Uploaded February 2026 | Updated September 2026, 3 weeks ago
Painful days spent optimizing the wrong part of a flow. Repeated attempts to blindly fix a performance issue. Speculative micro-"optimizations" that clutter the code with no measurable benefit. Only to later trace the problem to the most unexpected cause. This talk explains how to correctly zoom in on a performance bottleneck using distributed tracing, metrics, and method profiling. We learn to read a flame graph, then we review a series of bottlenecks typical for backend systems, like connection pool starvation, time-consuming Aspects, network calls, CPU hotpoints, lock contention, and Virtual Thread pinning. Join this session and prepare for the performance issues that any successful system will eventually have.
Painful days spent optimizing the wrong part of a flow. Repeated attempts to blindly fix a performance issue. Speculative micro-"optimizations" that clutter the code with no measurable benefit. Only to later trace the problem to the most unexpected cause. This talk explains how to correctly zoom in on a performance bottleneck using distributed tracing, metrics, and method profiling. We learn to read a flame graph, then we review a series of bottlenecks typical for backend systems, like connection pool starvation, time-consuming Aspects, network calls, CPU hotpoints, lock contention, and Virtual Thread pinning. Join this session and prepare for the performance issues that any successful system will eventually have.
![[VDBUH2026] Brian Vermeer - Breaching LLM-Powered Apps: Overcoming Security and Privacy Challenges](https://i.ytimg.com/vi/iU0ytnOo6Qw/mqdefault.jpg "[VDBUH2026] Brian Vermeer - Breaching LLM-Powered Apps: Overcoming Security and Privacy Challenges
LLMs accessing the database and intelligent agents that perform online purchases? The possibilities for AI in applications seem endless but so are their security and data privacy risks. In this session, we’ll address common issues such as prompt injection, key leakage, abuse of private customer data for model training, legal restrictions, and more. In addition, we will show that general security issues in your systems can also influence the behavior and outcome of LLMs.
During this session, you’ll get a solid overview of the vulnerabilities to avoid, strategies to ensure data privacy compliance and best practices for building secure LLM-powered applications.")
![[VDBUH2026] Alexander Chatzizacharias: How to build your own fun and absurd pair programmer](https://i.ytimg.com/vi/jnPtYh-n0LM/mqdefault.jpg "[VDBUH2026] Alexander Chatzizacharias: How to build your own fun and absurd pair programmer
Tired of AI assistants that are always so boring and soulless? Alexander was. So, he decided to build his own. An AI assistant with personality, flair, and a healthy dose of sarcasm. Imagine a pair programmer that offers sarcastic feedback, makes absurd suggestions, and threatens to blow up your code when it disagrees with your changes. And when things get too quiet, it might even challenge you to a game of tic-tac-toe.
This session is for anyone who believes the best way to learn new technologies is by playfully breaking them. If you’re curious about LLMs and agents beyond the typical use cases, this talk is for you. You’ll leave with practical insights into building your own agentic LLM workflows using Spring Boot, vector databases, and locally running models. Alexander will talk about Retrieval-Augmented Generation (RAG) flows that feed LLMs the right context, multi-vector search for fast context retrieval, and Model Context Protocol (MCP) integrations that let the assistant directly meddle with your file system.
Come to learn, chuckle, and get inspired to create your own dysfunctional digital sidekick.")
