Building a large, stateful Kafka Streams application that tracks the state of each outgoing email is crucial to marketing automation tools like Mailchimp. Joining us today in this episode, Mitch Seymour, staff engineer at Mailchimp, shares how ksqlDB and Kafka Streams handle the company’s largest source of streaming data.
The best-informed business insights that support better decision-making begin with data collection, ahead of data processing and analytics. Enterprises nowadays are engulfed by data floods, with data sources ranging from cloud services, applications, to thousands of internal servers. The massive volume of data that organizations must process presents data ingestion challenges for many large companies. In this episode, data security engineer, Vitalli Rudenskyi, discusses the decision to replace a vendor security information and event management (SIEM) system by developing a custom solution with Apache Kafka and Kafka Connect for a better data collection strategy.
Stream processing has become an important part of the big data landscape as a new programming paradigm to implement real-time data-driven applications. One of the biggest challenges for streaming systems is to provide correctness guarantees for data processing in a distributed environment. Guozhang Wang (Distributed Systems Engineer, Confluent) contributed to a leadership paper, along with other leaders in the Apache Kafka community, on consistency and completeness in streaming processing in Apache Kafka in order to shed light on what a reimagined, modern infrastructure looks like.
Using large amounts of streaming data increasingly requires interactive, real-time analytics and dashboards—and this applies to any industry, including tech. CTO and Co-Founder of Rockset Dhruba Borthakur shares how his company uses Apache Kafka to perform complex joins, search, and aggregations on streaming data with low latencies. The Kafka database integrations allow his team to make a cloud-native analytics database that is a fundamental piece of enterprise infrastructure.
Automated behavioral-driven testing of your event-driven microservices—sounds great, right? But how do you do it? SmartBear's Alianna Inzana shares about just that and some tooling that SmartBear makes to support efforts like this. In fact, SmartBear is actually responsible for many products that you're probably familiar with.
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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