Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search

Published on Nov 29, 2013

This is a technical architect's case study of how Loggly has employed the latest social-media-scale technologies as the backbone ingestion processing for our multi-tenant, geo-distributed, and real-time log management system. This presentation describes design details of how we built a second-generation system fully leveraging AWS services including Amazon Route 53 DNS with heartbeat and latency-based routing, multi-region VPCs, Elastic Load Balancing, Amazon Relational Database Service, and a number of pro-active and re-active approaches to scaling computational and indexing capacity.

The talk includes lessons learned in our first generation release, validated by thousands of customers; speed bumps and the mistakes we made along the way; various data models and architectures previously considered; and success at scale: speeds, feeds, and an unmeltable log processing engine.



https://www.youtube.com/embed/LpNbjXFPyZ0

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Kafka开源项目指南提供详尽教程,助开发者掌握其架构、配置和使用,实现高效数据流管理和实时处理。它高性能、可扩展,适合日志收集和实时数据处理,通过持久化保障数据安全,是企业大数据生态系统的核心。

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