PostgreSQL Administration, Optimization and Replication Training Course

Gain proficiency in AI integration with Postgres through this instructor-led live training in Denmark. Configure extensions, deploy pgvector embeddings, and connect LLMs for instant insights. Optimize query performance and develop intelligent systems within a hands-on live-lab setting.

This 21-hour instructor-led training in Denmark empowers data engineers and DBAs to seamlessly integrate AI models into PostgreSQL. Participants will learn to deploy optimized architectures, implement vector search, and enforce strict governance, ensuring the delivery of secure and high-performance enterprise-grade AI solutions.

This module examines the fundamentals of PostgreSQL server extensions and libraries that facilitate the integration of AI techniques into database environments. It covers similarity and semantic search using embedding vectors, Text-to-SQL queries, and Retrieval-Augmented Generation (RAG). Learners will progress through installing PgVector and PgAI, managing vector embeddings, establishing vector indexes, and executing semantic search and RAG workflows. The curriculum also includes developing Text-to-SQL applications via LangChain using Python or JavaScript, supported by live demos and practical labs to enhance both conceptual grasp and operational proficiency.

This course explores the core capabilities of PostgreSQL server extensions designed to embed AI methodologies within database architectures. A primary focus is placed on implementing similarity and semantic search using embedding vectors. Participants will acquire the skills necessary to install PgVector, process and ingest vector embeddings, establish vector indexes, and execute semantic search queries. Through a blend of live demonstrations and practical exercises, learners will solidify their grasp of both theoretical principles and hands-on technical skills.

Focused on practical application, this course delves into performance tuning strategies for PostgreSQL. It guides participants through analysing query execution, optimising indexing, and adjusting memory and system parameters to monitor workloads effectively. Live exercises and real-world case studies illustrate how to detect and resolve bottlenecks at both the database and system levels.

This course equips you with the core skills necessary to deploy, configure, and maintain PostgreSQL databases with confidence. You will master essential tasks such as securing user access, executing robust backup and restore strategies, overseeing log management, and optimizing foundational parameters. By engaging in hands-on exercises, you will apply these administrative skills to real-world scenarios while building a solid foundation for advanced concepts like performance tuning and replication.

This live, instructor-led training held in Denmark provides advanced DevOps professionals and database engineers with the skills to implement PostgresAI at scale. Through hands-on exercises in a live-lab environment, participants will gain mastery in database cloning, AI-driven query optimization, and comprehensive monitoring.

This training provides an extensive look at PostgreSQL replication, high availability, and cluster management. Participants will learn to construct and oversee multi-node setups, implement failover automation, and apply load balancing and connection pooling techniques. The curriculum features live replication labs and recovery simulations to reinforce learning.

This live, instructor-led training conducted in Denmark (either online or onsite) is tailored for intermediate-level developers and administrators looking to exploit the latest capabilities and improvements found in PostgreSQL 16.

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

• Comprehend the architecture and components of PostgreSQL 16.
• Employ advanced SQL features and PostgreSQL extensions.
• Enforce security best practices and manage access controls.
• Carry out database administration tasks, encompassing backup, recovery, and monitoring.
• Optimize database performance using tuning and indexing methods.
• Leverage PostgreSQL's internal tools for high availability and replication.
• Integrate PostgreSQL with modern application development frameworks.