Operational analytic databases are a new class of data systems that are emerging to store and analyze various types of operational data, including netflows. Popula …

This session will cover the industry landscape and latest developments in terms of data YANG modeling-driven management in the first part. And the second part will …

Network operators are increasingly adopting automation, but most networks today are managed as a set of individual devices. Further, approximately 70% of network o …

We are living in a new age that empowers network engineers to create the building blocks for the future of intent-based networks. The rising wave of network APIs and data models have changed the way w …

PayPal is one of the biggest Kafka users in the industry; it manages and maintains over 40 production Kafka clusters in three geodistributed data centers and supports 400 billion Kafka messages a day. Kevin Lu, Maulin Vasavada, and Na Yang explore the management and monitoring PayPal applies to Kafka, from client-perceived statistics to configuration management, failover, and data loss auditing.

Data is the lifeblood of an enterprise, and it's being generated everywhere. To overcome the challenges of data gravity, data analytics, including machine learning, is best done where the data is located: ubiquitous machine learning. Han Yang explains how to overcome the challenges of machine learning everywhere.

Han Yang explains how Cisco is leveraging big data and analytics and details how the company is helping customers to incorporate data sources from the internet of things and deploy machine learning at the edge and at the enterprise.

Lyfts business has grown over 100x in the past four years. Shenghu Yang explains how Lyfts data pipeline has evolved over the years to serve its ever-growing analytics use cases, migrating from the world's largest AWS Redshift clusters to Apache Hive and Presto for solving scalability and concurrency hard limits.