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Merge pull request #6107 from influxdata/docs/generalize-grafana-multinode
Enterprise multi-node recommendations and Python libraries update
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assets/jsconfig.json

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"baseUrl": ".",
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"paths": {
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"*": [
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"*",
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"../node_modules/*"
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"*"
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]
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}
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}

content/shared/v3-core-plugins/_index.md

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### Install Python dependencies
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If your plugin needs additional Python packages, use the `influxdb3 install` command:
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Use the `influxdb3 install package` command to add third-party libraries (like `pandas`, `requests`, or `influxdb3-python`) to your plugin environment.
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This installs packages into the Processing Engine’s embedded Python environment to ensure compatibility with your InfluxDB instance.
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{{% code-placeholders "CONTAINER_NAME|PACKAGE_NAME" %}}
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{{< code-tabs-wrapper >}}
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{{% code-tabs %}}
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[CLI](#)
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[Docker](#)
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{{% /code-tabs %}}
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{{% code-tab-content %}}
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```bash
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# Install a package directly
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# Use the CLI to install a Python package
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influxdb3 install package pandas
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```
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{{% /code-tab-content %}}
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{{% code-tab-content %}}
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```bash
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# With Docker
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# Use the CLI to install a Python package in a Docker container
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docker exec -it CONTAINER_NAME influxdb3 install package pandas
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```
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This creates a Python virtual environment in your plugins directory with the specified packages installed.
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{{% /code-tab-content %}}
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{{< /code-tabs-wrapper >}}
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These examples install the specified Python package (for example, pandas) into the Processing Engine’s embedded virtual environment.
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- Use the CLI command when running InfluxDB directly on your system.
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- Use the Docker variant if you're running InfluxDB in a containerized environment.
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> [!Important]
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> #### Use bundled Python for plugins
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> When you start the server with the `--plugin-dir` option, InfluxDB 3 creates a Python virtual environment (`<PLUGIN_DIR>/venv`) for your plugins.
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> If you need to create a custom virtual environment, use the Python interpreter bundled with InfluxDB 3. Don't use the system Python.
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> Creating a virtual environment with the system Python (for example, using `python -m venv`) can lead to runtime errors and plugin failures.
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>
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>For more information, see the [processing engine README](https://github.com/influxdata/influxdb/blob/main/README_processing_engine.md#official-builds).
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{{% /code-placeholders %}}
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InfluxDB creates a Python virtual environment in your plugins directory with the specified packages installed.
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{{% show-in "enterprise" %}}
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### Connect Grafana to your InfluxDB instance
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## Distributed cluster considerations
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When you deploy {{% product-name %}} in a multi-node environment, configure each node based on its role and the plugins it runs.
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### Match plugin types to the correct node
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Each plugin must run on a node that supports its trigger type:
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| Plugin type | Trigger spec | Runs on |
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|--------------------|--------------------------|-----------------------------|
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| Data write | `table:` or `all_tables` | Ingester nodes |
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| Scheduled | `every:` or `cron:` | Any node with scheduler |
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| HTTP request | `path:` | Nodes that serve API traffic|
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For example:
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- Run write-ahead log (WAL) plugins on ingester nodes.
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- Run scheduled plugins on any node configured to execute them.
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- Run HTTP-triggered plugins on querier nodes or any node that handles HTTP endpoints.
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Place all plugin files in the `--plugin-dir` directory configured for each node.
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> [!Note]
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> Triggers fail if the plugin file isn’t available on the node where it runs.
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### Route third-party clients to querier nodes
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External tools—such as Grafana, custom dashboards, or REST clients—must connect to querier nodes in your InfluxDB Enterprise deployment.
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When configuring Grafana to connect to an InfluxDB 3 Enterprise instance:
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#### Examples
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- **URL**: Use a querier URL or any node that serves queries
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- **Grafana**: When adding InfluxDB 3 as a Grafana data source, use a querier node URL, such as:
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`https://querier.example.com:8086`
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- **REST clients**: Applications using `POST /api/v3/query/sql` or similar endpoints must target a querier node.
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Example URL format: `https://querier.your-influxdb.com:8086`
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{{% /show-in %}}

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