Implementing High Availability in PostgreSQL Training Course

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

This instructor-led, live training (available online or on-site) is designed for intermediate-level database professionals and developers who aim to integrate, manage, and optimise AI capabilities directly within Postgres.

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

• Set up and configure Postgres extensions tailored for AI workloads.
• Implement embeddings and similarity search using pgvector.
• Integrate both open-source and proprietary LLMs with Postgres to deliver real-time insights.
• Optimise Postgres to efficiently handle AI-driven queries and workflows.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• To request a customised version of this training, please contact us to arrange.

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

This instructor-led, live training (delivered online or on-site) is designed for intermediate to advanced data engineers, DBAs, and solution architects who wish to design, implement, and govern enterprise-grade AI systems that leverage PostgreSQL.

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

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

Course Format

• Interactive lectures and enterprise case study discussions.
• Practical exercises and real-world lab sessions.
• Hands-on implementation within a live PostgreSQL environment.

Course Customisation Options

• To request a customised version of this training, please contact us to make arrangements.

This instructor-led, live training in New Zealand (online or on-site) is designed for database administrators and cloud architects seeking 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 select the database that best aligns with business objectives and needs.
• Prepare databases to move definitions, data, and procedures from Oracle to an Azure SQL or PostgreSQL database system.
• Execute post-migration steps to test, optimise, update, and maintain a migrated database.

This course explores the core PostgreSQL server extensions and libraries essential for embedding AI capabilities into database systems. Key topics include semantic and similarity search using vector embeddings, Text-to-SQL querying, and Retrieval-Augmented Generation (RAG). Participants will gain practical skills in installing PgVector and PgAI, generating and ingesting vector embeddings, constructing vector indexes, and implementing semantic search and RAG workflows. The curriculum also covers building Text-to-SQL applications with LangChain using Python or JavaScript. Through demonstrations and hands-on exercises, these foundational concepts and practical techniques are reinforced.

This hands-on course focuses on the practical aspects of performance tuning in PostgreSQL. Participants will learn to analyse query execution, optimise indexing, adjust memory and system parameters, and monitor workloads effectively. Real-world scenarios and live exercises demonstrate how to identify and resolve bottlenecks at both the database and system levels.

This course covers the administration and performance tuning of PostgreSQL databases. Participants will learn to utilise specialised PostgreSQL (also known as Postgres) modules, including replication, connection pooling, and full-text search.

This training is tailored for Database Administrators and Architects who wish to build a solid foundation in PostgreSQL from the ground up.

You will gain a comprehensive understanding of PostgreSQL architecture, installation procedures, database design principles, as well as best practices for backing up and recovering databases in PostgreSQL.

This training is tailored for Database Administrators and Architects seeking to master the tools and techniques required to implement backups, high availability, and database security in PostgreSQL.
You will also learn how to identify slow queries, monitor database performance, and tune PostgreSQL for optimal performance.

This training is designed for Database Administrators and Architects who wish to optimise PostgreSQL for enhanced performance. You will learn how to log slow workloads and identify potential bottlenecks in queries. The course also covers the most critical parameters that require tuning to achieve optimal performance.

In this instructor-led, live training in New Zealand (onsite or remote), participants will explore both fundamental and advanced aspects of PostgreSQL, including administration, performance tuning, advanced development, and replication. This is achieved through a series of practical, hands-on lab exercises covering setup, configuration, testing, deployment, and troubleshooting.

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

• Apply advanced administrative techniques to configure and manage a PostgreSQL server.
• Optimise databases and queries to achieve maximum performance.
• Replicate and scale a PostgreSQL server.

PostgresAI is a platform that enables database teams to clone, test, and optimise 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 optimisation.

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 optimisation and performance tuning.
• Implement governance, auditing, and data privacy controls for cloned environments.

Format of the Course

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

Course Customisation Options

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

This course provides programmatic interaction with PostgreSQL databases. Learn the techniques, syntaxes, and structures required to develop high-quality applications using a PostgreSQL backend. This training also covers SQL tuning, including best practices for writing efficient SQL queries.

The target audience includes developers who wish to use or extend PostgreSQL, as well as database architects.

This course offers comprehensive coverage of replication, high availability, and cluster management within PostgreSQL. Participants will build and manage multi-node environments, configure automated failover, and explore solutions for load balancing and connection pooling. The course features hands-on replication labs and recovery simulations.

This instructor-led, live training in New Zealand (available online or on-site) is designed for system administrators and developers who wish to leverage 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 PostgreSQL database tables and schemas.
• Learn how to perform data manipulations and queries.
• Explore the different programming interfaces (client and server) to fully utilise and extend functionalities in PostgreSQL 13.