Installing and Removing the ClickHouse DBMS

Preparing SSL Certificate and Private Key for ClickHouse DBMS Server

Running Docker Service with ClickHouse DBMS

Environment Variables

Connecting the Operavix Server to the ClickHouse Analytical DBMS

Removing ClickHouse DBMS

# Installing and Removing the ClickHouse DBMS

To install or remove ClickHouse on a Linux server via Docker, you must prepare the environment in accordance with system requirements.

For recommendations on system requirements, refer to the [Technical Requirements for Server and Hardware Equipment](../1.General/6.Technical_requirements.md) page.

## Preparing SSL Certificate and Private Key for ClickHouse DBMS Server

Before installing and launching ClickHouse, you must ensure secure connection between client applications and the DBMS.

For instructions on preparing an SSL certificate and privat key to enable secure HTTPS connections with the ClickHouse server, see: [Preparing a Certificate and Private Key for the ClickHouse DBMS Server#Preparing a Certificate and Private Key for the ClickHouse DBMS Server](../6.quick_start/3.quick_installation_server.md).

## Running Docker Service with ClickHouse DBMS

Once the SSL certificates are ready, proceed with installing the ClickHouse DBMS in a Docker container.

The step-by-step process for launching the ClickHouse Docker service is provided here: [Starting the ClickHouse DBMS Docker Service#Starting the ClickHouse DBMS Docker Service](../6.quick_start/3.quick_installation_server.md).

### Environment Variables

When launching the container, you can pass environment variables that modify configuration files of the application. The available parameters are presented in the table below.

| **Parameter** | **Value** | **Description** |
|---|---|---|
| `APP_USER_ACCESS_MANAGEMENT` | `0` or `1` Default: `0` | Disallows/allows ClickHouse administrator to create additional users and manage access rights via SQL queries|
| `LIMIT_MEMORY` | Default: `0.9` (90%) | The coefficient of maximum memory consumption by the server for processing all SQL queries|
| `PROMETHEUS`| `true` or `false` Default: `false` | Enables the transmission of metrics for Prometheus. To ensure proper operation, it is necessary to open port 9363 in the container. To do this, add the following to the service launch command: `--publish published=9363,target=9363` |
|`SIZE_LOG_FILE`|Log size in megabytes. Default is `1000` (1 GB)|Size of technical logs *clickhouse-server.log* and *clickhouse-server.err.log*|
|`COUNT_LOG_FILE`|Default is `10`|Number of retained technical log files|

You can find more detailed information about Prometheus in the [ClickHouse documentation](https://clickhouse.com/docs/operations/server-configuration-parameters/settings).

## Connecting the Operavix Server to the ClickHouse Analytical DBMS

After installing ClickHouse DBMS and the Operavix application, you must configure a connection between them so that Operavix can use the DBMS for creating reports, executing SQL queries, and analytics.

This section explains how to correctly specify connection parameters to ensure stable and secure data exchange between system components: [Connecting the Operavix Server to the ClickHouse Analytical DBMS#Connecting the Operavix Server to the ClickHouse Analytical DBMS](../6.quick_start/3.quick_installation_server.md).

## Removing ClickHouse DBMS

When ClickHouse is no longer needed or requires reinstallation, you must properly remove all components: the service, secrets, volumes, and Docker cluster configuration.

To remove ClickHouse DBMS, execute the following commands on the server where it is installed:

```
# docker service rm operavix-clickhouse
```

```
# docker secret rm operavix_app_user operavix_app_user_password_hash operavix_clickhouse.crt operavix_clickhouse.key operavix_clickhouse_dhparam.pem operavix_external_user operavix_external_user_password_hash
```

```
# docker volume rm operavix-clickhouse operavix-clickhouse-log
```

```
# docker swarm leave –force
```

You can find the commands to remove Docker for a specific Linux distribution in the [official documentation](https://docs.docker.com/engine/install/).

Updating the ClickHouse DBMS

Differences Between Operavix on Linux and Windows Operating Systems

What Is Operavix

Quick Installation of the Operavix Server Component

Monitoring Agent

JS Tracker (Customer Journey Tracking)

Quick Installation

Quick System Setup

Building a Custom Dashboard

Template-Based Reports for Data Analysis

First Dashboard

What’s Next?

Quick Start 

Functional Architecture

Network Interaction of System Components

Description of the System Functioning

System Integration with External Automated Systems

Technical Requirements for Server and Hardware Equipment

Architectural Scheme of the Operavix Application

Network Scheme of the Operavix Application

Glossary

Description of the Operavix System 

Installing, Configuring, and Removing the Operavix Application on Windows

Installing the Operavix Application on Linux

Updating Operavix on Windows

Updating Operavix on Linux

Updating Operavix

Cluster Mode Setup

Migrating the Operavix Server from Windows to Linux

Installing the Automation Module on a Separate Server

Installing and Running the AI Agent

Installing and Running the Webhook Agent

Instructions for Installing, Updating, and Removing the System

License Key

Beta Version Functionality

System Licensing

Working with Databases

Working with the System

System Configuration Files

Prometheus Metrics

Access Roles

Working with GraphQL

Managing System Users

System Emails to Users

Embedding Operavix Dashboards

Administration 

Connecting the Application to the ClickHouse Analytical DBMS

Creating User Accounts in ClickHouse

Setting up a ClickHouse DBMS Cluster in Docker with Replication Support

ClickHouse 

User Data Collection by Monitoring Agent

Obtaining The Monitoring Agent Distribution

Monitoring Agent Configurator

Installing, Updating, and Removing the Monitoring Agent on Windows

Installing, Updating, and Removing the Monitoring Agent on Linux

Starting and Stopping the Monitoring Agent

Managing the Monitoring Agent

Monitoring Logs

Storing Monitoring Agent Logs

Collecting Screenshots with the Monitoring Agent

Export and Import of User Activity

Activity Archiving

Working with Damaged Monitoring Archives

Data Storage Structure in ClickHouse

Monitoring 

Signing In to the System

How to Recover Your Password

Home Page

Filtering

Navigation in the System

Workspaces

Personal Profile

System Settings

Users

Departments

Bulk Actions

Adding API Keys

Keytab File Creation for the Kerberos Authentication in Active Directory

Configuring Authentication Using OpenID Connect and Keycloak

Configuring SAML Authentication in Keycloak

Adding Authentication

About the system

The Monitoring Section

The Connections Section

Data Storages

System Tables

System Settings 

Automation Agents

Execution Log

Control Panel

Configuring an SMB Connection

Connections

Automation Blocks

Trigger Blocks

Working with Files

Working with Services

Working with LLM

Tools

Event Processing

Editing a Script

Query and Code Editor

Script Testing and Publishing

Running a Script

Script Example

Automation 

Custom Integrations 

System Events

JS Tracker 

Access Settings for Workspaces

Adding and Configuring Tables

Replacing Tables

Adding and Configuring Processes

Global Workspace Indicators

Display Rules

Configuring the Data Model

Packages

General

Configuring Access to Dashboards

Click to Filter

Table Report Export

Browse mode

Edit Mode

Views

Dimensions and Measures

Widget Basic Settings

Widget Display Settings

Widget Filtering Settings

Widget List

Widgets

Sorting

Markdown Usage Rules

Variables

Global Dashboard Indicators

Running Script from Dashboard

Go to URL

Run Script

Open View

Update Variable

Click Actions

Input Methods

Displaying Monitoring Screenshots in a Dashboard

Formula Editor

Functions for Formulas

The process Function

View Configuration in YAML

Widget Configuration in YAML

Dimensions and Measures in YAML

Process-Based Dimensions and Measures in YAML

Data Formats and Formatting in YAML

YAML Editor

Dashboards

Report Example

Business Intelligence 

OperavixAI

Package Creation Guide

Marketplace 

Template-Based Dashboards

Configuring Depersonalization Of User Data When Deleted In AD

Activating LDAPS

Synchronized Attributes Between the System and AD

Getting Information About AD Security Groups Using A GraphQL Request

Configuring User Synchronization with Active Directory

User Synchronization 

Audit Mechanism Description

System Status Monitoring

Implemented Information Security Protection Measures in the System

Audit Logs

Docker Containers

Mutual Authentication Between Application Server and ClickHouse

For Security Administrator 

Known Issues

Known Issues and Limitations 

Frequently Asked Questions

Parameter	Value	Description
`APP_USER_ACCESS_MANAGEMENT`	`0` or `1` Default: `0`	Disallows/allows ClickHouse administrator to create additional users and manage access rights via SQL queries
`LIMIT_MEMORY`	Default: `0.9` (90%)	The coefficient of maximum memory consumption by the server for processing all SQL queries
`PROMETHEUS`	`true` or `false` Default: `false`	Enables the transmission of metrics for Prometheus. To ensure proper operation, it is necessary to open port 9363 in the container. To do this, add the following to the service launch command: `--publish published=9363,target=9363`
`SIZE_LOG_FILE`	Log size in megabytes. Default is `1000` (1 GB)	Size of technical logs clickhouse-server.log and clickhouse-server.err.log
`COUNT_LOG_FILE`	Default is `10`	Number of retained technical log files