Join Kris Jenkins and guests from the community as they discuss the latest Apache Kafka® news, use cases, and trends spanning the topics of data streaming, microservices, modern IT architectures, and the cloud.
Can we use machine learning to detect security threats in real-time? As organizations increasingly rely on distributed systems, it is becoming more important to analyze the traffic that passes through those systems quickly. Confluent Hackathon ’22 finalist, Géraud Dugé de Bernonville (Data Consultant, Zenika Bordeaux), shares how his team used TensorFlow (machine learning) and Neo4j (graph database) to analyze and detect network traffic data in real-time. What started as a research and development exercise turned into ZIEM, a full-blown internal project using ksqlDB to manipulate, export, and visualize data from Apache Kafka.
What happens when you need to store more than a few petabytes of data? Rittika Adhikari (Software Engineer, Confluent) discusses how her team implemented tiered storage, a method for improving the scalability and elasticity of data storage in Apache Kafka. She also explores the motivating factors for building it in the first place: cost, performance, and manageability.
In principle, data mesh architecture should liberate teams to build their systems and gather data in a distributed way, without having to explicitly coordinate. Data is the thing that can and should decouple teams, but proper implementation has its challenges. In this episode, Kris talks to Florian Albrecht (Solution Architect, Hermes Germany) about Galapagos, an open-source DevOps software tool for Apache Kafka® that Albrecht created with his team at Hermes, a German parcel delivery company.
Is real-time data streaming the future, or will batch processing always be with us? In this episode, Kris talks to a panel of industry experts with decades of experience building and implementing data systems. They discuss the state of streaming adoption today, if streaming will ever fully replace batch, and whether it even could (or should).
Streaming real-time data at scale and processing it efficiently is critical to cybersecurity organizations like SecurityScorecard. Jared Smith, Senior Director of Threat Intelligence, and Brandon Brown, Senior Staff Software Engineer, Data Platform at SecurityScorecard, discuss their journey from using RabbitMQ to open-source Apache Kafka for stream processing. As well as why turning to fully-managed Kafka on Confluent Cloud is the right choice for building real-time data pipelines at scale.
Kris Jenkins is a senior developer advocate for Confluent, a veteran contractor, and former CTO and co-founder of a gold-trading business. He's especially interested in software design, functional programming, real-time systems, and electronic music.
If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.Email Us