July 17-19 | Tokyo, Japan
View More Details  & Register Here
Back To Schedule
Wednesday, July 17 • 13:30 - 14:10
Building Telemetry and Anomaly Detection Models for Cloud Native Storage - Xing Yang, Futurewei & Seiya Takei, Yahoo Japan Corporation

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
Integrating with heterogeneous storage in the Cloud Native environment has always been a challenge. How to detect problems and fix them in a timely fashion is important for mission critical workloads.

In this session, Takei-san and Xing will describe a common volume metrics model designed to retrieve data from heterogeneous storage in the Cloud Native environment. They will also illustrate a ML module that analyzes the data to detect anomaly, and discuss how it helps Yahoo Japan identify problems early to keep the storage systems healthy.

Volume metrics such as IOPs, bandwidth, latency, and capacity are generated from storage backends serving workloads running on Kubernetes, and collected by the Prometheus server. Data is also piped through Kafka, parsed and saved in MongoDB. The ML module retrieves data to train the models, chooses the best model to detect anomalous data points.


Seiya Takei

Storage Engineer, Yahoo Japan Corporation
Seiya Takei is in charge of private cloud compute and storage at Yahoo Japan. Yahoo Japan has been participated in the End-User Advisory Committee of OpenSDS, an open source project under Linux Foundation, since July 2017. Seiya Takei has speaking experiences at local conferences... Read More →
avatar for Xing Yang

Xing Yang

Tech Lead, VMware
Xing Yang is a Tech Lead in the Cloud Native Storage team at VMware. She is a co-chair of CNCF Storage TAG, a co-chair of the Kubernetes Storage SIG, a co-chair of the Data Protection WG, and a maintainer in Kubernetes CSI. Before joining VMware, Xing was the Lead Architect of OpenSDS... Read More →

Wednesday July 17, 2019 13:30 - 14:10 JST
Hall B (3) (Floor 4F)
  Artificial Intelligence
  • Experience Level Any