Description

Introduction

The MariaDB Advanced Technologies & Cloud Platforms training course explores advanced MariaDB capabilities and modern database deployment environments. Participants learn advanced database architecture, distributed database technologies, cloud deployment, containerization, database integration, and enterprise data management.

The course covers cloud-based MariaDB solutions, Kubernetes deployments, database migration, automation, monitoring, and advanced security. Hands-on exercises help participants build, deploy, integrate, and manage MariaDB environments across modern infrastructure platforms.

Prerequisites

1. Basic knowledge of MariaDB or MySQL.

2. Understanding of SQL and relational database concepts.

3. Familiarity with database administration and configuration.

4. Basic knowledge of Linux commands.

5. Understanding of networking and client-server architecture.

6. Familiarity with cloud computing concepts is helpful.

7. Basic knowledge of containers and scripting is beneficial.

Estimated Duration

1. Beginner Level: 3 days (18–20 hours)

2. Intermediate Level: 5 days (30–35 hours)

3. Advanced Level: 7 days (40–45 hours)

4. Enterprise Level: 10 days (50–60 hours)

Training Lab Setup Specifications

1. Operating System: Windows 10/11, Ubuntu 22.04 LTS, or an equivalent Linux distribution.

2. Database Server: MariaDB 10.6 or later.

3. Database Tools: MariaDB command-line client, DBeaver, or HeidiSQL.

4. Hardware: Minimum 4 CPU cores and 8 GB RAM; 16 GB RAM recommended.

5. Storage: Minimum 40 GB available disk space.

6. Network: Stable internet connection for cloud access, package downloads, and documentation.

7. Container Tools: Docker Desktop or Docker Engine.

8. Orchestration Tools: Kubernetes environment such as Minikube or a suitable managed cluster.

9. Cloud Platform: Access to a cloud account or sandbox environment for deployment exercises.

10. Development Tools: Git, a code editor, and scripting tools.

11. Privileges: Administrative access for installation, configuration, and deployment.

12. Practice Environment: Multiple MariaDB instances, sample databases, and test application workloads.

TABLE OF CONTENTS

Module 1: Advanced MariaDB Architecture and Technologies

1.1 Advanced MariaDB Architecture

1.1.1 MariaDB Enterprise Architecture Overview
1.1.2 Understanding Advanced Database Components
1.1.3 Storage Engine Architecture and Selection
1.1.4 Managing Distributed Database Environments

1.2 MariaDB Enterprise Platform

1.2.1 Introduction to MariaDB Enterprise Platform
1.2.2 MariaDB Enterprise Server Features
1.2.3 Understanding Enterprise Database Components
1.2.4 Integrating MariaDB Enterprise Services

1.3 Advanced Database Technologies

1.3.1 Understanding Distributed Database Concepts
1.3.2 Managing Large-Scale Database Workloads
1.3.3 Working with Advanced Data Processing
1.3.4 Exploring Modern Database Capabilities

Module 2: MariaDB ColumnStore and Advanced Analytics

2.1 Introduction to MariaDB ColumnStore

2.1.1 Understanding Columnar Database Architecture
2.1.2 Comparing Row-Based and Columnar Storage
2.1.3 Exploring ColumnStore Features
2.1.4 Understanding Analytical Database Workloads

2.2 ColumnStore Installation and Configuration

2.2.1 Installing MariaDB ColumnStore
2.2.2 Configuring ColumnStore Components
2.2.3 Managing Storage and Data Distribution
2.2.4 Monitoring ColumnStore Services

2.3 Analytical Query Processing

2.3.1 Working with Analytical SQL Queries
2.3.2 Managing Large Data Volumes
2.3.3 Optimizing Analytical Query Execution
2.3.4 Analyzing Data Processing Performance

2.4 Enterprise Analytics and Data Integration

2.4.1 Integrating ColumnStore with MariaDB Server
2.4.2 Managing Analytical Data Workloads
2.4.3 Working with External Data Sources
2.4.4 Applying Data Warehousing Concepts

Module 3: MariaDB MaxScale and Advanced Database Routing

3.1 Introduction to MariaDB MaxScale

3.1.1 Understanding MaxScale Architecture
3.1.2 Exploring MaxScale Components
3.1.3 Understanding Database Proxy Functionality
3.1.4 Installing and Configuring MaxScale

3.2 Query Routing and Load Balancing

3.2.1 Configuring Read and Write Splitting
3.2.2 Managing Query Routing Rules
3.2.3 Configuring Load Balancing
3.2.4 Managing Database Connections

3.3 High Availability with MaxScale

3.3.1 Integrating MaxScale with Replication
3.3.2 Configuring Automatic Failover
3.3.3 Managing Database Server Monitoring
3.3.4 Testing High Availability Configurations

3.4 MaxScale Security and Administration

3.4.1 Configuring Authentication and Authorization
3.4.2 Managing Secure Database Connections
3.4.3 Monitoring MaxScale Operations
3.4.4 Troubleshooting Routing and Connectivity Issues

Module 4: MariaDB Cloud Platforms and Deployment

4.1 Introduction to MariaDB Cloud

4.1.1 Understanding Cloud Database Architecture
4.1.2 Exploring MariaDB Cloud Services
4.1.3 Comparing Managed and Self-Managed Databases
4.1.4 Understanding Cloud Deployment Models

4.2 MariaDB Cloud Deployment

4.2.1 Creating and Configuring Cloud Database Services
4.2.2 Deploying MariaDB on AWS
4.2.3 Deploying MariaDB on Microsoft Azure
4.2.4 Deploying MariaDB on Google Cloud

4.3 Cloud Database Management

4.3.1 Managing Cloud Database Instances
4.3.2 Configuring Cloud Database Connectivity
4.3.3 Managing Cloud Storage and Scaling
4.3.4 Monitoring Cloud Database Performance

4.4 Cloud Security and Availability

4.4.1 Configuring Cloud Database Access
4.4.2 Managing Encryption and Network Security
4.4.3 Configuring Cloud Backup and Recovery
4.4.4 Managing Cloud Database Availability

Module 5: Containerization and Kubernetes Deployment

5.1 MariaDB with Docker

5.1.1 Understanding Containerization Concepts
5.1.2 Installing Docker and MariaDB Images
5.1.3 Creating and Managing MariaDB Containers
5.1.4 Configuring Container Storage and Networking

5.2 MariaDB on Kubernetes

5.2.1 Understanding Kubernetes Architecture
5.2.2 Deploying MariaDB on Kubernetes
5.2.3 Managing Pods, Services, and Persistent Volumes
5.2.4 Configuring MariaDB Kubernetes Operators

5.3 Container Management and Scaling

5.3.1 Managing Container Resources
5.3.2 Configuring Database Replication in Containers
5.3.3 Scaling MariaDB Deployments
5.3.4 Monitoring Containerized Database Services

5.4 Cloud-Native Database Operations

5.4.1 Managing Database Configuration and Secrets
5.4.2 Implementing Persistent Database Storage
5.4.3 Automating Container Deployment
5.4.4 Troubleshooting Kubernetes Database Environments

Module 6: MariaDB Connectors and Application Integration

6.1 MariaDB Connector Fundamentals

6.1.1 Understanding MariaDB Connector Architecture
6.1.2 Selecting Appropriate Database Connectors
6.1.3 Configuring Database Connection Parameters
6.1.4 Managing Connection Security

6.2 Application Development Integration

6.2.1 Connecting Applications Using Python
6.2.2 Integrating MariaDB with Java Applications
6.2.3 Connecting Node.js Applications
6.2.4 Working with PHP and MariaDB

6.3 Advanced Database Connectivity

6.3.1 Managing Connection Pools
6.3.2 Configuring Secure Application Connections
6.3.3 Handling Database Transactions
6.3.4 Managing Connection Errors and Timeouts

6.4 Enterprise Application Integration

6.4.1 Integrating MariaDB with Enterprise Applications
6.4.2 Connecting MariaDB with REST APIs
6.4.3 Managing Data Exchange Between Systems
6.4.4 Applying Application Integration Best Practices

Module 7: Database Migration, Automation and DevOps

7.1 Advanced Database Migration

7.1.1 Planning Database Migration Projects
7.1.2 Migrating Data from MySQL to MariaDB
7.1.3 Migrating Data from Other Database Platforms
7.1.4 Validating Migrated Database Environments

7.2 Database Automation

7.2.1 Automating Database Deployment
7.2.2 Managing Database Configuration with Scripts
7.2.3 Scheduling Database Administration Tasks
7.2.4 Automating Backup and Monitoring Operations

7.3 DevOps and CI/CD Integration

7.3.1 Understanding Database DevOps Practices
7.3.2 Managing Database Changes with Version Control
7.3.3 Integrating Database Operations into CI/CD Pipelines
7.3.4 Automating Database Testing and Deployment

7.4 Infrastructure as Code

7.4.1 Understanding Infrastructure as Code Concepts
7.4.2 Deploying MariaDB with Terraform
7.4.3 Managing Configuration with Ansible
7.4.4 Maintaining Consistent Database Environments

Module 8: Advanced Security, Monitoring and AI Integration

8.1 Enterprise Database Security

8.1.1 Managing Advanced Authentication
8.1.2 Configuring Role-Based Access Control
8.1.3 Implementing Encryption and Secure Connectivity
8.1.4 Managing Security Auditing and Compliance

8.2 Advanced Monitoring and Observability

8.2.1 Monitoring Database Health and Performance
8.2.2 Managing Centralized Database Logs
8.2.3 Configuring Alerts and Performance Reports
8.2.4 Monitoring Enterprise Database Environments

8.3 Modern Data and AI Integration

8.3.1 Understanding Vector Data and Search Concepts
8.3.2 Exploring MariaDB AI and RAG Capabilities
8.3.3 Integrating Database Services with AI Applications
8.3.4 Managing Data Access for AI Workloads

8.4 Enterprise Operations and Governance

8.4.1 Managing Database Configuration Standards
8.4.2 Planning Enterprise Database Capacity
8.4.3 Applying Data Governance Practices
8.4.4 Maintaining Enterprise Database Reliability

Module 9: Practical Labs and Capstone Project

9.1 Advanced Technologies Lab

9.1.1 Configuring MariaDB Enterprise Components
9.1.2 Exploring ColumnStore and Analytical Queries
9.1.3 Configuring MaxScale and Query Routing
9.1.4 Monitoring Advanced Database Workloads

9.2 Cloud and Container Deployment Lab

9.2.1 Deploying MariaDB on a Cloud Platform
9.2.2 Creating MariaDB Docker Containers
9.2.3 Deploying MariaDB on Kubernetes
9.2.4 Configuring Cloud Database Security

9.3 Integration and Automation Lab

9.3.1 Connecting Applications with MariaDB
9.3.2 Automating Database Deployment
9.3.3 Implementing CI/CD Database Workflows
9.3.4 Testing Database Migration Procedures

9.4 Capstone Project

9.4.1 Designing an Enterprise MariaDB Architecture
9.4.2 Deploying MariaDB in a Cloud Environment
9.4.3 Integrating Advanced Database Technologies
9.4.4 Implementing Security and Monitoring
9.4.5 Presenting the Enterprise Database Solution

Conclusion

This training provides advanced knowledge of MariaDB technologies and cloud-based database environments. Participants gain practical experience with ColumnStore, MaxScale, cloud deployment, containers, Kubernetes, application connectors, automation, and modern data integration. The course prepares database professionals to design, deploy, integrate, and manage scalable MariaDB solutions for enterprise workloads.

https://locusit.com/academy/

https://mariadb.com/docs/mariadb-cloud