Becoming Data Driven with Apache Kafka and Stream Processing ft. Daniel Jagielski episode artwork

EPISODE · Feb 22, 2021 · 48 MIN

Becoming Data Driven with Apache Kafka and Stream Processing ft. Daniel Jagielski

from Confluent Developer ft. Tim Berglund, Adi Polak & Viktor Gamov · host Confluent, original creators of Apache Kafka®

When it comes to adopting event-driven architectures, a couple of key considerations often arise: the way that an asynchronous core interacts with external synchronous systems and the question of “how do I refactor my monolith into services?” Daniel Jagielski, a consultant working as a tech lead/dev manager at VirtusLab for Tesco, recounts how these very themes emerged in his work with European clients. Through observing organizations as they pivot toward becoming real time and event driven, Daniel identifies the benefits of using Apache Kafka® and stream processing for auditing, integration, pub/sub, and event streaming.He describes the differences between a provisioned cluster vs. managed cluster and the importance of this within the Kafka ecosystem. Daniel also dives into the risk detection platform used by Tesco, which he helped build as a VirtusLab consultant and that marries the asynchronous and synchronous worlds.As Tesco migrated from a legacy platform to event streaming, determining risk and anomaly detection patterns have become more important than ever. They need the flexibility to adjust due to changing usage patterns with COVID-19. In this episode, Daniel talks integrations with third parties, push-based actions, and materialized views/projects for APIs.Daniel is a tech lead/dev manager, but he’s also an individual contributor for the Apollo project (an ICE organization) focused on online music usage processing. This means working with data in motion; breaking the monolith (starting with a proof of concept); ETL migration to stream processing, and ingestion via multiple processes that run in parallel with record-level processing.EPISODE LINKSBuilding an Apache Kafka Center of Excellence Within Your Organization ft. Neil Buesing Risk Management in Retail with Stream ProcessingEvent Sourcing, Stream Processing and ServerlessIt’s Time for Streaming to Have a Maturity Model ft. Nick DeardenRead Daniel Jagielski's articles on the Confluent blogJoin the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperLive demo: Kafka streaming in 10 minutes on Confluent CloudUse 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)SEASON 2 Hosted by Tim Berglund, Adi Polak and Viktor Gamov Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed Music by Coastal Kites Artwork by Phil Vo  🎧 Subscribe to Confluent Developer wherever you listen to podcasts. ▶️ Subscribe on YouTube, and hit the 🔔 to catch new episodes.👍 If you enjoyed this, please leave us a rating. 🎧 Confluent also has a podcast for tech leaders: "Life Is But A Stream" hosted by our friend, Joseph Morais.

Episode metadata supplied by the publisher feed · Published Feb 22, 2021

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When it comes to adopting event-driven architectures, a couple of key considerations often arise: the way that an asynchronous core interacts with external synchronous systems and the question of “how do I refactor my monolith into services?” Daniel Jagielski, a consultant working as a tech lead/dev manager at VirtusLab for Tesco, recounts how these very themes emerged in his work with European clients. Through observing organizations as they pivot toward becoming real time and event dr...

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Becoming Data Driven with Apache Kafka and Stream Processing ft. Daniel Jagielski

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This episode was published on February 22, 2021.

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