Voxxed Days CERN 2026
2026-02-10
Meyrin (Geneva), Switzerland
[Voxxed Days CERN 2017, Voxxed Days CERN 2019, Voxxed Days CERN 2025, Voxxed Days CERN 2026]
who it's for
java developers, platform engineers, data engineers, machine learning engineers, site reliability engineers, frontend developers, security engineers, engineering managers
topics
advanced TypeScript mapped types; billion-scale vector search; UI code mods with JSCodeShift; JVM low-latency trading techniques; streaming data privacy with Kafka and Flink; JPA performance pitfalls; TornadoVM GPU acceleration for Java; Project Leyden AOT startup caching; semantic search with embeddings; Spring Boot observability stack; Kubernetes resource optimization; chaos engineering game days
| title | author | length |
|---|---|---|
| A Deep Dive Into Advanced TypeScript - A Live Coding Expedition | Christian Wörz | 44m |
Live-coding shows concrete TypeScript patterns: a mapped type that generates onAdd/onRemove handlers from an events union using template literals and the… | ||
| Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch | Pietro Mele | 45m |
Managing 1 billion embeddings in Elasticsearch and OpenSearch requires concrete tradeoffs: GPU + NVIDIA Cagra speeds up index building but a naive float32 ANN… | ||
| Compilers, User Interfaces & the Rest of Us | Matheus Albuquerque | 46m |
Claim: modern UI compilers and static analysis already rewrite how front ends are changed and optimized. Examples: using JSCodeShift/AST grep and code mods to… | ||
| Help! My manager is asking me for KPIs ! | geoffrey graveaud | 44m |
Three real cases: a top‑down mandate for 80% code coverage, a subsidiary told to hit 200 velocity points, and a push to adopt DORA metrics (lead time for… | ||
| High-Speed Crypto Trading: JVM Techniques Behind Bitvavo’s µs Revolution | Oleg Lobanov, Marcos Maia | 49m |
Rebuild uses a deterministic replicated-state-machine on JVM with Raft, Aeron for reliable UDP + SBE + zero-copy transport, and strict zero-allocation code… | ||
| Keeping data private in real-time pipelines | Olena Kutsenko | 33m |
Practical pipeline patterns for keeping streaming data useful while preventing reidentification using Apache Kafka and Apache Flink with Iceberg storage… | ||
| A Beginner’s Guide to Semantic Search | Pietro Mele | 13m |
Compares classic TF-IDF and BM25 lexical search with dense neural embeddings and shows concrete tradeoffs: lexical can be tuned but fails on vocabulary… | ||
| When ORM Becomes OMG: Performance Pitfalls in JPA and Friends | Jos Roseboom | 45m |
A sample app FunFactStore uses Postgres, Java 25, Spring Boot 4, Spring Data JPA and Hikari to show concrete pitfalls: connection pooling is ~1000x faster than… | ||
| TornadoVM: Supercharge your Java with GPU acceleration | Christos Kotselidis, Mary Xekalaki | 46m |
TornadoVM is a Java JDK plugin (current release 2.2.0) that compiles and offloads Java kernels to GPUs via OpenCL CUDA SPIR-V (Metal in progress), automates… | ||
| The Room of Requirements for Developers: Scaling AI Magic with Internal Portals | Maarten Vandeperre | 48m |
Shows that a developer portal (Backstage with dynamic plugins) plus YAML blueprints actually spins up a sovereign chatbot in minutes: the demo scaffolds source… | ||
| Supercharge your JVM performance with Project Leyden and Spring Boot | Moritz Halbritter | 45m |
Project Leyden features in Java 25 via an AOT cache that records a training run (XXAOT mode record / XXAOT cache output) and speeds startup by preloading class… | ||
| Training My Rival in Java: A Deep Q-Learning AI to Play Azul | Victor Uria Valle | 17m |
Built a Deep Q-Network in Java (no PyTorch or TensorFlow) that encodes Azul state and actions (factories or center, color, target row, wall, pattern lines… | ||
| The developer's guide to making money in the open source galaxy | Ronald Dehuysser | 43m |
JobRunr starts as a Java port of Hangfire and becomes a DB-backed job store with a tiny jar, dashboard, Kubernetes-friendly servers polling the database, and… | ||
| TDD makes you a better everyday developer | Jesse Kershaw | 45m |
Demonstrates TDD as the red–green–refactor loop with a live IntelliJ demo that creates a Greeter class, writes JUnit asserts, then refactors; claims it… | ||
| Spring Boot Observability in Practice: Actuator, Micrometer & OpenTelemetry | Patrick Baumgartner | 47m |
Shows concrete Spring Boot wiring: Actuator endpoints (can run on a separate port with liveness/readiness probes), Micrometer meterRegistry with… | ||
| Streams – Below the Surface | Cay Horstmann, Maurice Naftalin | 47m |
Explains how Java Streams build a pipeline from spliterator through intermediate ops to a terminal op, why Gatherers (Java 23) let you write custom… | ||
| Rethinking Full Stack Application Development with Kiro | Alessandra Pasini, Romain Jourdan | 46m |
Kiro claims to turn a marketplace prototype (React Next.js frontend, Spring Boot Java 25 backend, images in S3) into a production-ready feature by iterating… | ||
| RamaLama: Making working with AI Models Boring | Cedric Clyburn | 47m |
RamaLama packages open-source LLMs into reproducible containers using Podman or Docker, pulls models from Ollama, Hugging Face or OCI, and runs llama.cpp or… | ||
| Plan for Unplanned Work: Game Days with Chaos Engineering | Daniel Afonso | 42m |
Explains how PagerDuty runs controlled chaos engineering as scheduled failure Fridays (now “failure any days”), injecting real-world variables like killed… | ||
| Optimizing Resource Usage in Kubernetes | Carlos Sanchez | 39m |
Adobe Experience Manager runs >70 clusters with 17,000 customer environments, ~200,000 deployments and ~18,000 namespaces and uses standard Kubernetes plus… | ||
| One AI Chat to Rule Them All: Connecting Enterprise Tools with MCP | Karthik Sayapparaju | 16m |
Demonstrates an on‑prem AI integration using the Model Context Protocol (open‑sourced by Anthropic Nov 2024 and donated to the Linux Foundation with… | ||
| MCP at the LHC: Coordinating the World’s Largest Machine | Georg Šumailov | 13m |
Prototype MCP server connects MS Project via the scheduling backend to an on‑prem LLM and returns conflict analyses rather than raw tables, shaving context by… | ||
| Be more productive with IntelliJ IDEA | Marit van Dijk | 44m |
Live demo shows IntelliJ creating a Spring Boot project, editing Java that reads lines from a file and refactors it into a try‑with‑resources with streams, and… | ||
| LLMs can't optimize schedules, but AI can! | Tom Cools | 45m |
Argues LLMs fail at combinatorial planning (30 employees → 150 shifts, search space ~30^150) and shows a working alternative: metaheuristics via the Java… | ||
| The Past, Present and Future of Programming Languages | Kevlin Henney | 52m |
Main claim: mainstream languages change slowly — the top five unchanged for six years across TIOBE/RedMonk/IEEE, with Python roughly ten times the use of many… | ||
| How we rebuild a legacy monolithic platform at CERN and still sleep at night | Dmitry Kekelidze | 45m |
A 30-year Java monolith that runs HR, finance and operations migrates by forking the repo and incrementally extracting a fork-and-refactor core into versioned… | ||
| Are We Ready For The Next Cyber Security Crisis Like Log4Shell? | Soroosh Khodami | 47m |
A live demo shows a malicious Gson package and a crafted npm release cause a reverse shell during Maven and npm installs, giving interactive access to a VPS… | ||
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