pydase)).
+
+- **`SERVICE_CONFIG_DIR`**:  
+  Specifies the directory for configuration files (e.g., `web_settings.json`). Defaults
+  to the `config` folder in the service root. Access this programmatically using:
+
+    ```python
+    import pydase.config
+    pydase.config.ServiceConfig().config_dir
+    ```
+
+- **`SERVICE_WEB_PORT`**:  
+  Defines the web server’s port. Ensure each service on the same host uses a unique 
+  port. Default: `8001`.
+
+- **`GENERATE_WEB_SETTINGS`**:  
+  When `true`, generates or updates the `web_settings.json` file. Existing entries are 
+  preserved, and new entries are appended.
+
+### Configuring `pydase` via Keyword Arguments
+
+Some settings can also be overridden directly in your service code using keyword 
+arguments when initializing the server. This allows for flexibility in code-based 
+configuration:
+
+```python
+import pathlib
+from pydase import Server
+from your_service_module import YourService
+
+server = Server(
+    YourService(),
+    web_port=8080,                             # Overrides SERVICE_WEB_PORT
+    config_dir=pathlib.Path("custom_config"),  # Overrides SERVICE_CONFIG_DIR
+    generate_web_settings=True                 # Overrides GENERATE_WEB_SETTINGS
+).run()
+```
+
+## Separating Service Code from Configuration
+
+To decouple configuration from code, `pydase` utilizes `confz` for configuration 
+management. Below is an example that demonstrates how to configure a `pydase` service 
+for a sensor readout application.
+
+### Scenario: Configuring a Sensor Service
+
+Imagine you have multiple sensors distributed across your lab. You need to configure 
+each service instance with:
+
+1. **Hostname**: The hostname or IP address of the sensor.
+2. **Authentication Token**: A token or credentials to authenticate with the sensor.
+3. **Readout Interval**: A periodic interval to read sensor data and log it to a 
+  database.
+
+Given the repository structure:
+
+```bash title="Service Repository Structure"
+my_sensor
+├── pyproject.toml        
+├── README.md             
+└── src                   
+    └── my_sensor       
+        ├── my_sensor.py
+        ├── config.py     
+        ├── __init__.py   
+        └── __main__.py   
+```
+
+Your service might look like this:
+
+### Configuration
+
+Define the configuration using `confz`:
+
+```python title="src/my_sensor/config.py"
+import confz
+from pydase.config import ServiceConfig
+
+class MySensorConfig(confz.BaseConfig):
+    instance_name: str
+    hostname: str
+    auth_token: str
+    readout_interval_s: float
+
+    CONFIG_SOURCES = confz.FileSource(file=ServiceConfig().config_dir / "config.yaml")
+```
+
+This class defines configurable parameters and loads values from a `config.yaml` file
+located in the service’s configuration directory (which is configurable through an 
+environment variable, see [above](#configuring-pydase-using-environment-variables)).  
+A sample YAML file might look like this:
+
+```yaml title="config.yaml"
+instance_name: my-sensor-service-01
+hostname: my-sensor-01.example.com
+auth_token: my-secret-authentication-token
+readout_interval_s: 5
+```
+
+### Service Implementation
+
+Your service implementation might look like this:
+
+```python title="src/my_sensor/my_sensor.py"
+import asyncio
+import http.client
+import json
+import logging
+from typing import Any
+
+import pydase.components
+import pydase.units as u
+from pydase.task.decorator import task
+
+from my_sensor.config import MySensorConfig
+
+logger = logging.getLogger(__name__)
+
+
+class MySensor(pydase.DataService):
+    def __init__(self) -> None:
+        super().__init__()
+        self.readout_interval_s: u.Quantity = (
+            MySensorConfig().readout_interval_s * u.units.s
+        )
+
+    @property
+    def hostname(self) -> str:
+        """Hostname of the sensor. Read-only."""
+        return MySensorConfig().hostname
+
+    def _get_data(self) -> dict[str, Any]:
+        """Fetches sensor data via an HTTP GET request. It passes the authentication 
+        token as "Authorization" header."""
+
+        connection = http.client.HTTPConnection(self.hostname, timeout=10)
+        connection.request(
+            "GET", "/", headers={"Authorization": MySensorConfig().auth_token}
+        )
+        response = connection.getresponse()
+        connection.close()
+
+        return json.loads(response.read())
+
+    @task(autostart=True)
+    async def get_and_log_sensor_values(self) -> None:
+        """Periodically fetches and logs sensor data."""
+        while True:
+            try:
+                data = self._get_data()
+                # Write data to database using MySensorConfig().instance_name ...
+            except Exception as e:
+                logger.error(
+                    "Error occurred, retrying in %s seconds. Error: %s",
+                    self.readout_interval_s.m,
+                    e,
+                )
+            await asyncio.sleep(self.readout_interval_s.m)
+```
+
+### Starting the Service
+
+The service is launched via the `__main__.py` entry point:
+
+```python title="src/my_sensor/__main__.py"
+import pydase
+from my_sensor.my_sensor import MySensor
+
+pydase.Server(MySensor()).run()
+```
+
+You can now start the service with:
+
+```bash
+python -m my_sensor
+```
+
+This approach ensures the service is fully configured via the `config.yaml` file,
+separating service logic from configuration.
diff --git a/mkdocs.yml b/mkdocs.yml
index b360f0b..40765de 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -11,6 +11,7 @@ nav:
     - Understanding Tasks: user-guide/Tasks.md
     - Understanding Units: user-guide/Understanding-Units.md
     - Validating Property Setters: user-guide/Validating-Property-Setters.md
+    - Configuring pydase: user-guide/Configuration.md
   - Developer Guide: 
     - Developer Guide: dev-guide/README.md
     - API Reference: dev-guide/api.md