Why PostgreSQL matters in the AI space as source, central component and target.

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. Failure could result in adverse consequences such as poor performance, confidential information exposure, or regulatory requirement breaches. An integrated data platform is a powerful way to accelerate the development of generative AI applications by providing real-time data feeds, consolidating inputs from different sources, and defining clear information boundaries. If you are considering generative AI for your business, this lightning talk provides methods for creating safe, up-to-date, and performant applications

When attacking any system, taking control of its central nervous system is the first step in infiltrating the core infrastructure and gaining control over its vital functions. Translating this to organization data, a clear target is Apache Kafka, the data hub increasingly adopted for mission-critical systems. This session explores the topic of attacking and defending Apache Kafka, shedding light on potential threats, attack vectors, and countermeasures.

Initially, we’ll focus on understanding the potential attack surface of Apache Kafka. Defining attackers’ objectives and vectors, including unauthorized access, injection attacks, misconfigurations, and distributed denial-of-service (DDoS). With the fundamental threat surface and actors understood, we’ll shift our focus to defensive strategies that protect Apache Kafka deployments. We will discuss and demonstrate best practices and security measures including ACLs, encryption, and monitoring that can help reduce potential attacks.

Useful Links

• Aiven Signup
• Code examples to run with Aiven for Apache Flink
• Flink JDBC SQL Connector
• Flink SQL CDC Connecto for PostgreSQL

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How and Why using Schema Registry with Apache Kafka

A talk about JSON handling in PostgreSQL: from data loading to query to indexing.

Strings are one of the most used types in databases; they can store pretty much any data and don’t enforce any rules on the inserted input. This talk showcases the risk of using strings and how to mitigate them to ensure data quality.

Extract metadata from your existing data tools and build a queryable graph interface in PostgreSQL®

A deep dive into Kafka connect settings and pitfalls, analysing several tips to have a better experience when setting up a connector.

Collect, analyze, query your metadata to keep control over your data assets