[Talk] Enriching Kafka Applications With Real-time Contextual Data

cfp/2023-06-06-enriching-kafka-applications-with-real-time-contextual-data.md

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+---
+title: "Enriching Kafka Applications With Real-time Contextual Data"
+date: 2023-06-06T10:31:36Z
+github_username: fawazghali
+twitter_username: fawazghali
+---
+### Author's Name
+
+Fawaz Ghali
+
+### Author's Bio
+
+Fawaz Ghali is the Principal Data Science Architect and the Head of Developer Relations at Hazelcast with 20+ years of experience in software development, machine learning and real-time intelligent applications. He holds a PhD in Computer Science and has worked in the private sector as well as Academia as a Researcher and Senior Lecturer. He has published over 46 scientific papers in the fields of machine learning and data science. His strengths and skills lie within the fields of low latency applications, IoT & Edge, distributed systems and cloud technologies.
+
+
+### Expected time
+
+Standard talk (~40 min)
+
+### Language
+
+- [ ] French
+- [X] English
+
+### Abstract
+
+Developing high-performance large-stream processing applications is a challenging task. Choosing the right tool(s) is crucial to get the job done; as developers, we tend to focus on performance, simplicity, and cost. However, the cost becomes relatively high if we end up with two or more tools to do the same task. Simply put, you need to multiply development time, deployment time, and maintenance costs by the number of tools. Kafka is great for event streaming architectures, continuous data integration (ETL), and messaging systems of record (database). However, Kafka has some challenges, such as a complex architecture with many moving parts, it can’t be embedded, and it’s a centralized middleware, just like a database. Moreover, Kafka does not offer batch processing, and all intermediate steps are materialized to disk in Kafka. This leads to enormous disk space usage. In this talk, we will address these challenges and how real-time stream processing can be used to enhance Kafka pipelines by simplifying deployment and operations with ultra-low latency and a lightweight architecture making it a great tool for edge (restricted) environments. This talk aims to take your Kafka applications to the next level. The combination of Real-time storage and computing provides a unique synergy that enables applications to address real-time use cases at any scale.
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