There are rapid changes occurring in the intra-data center connectivity realm. We took interest in work from the 25-50-100 Gigabit Ethernet camp. The connectivity …

The talk will focus on how to route our end users to the closest location serving content – i.e. to the closest PoP. Traditionally LinkedIn used geo-location base …

Shirshanka Das and Yael Garten describe how LinkedIn redesigned its data analytics ecosystem in the face of a significant product rewrite, covering the infrastructure changes, such as client-side activity tracking, a unified reporting platform, and data virtualization techniques to simplify migration, that enable LinkedIn to roll out future product innovations with minimal downstream impact.

With Apache Kakfa 0.9, the community has introduced a number of features to make data streams secure. Jun Rao explains the motivation for making these changes, discusses the design of Kafka security, and demonstrates how to secure a Kafka cluster. Jun also covers common pitfalls in securing Kafka and talks about ongoing security work.

For the past year, LinkedIn has been running and iteratively improving Luminol, its anomaly detection system for real user monitoring data. Ritesh Maheshwari and Yang Yang offer an overview of Luminol, focusing on how to build a low-cost end-to-end system that can leverage any algorithm, and explain lessons learned and best practices that will be useful to any engineering or operations team.

Chad Bailey demonstrates how to put the combination of static and dynamic data to work in your own apps.

Youve decided you need data scientists. You know who to hire. Now, what do you do with them? Yael Garten offers examples of how companies like LinkedIn use data to make business and product decisions. Yael reviews the spectrum of data science, and discusses the culture, process and tools needed to transform companies into data-driven organizations.

Apache Kafka lies at the heart of the largest data pipelines, handling trillions of messages and petabytes of data every day. Learn the right approach for getting the most out of Kafka from the experts at LinkedIn and Confluent. Todd Palino and Gwen Shapira explore how to monitor, optimize, and troubleshoot performance of your data pipelinesfrom producer to consumer, development to production.