Constant-Time Aggregations with Star-Tree in OpenSearch
Discover how OpenSearch breaks linear scaling. Inspired by Apache Pinot, the Star-Tree index moves performance dependency from document count to field cardinality. Learn how we extended Lucene’s DocValues to build multi-dimensional materialized views that deliver sub-second analytics on billion-scale datasets for observability workloads.
10x CouchDB Performance Gains for a AAA Game Launch
All software benchmarks and claims of performance are carefully crafted lies and this talk is no different. Instead of giving you a quick “do steps one, two, three for a magic speedup”, we aim to explain how we arrived at the changes we made and how we rigorously tested those changes to make sure we understand their impact.
Streamling: Lightweight, Extensible Streaming on DataFusion
Apache DataFusion is moving beyond batch into streaming. We built Streamling, a Rust streaming engine that uses DataFusion planning and Arrow RecordBatch streams for real-time SQL/WASM transforms. This talk covers how we built it, highlights key features (FFI plugins, WASM transforms, and dynamic tables), and shares production lessons.
When better retrieval makes agents worse
Agentic systems can break not because information is missing, but because persuasively wrong context gets promoted into action. We examine a recurring pattern: retrieval metrics improve while agent behavior degrades as distractors enter multi-step loops. We show why relevance, reliability, and security are tightly connected in agentic retrieval.
Let LLMs Wander: Engineering RL Environments
What if, instead of learning only from examples, Language Models could explore crafted Environments, little worlds where they can act and improve autonomously?
Join me to see how Reinforcement Learning Environments work, how to build them with open-source tools, and how to use them to evaluate and train LLMs/Agents.
Zero downtime index upgrade in Apache Solr
In this talk we’ll explore how Apache Solr introduced the capability to upgrade an index in-place with zero downtime. This upgrade path helps prepare the index for a future Solr major version upgrade without needing to recreate the index from source as is the case with Lucene based search engines today.
Building a Local News RAG: The Quest for Trustworthiness
We will show you how we build a local newspaper rag and all the problems that came along the way. From trustworthiness to customer wishes, search optimization and generation problems. Local villages, that LLMs know nothing about, content that is semantically the same and outdated information are only a part of the journey we made.
No 0-day required, just target the AI coding assistant!
Discover how attackers can manipulate AI coding assistants through hidden text, typosquatting and code errors. Learn to detect concealed instructions and set up trusted dependencies to keep unsafe code out of your environment.
Ultraviolet: Turn Hidden Document Data into an AI Advantage
Every PDF hides a world of structure, metadata and embedded signals that can silently influence AI based processing. With ultraviolets, we reveal how those can be exploited for malicious purposes and even become powerful tools for smarter applications. Designing for both humans and machines become a vital aspect of AI experience design.
One GPU, Four Retrieval Modes: Multi-Model Search Serving
Competitive search now needs dense embeddings, sparse vectors, ColBERT, and cross-encoder reranking. Most teams run four separate containers. This talk shows how to serve all four from one process, walks through building a hybrid retrieval pipeline with real benchmark data, and covers where each retrieval mode wins and where it wastes compute.