Join our hosts 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.
Entomophiliac, Anna McDonald (Principal Customer Success Technical Architect, Confluent) has seen her fair share of Apache Kafka bugs. For her annual holiday roundup of the most noteworthy Kafka bugs, Anna tells Kris Jenkins about some of the scariest, most surprising, and most enlightening corner cases that make you ask, “Ah, so that’s how it really works?”
Could you explain Apache Kafka in ways that a small child could understand? When Mitch Seymour, author of Mastering Kafka Streams and ksqlDB, wanted a way to communicate the basics of Kafka and event-based stream processing, he decided to author a children’s book on the subject, but it turned into something with a far broader appeal.
What are the key factors to consider when developing event-driven architecture? In this podcast, Adam Bellemare, Staff Technologist at Confluent, discusses the 4 dimensions of events and designing event streams along with best practices, and an overview of a new course he just authored. This course, called Introduction to Designing Events and Event Streams, walks you through the process of properly designing events and event streams in any event-driven architecture.
Is there a better way to manage access to resources without compromising security? New employees need access to a variety of resources within a company's tech stack. But manually granting access can be error-prone. And when employees leave, their access must be revoked, thus potentially introducing security risks if an admin misses one. In this podcast, Kris Jenkins talks to Anuj Sawani (security product manager at Confluent) about the centralized identity management system he helped build to integrate with Apache Kafka to prevent common identity management headaches and security risks.
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.
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.
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