MEET OUR SPEAKERS

Jorge is a Global Senior Solutions Architect for AWS Energy. With two decades of experience in enterprise IT, he holds all AWS certifications, two master degrees in Computer Science and Enterprise Management, and multiple Agile Management certifications. At AWS, he drives customers through their cloud journeys by converting complex challenges into actionable roadmaps for both technical and business audiences. Jorge is also an SME for migration and modernization, digital identity, web3, and emotional intelligence. 𝐒𝐞𝐬𝐬𝐢𝐨𝐧 𝐓𝐢𝐥𝐞: Cloud migration and modernization approaches that work 𝗦𝘆𝗻𝗼𝗽𝘀𝗶𝘀: Enterprises are increasingly undertaking complex journeys of IT transformation, migration, and modernization in the cloud. This session focuses on valuable lessons learned from the thousands of enterprises who have migrated and modernized their on-premises workloads with AWS. We will dive deep into several successful cloud journeys to learn about their technical approaches, mental models used, how they set up their teams to modernize as they migrate, and how they successfully engaged with internal and external stakeholders.

Daniel Hiller is a software engineer with more than 20 years of work experience. He strives to create software that is useful for people so they can do stuff that matters. He’s currently part of the KubeVirt community. KubeVirt is a Kubernetes addon to run virtual machines on Kubernetes clusters. There he maintains, improves and automates CI and testing processes for the KubeVirt organization using Prow on Kubernetes and Golang. 𝐒𝐞𝐬𝐬𝐢𝐨𝐧 𝐓𝐢𝐥𝐞: Squash the flakes! - how to minimize the impact of flaky tests 𝗦𝘆𝗻𝗼𝗽𝘀𝗶𝘀: Flakes aka tests that don’t behave deterministically, i.e. they fail sometimes and pass sometimes, are an ever-recurring problem in software development. There are various reasons why a test can be flaky, however the impact can be as fatal as CI being loaded beyond capacity causing overly long feedback cycles or even users losing trust in CI itself. For the [KubeVirt] project we want to remove flakes as fast as possible to minimize the number of retests required. This leads to shorter time to merge, improves trust in CI, while at the same time it decreases the overall load for the CI system.

Enrico is a Tech Lead and Principal Software Engineer at Elastic. He is an open source contributor (e.g. Langchain) and a developer since 1996. He is an adjunct Professor of computer science at the University of Turin. He has been a research programmer at the University of Amsterdam. TEDx and international speaker in 120+ conferences. He has a Master in Data Analytics from University of Roma Tre. 𝐒𝐞𝐬𝐬𝐢𝐨𝐧 𝐓𝐢𝐥𝐞: Talk with your data: building a RAG system for searching (private) data in natural language 𝗦𝘆𝗻𝗼𝗽𝘀𝗶𝘀: In this presentation, we will introduce a recent proposal in AI that is called Retrieval-Augmented Generation (RAG). This technique is able to leverage the natural language capabilities of Large Language Model (LLM) such as ChatGPT in order to query a private database. You can literally ask questions about your data, without the need to fine-tune an LLM. We will build a simple RAG system using Langchain, an open source framework for writing applications for LLM. We will show with a few lines of Python that you can build a prototype system using a vector database like Elasticsearch.