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Build Enterprise Worthy LLM Inference with Open Source and Kubernetes

Event artwork for Build Enterprise Worthy LLM Inference with Open Source and Kubernetes

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About this event

What to expect

Enterprise LLM deployment demands robust infrastructure, production-ready tooling, and deep understanding of scalability challenges — this comprehensive online masterclass cuts through the complexity to show you exactly how to build inference systems that can handle real-world workloads. Whether you're architecting AI platforms for large organisations or scaling machine learning systems, this session delivers the practical knowledge you need to deploy large language models with confidence.

This hands-on workshop focuses on production-grade LLM inference using open-source technologies and Kubernetes orchestration. You'll learn how to architect scalable inference pipelines that meet enterprise requirements for reliability, security, and performance. The session covers model serving frameworks, resource optimisation, load balancing strategies, and monitoring approaches that work at scale.

What You'll Master

  • Building production LLM inference infrastructure using Kubernetes and open-source tools
  • Implementing efficient model serving with resource constraints and cost considerations
  • Designing for high availability, fault tolerance, and horizontal scaling
  • Monitoring and observability patterns for LLM inference workloads
  • Security and governance practices for enterprise AI deployments
  • Real-world architectural patterns from production systems

This masterclass targets senior engineers, technical leads, and architects responsible for building or maintaining AI infrastructure. You should have working knowledge of Kubernetes fundamentals and containerisation, along with basic understanding of machine learning deployment challenges. The session emphasises practical, battle-tested approaches over theoretical concepts.

Hosted by The Principal Dev, this workshop brings together expertise in distributed systems, cloud architecture, and production machine learning. The format combines technical deep-dives with hands-on demonstrations, giving you actionable patterns you can immediately apply to your own infrastructure projects.

The online format makes this accessible regardless of your location, with interactive components that let you engage directly with the material and ask questions specific to your deployment scenarios. You'll walk away with architectural blueprints, configuration examples, and a clear roadmap for building LLM inference systems that can scale from prototype to production.

[Register for this masterclass](https:

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