Open Source Data Breakfast Toronto
Enjoy breakfast and practical discussions on Apache Kafka, Clickhouse and much more. Enjoy a session designed for data engineers, architects and technical decisions-makers like you, who want to address the challenges they face in data-infrastructure. No high-level pitches but straight into practical discussions on how to build scalable, efficient open sourced-powered data platforms.
Speakers:
Maulik Parkikh, Staff Solution Architect at Aiven
Steve Hutchinson, Technical Account Manager at Aiven
Jishnu Raj, Product Group Engineering Lead at Priceline
Agenda:
09:00 to 09:30 AM – Doors Open & Networking
09:30 to 10:00 AM - Session 1: Event Driven Search and Personalization at Priceline: Transformation Journey
10:00 to 10:30 AM – Session 2: The Diskless Revolution: Scaling Observability to Petabytes with Kafka, ClickHouse, and Thanos
10:30 to 10:45 AM – Open Q&A and Technical Breakouts
Abstract Session 1:
A look at how Priceline modernized its search and personalization capabilities through an event-driven architecture, from capturing customer intent signals to delivering intelligent, high-performance search results that drive relevance and conversion.
Abstract Session 2:
As telemetry data explodes, the "Observability Tax"— the cost of storing logs, metrics, and traces—often outpaces the cost of the actual production environment. Traditional architectures rely on expensive block storage and rigid scaling. But what if you could decouple your data from your disks entirely? In this session, we explore a next-generation observability architecture using Diskless Kafka (utilizing Tiered Storage), ClickHouse, and Thanos. We will share case study and practical lessons of how we evolved and achieved 45%+ savings on telemetry. We will walk through how we built a unified pipeline that handles high-throughput telemetry while offloading data to cost-effective object storage without sacrificing query performance. Attendees will learn how to bridge the gap between real-time streaming and long-term analytical storage using open standards.