Implementing High Availability in PostgreSQL Training Course

Postgres is an advanced open-source relational database that can serve as a foundation for AI-powered systems and data intelligence applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level database professionals and developers who wish to integrate, manage, and optimize AI capabilities directly within Postgres.

By the end of this training, participants will be able to:

• Set up and configure Postgres extensions for AI workloads.
• Implement embeddings and similarity search using pgvector.
• Integrate open source and proprietary LLMs with Postgres for real-time insights.
• Optimize Postgres for handling AI-driven queries and workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

PostgreSQL is a robust, open-source relational database that can be augmented with AI capabilities to enhance enterprise data intelligence, predictive analytics, and automation.

This instructor-led live training, available online or onsite, targets intermediate to advanced data engineers, DBAs, and solution architects seeking to design, implement, and govern enterprise-grade AI systems leveraging PostgreSQL.

Upon completing this program, participants will acquire the expertise to:

• Integrate AI models and vector search capabilities directly into PostgreSQL.
• Deploy AI-optimized architectures designed for high-volume enterprise workloads.
• Establish robust governance, auditing, and compliance frameworks for AI data pipelines.
• Securely leverage both open-source and proprietary AI frameworks within PostgreSQL environments.

Format of the Course

• Interactive lectures and enterprise case discussions.
• Practical exercises and real-world labs.
• Hands-on implementation in a live PostgreSQL environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Czech Republic (online or onsite) is designed for database administrators and cloud architects who wish to migrate Oracle databases to Azure SQL or PostgreSQL.

By the end of this training, participants will be able to:

• Compare Azure SQL with PostgreSQL to choose the database that best meets business objectives and needs.
• Prepare databases to move definitions, data, and procedures from Oracle to AzureSQL or PostgreSQL database system.
• Perform post-migration steps to test, optimize, update, and maintain a migrated database.

This course explores the essential foundations of PostgreSQL server extensions and libraries designed to incorporate AI capabilities into database systems. Key topics include similarity and semantic search utilizing embedding vectors, Text-to-SQL query formulation, and Retrieval-Augmented Generation (RAG). Participants will acquire the skills to install PgVector and PgAI, create and load vector embeddings, establish vector indexes, and execute semantic search and RAG implementations. Additionally, the curriculum covers developing Text-to-SQL applications with LangChain using Python or JavaScript. Through demonstrations and practical exercises, the core concepts and essential skills are reinforced.

This practical course centres on the real-world aspects of performance tuning within PostgreSQL. Attendees will acquire skills in analysing query execution, optimising indexing strategies, configuring memory and system parameters, and effectively monitoring workloads. Through real-world scenarios and live exercises, participants will learn to identify and resolve bottlenecks at both the database and infrastructure levels.

This course focuses on the administration and performance tuning of PostgreSQL databases. Participants will gain hands-on experience with specialized PostgreSQL (also known as Postgres) modules, including replication, connection pooling, and full-text search capabilities.

This training is tailored for Database Administrators and Architects seeking to master PostgreSQL from the ground up.

Participants will gain comprehensive knowledge of PostgreSQL architecture, installation procedures, and design principles, along with techniques for performing database backups and recovery.

This course is tailored for Database Administrators and Architects seeking to master the tools and techniques required for implementing Backups, High Availability, and Database Security within PostgreSQL.
Participants will also gain the skills to identify slow queries, monitor database performance, and optimize PostgreSQL for enhanced speed and efficiency.

Designed for Database Administrators and Architects seeking to enhance PostgreSQL performance, this training guides you through logging slow workloads and identifying query bottlenecks. Additionally, it covers the critical parameters that must be adjusted to achieve optimal performance.

In this instructor-led, live training at Czech Republic (onsite or remote), participants will explore the general and advanced aspects of PostgreSQL, including administration, performance tuning, advanced development, and replication. The course includes a series of hands-on, live-lab exercises covering setup, configuration, testing, deployment, and troubleshooting.

By the end of this training, participants will be able to:

• Use advanced administration techniques to configure and manage a PostgreSQL server.
• Optimize the database and queries for maximum performance.
• Replicate and scale a PostgreSQL server.

PostgresAI is a platform that enables database teams to clone, test, and optimize PostgreSQL environments using AI-driven automation.

This instructor-led, live training (online or onsite) is aimed at advanced-level DevOps professionals and database engineers who wish to implement PostgresAI at enterprise scale for database monitoring, cloning, and AI-driven optimization.

By the end of this training, participants will be able to:

• Deploy and configure PostgresAI in enterprise environments.
• Integrate PostgresAI with CI/CD pipelines and PostgreSQL clusters.
• Leverage AI-driven insights for query optimization and performance tuning.
• Implement governance, auditing, and data privacy controls for cloned environments.

Course Format

• Interactive lecture and discussion.
• Numerous exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This course teaches how to programmatically interact with PostgreSQL databases. It covers the techniques, syntax, and structures required to build high-quality applications using a PostgreSQL backend. The training also includes SQL Tuning, focusing on best practices for writing efficient SQL code.

The intended audience consists of developers who wish to utilize or extend PostgreSQL, as well as database architects.

This program offers comprehensive instruction on replication, high availability, and cluster management within PostgreSQL. Students will learn to construct and administer multi-node systems, set up automated failover mechanisms, and investigate options for load balancing and connection pooling. The curriculum features hands-on replication exercises and disaster recovery drills.

This instructor-led, live training in Czech Republic (online or onsite) is aimed at sysadmins and developers who wish to use PostgreSQL 13 to set up, build, and manage databases for high-performance applications.

By the end of this training, participants will be able to:

• Install and configure PostgreSQL 13.
• Understand the features, architecture, and fundamentals of operating, managing, and maintaining databases with PostgreSQL 13.
• Learn how to configure Postgres database tables and schemas.
• Learn how to perform data manipulations and queries.
• Explore the different programming interfaces (client and server) to fully utilize and extend functionalities in PostgreSQL 13.