KubeCon + CloudNativeCon India 2025

This session delves into the critical aspects of developing production-ready Large Language Model (LLM) applications using Java. We'll explore how to leverage Java's strengths to build scalable and efficient LLM systems, addressing key challenges such as performance optimization, resource management, and seamless integration with existing infrastructures.

Attendees will gain practical knowledge on handling massive datasets, optimizing model inference, and fine-tuning LLMs for optimal performance. We'll discuss strategies for ensuring the reliability and scalability of your LLM deployments, empowering you to create robust and high-performing AI applications. Whether you're a seasoned Java developer or new to the AI domain, this session will provide valuable insights and guidance for your LLM development journey, equipping you with the tools and knowledge to navigate the complexities of building production-grade LLM systems.

Kubernetes Operators are revolutionasing cloud-native application management—but when designing an operator, should we go one CRD per operator or manage multiple CRDs within a single operator? How does cascading CRDs impact reconciliation, dependency handling, and performance?

In this talk, we'll dive deep into real-world use cases to explore the trade-offs between these approaches. Whether we are building custom Kubernetes controllers or optimising cloud-native infrastructure, this session will help one make the right design choice for scalability, maintainability, and performance.

Kubernetes-native development is exhilarating—until complex workflows, slow feedback loops, and steep learning curves slow you down. Teams often spend days or weeks setting up environments, managing dependencies, and debugging microservices. GitLab found that nearly 44% of organizations take over two months to onboard new developers—precious time lost in today’s fast-paced tech world.
This session shows how we cut environment setup from days to minutes, slashed feedback loops by over 90%, and reduced onboarding time by 50%.
The secret? A powerful blend of CNCF tools—Kind and DevSpace—combined with simple lightweight Node.js and Bash/PowerShell scripts, We have automated environment provisioning, code synchronization, and cluster management so that developers can focus on shipping features.
Discover how to integrate Kind and DevSpace for a seamless workflow with real metrics and tips. Developers, architects, and DevOps can streamline Kubernetes, speed onboarding, and boost iterations.