Linkedin Learning – Achieving Low-Latency Data with Edge Computing

Linkedin Learning – Achieving Low-Latency Data with Edge Computing-XQZT
English | Tutorial | Size: 177.22 MB


Learn how to design, implement, and manage low-latency data processing using edge computing architecture
Edge computing processes data at or near its actual physical source, which allows you to make data available faster than ever-without poor user experiences, bottlenecks, or system degradation. In this course, instructor Gregory Green walks you through how to achieve low latency by building a scaling architecture for edge computing data integration and management.

Discover best practices for reliable messaging and patterns for throughput as well as low latency with flexible data pipelines and multisite cloud-based use cases. Explore some of the most important factors that affect edge computing latency, diving deeper into antipatterns and the pros and cons of database management technologies, with examples drawn from RabbitMQ, Apache Geode, MQTT, and Spring. Along the way, Gregory gives you tips and pointers with hands-on demonstrations of how to successfully design and implement edge computing architecture for low-latency data access in real time.

Author: Gregory Green
Duration: 1:13:09

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