Francesco Tisiot

Whether you’re running mission critical applications or just shipping logs in real time, Tiered Storage can make your Kafka Cluster cheaper, easier to manage and faster. To understand the benefits, tradeoffs and the development history join this talk where we’ll uncover KIP-405 and showcase how the community backed up this important feature for Apache Kafka. We’ll rollback the KIP history, starting from 2018, to understand the major milestones and share details on how major industry leaders like Apple, Datadog and Slack helped out and tested both the Tiered Storage functionality and the first AWS S3 open source plugin. Furthermore, we’ll share details, gotchas, and tradeoffs of users successfully adopting Tiered Storage in production at scale, surpassing 150 GB/s of throughput. If you want to optimize your Apache Kafka cluster for performance, cost, and overall health, this session is for you.

Vector similarity is fundamental for organizations looking to develop secure, cost-effective, and scalable AI solutions. Yet the inexact and complex nature of proximity search represents a risk for use cases, including regulated or sensitive data where precision in the retrieval is an absolute necessity.

PostgreSQL may not be the first thing that comes to mind when we think about AI, but it's becoming increasingly important for a growing number of users. In this talk, we'll take a look at the current state of AI and explain why PostgreSQL has a potential to play a key role in it.

Generative AI is revolutionizing how we work and interact. Yet for generative AI applications relying on private, regulated, or commercially valuable data, feeding the model with the right information is crucial.

Optimization problems are everywhere, from deciding which clothes to pack in our luggage (aka the knapsack problem), to selecting the tasks that will be worked during a sprint.

Let's build an event driven application together! Using Flask as framework we'll add the powerful Apache Kafka, a streaming platform, as backend... all live on stage! Join to understand how to integrate your application with Apache Kafka!

An application with a central database and a series of ETL (Extract, Transform, Load) flows to get data from there to the data warehouse is a familiar pattern in software architecture everywhere.

Any conversation about Big Data would be incomplete without talking about Apache Kafka and Apache Flink: the winning open source combination for high-volume streaming data pipelines. In this talk we'll explore how moving from long running batches to streaming data changes the game completely.

Optimization problems are everywhere, from deciding which clothes to pack in our luggage (aka the knapsack problem), to selecting the tasks that will be worked during a sprint. Trying to solve these type of problems by hand is a tedious task often resulting in sub-optimal decisions.

Code and data go together like tomato and basil; not many applications work without moving data in some way. As our applications modernise and evolve to become more event-driven, the requirements for data are changing.