KubeCon + CloudNativeCon China 2018: Full Schedule

November 13–15, 2018 - Shanghai, China
Click Here For Information & Registration

To view the Chinese version of this schedule please go here.
请点击此处查看中文版本。

我们将为所有主题演讲和分组会议提供同声传译服务。
Simultaneous translation will be provided for all keynote and breakout sessions.

11:05 CST

A Day in the Life of a Data Scientist. Conquer ML Lifecycle on Kubernetes - Rita Zhang & Brian Redmond, Microsoft

Ever wondered how machine learning models are built? Well, here’s your opportunity to come spend a day in the life of a data scientist. This will be a practical guide to the day-to-day lifecycle of a machine learning model. Dive end-to-end through code collaboration, dataset preparation, training and serving. We will cover how to utilize open source tools like Kubeflow and offer an in-depth view of how they operate and aide the machine learning development lifecycle. This session is for both data scientists and infrastructure/SRE teams alike helping bring the benefits of DevOps to AI and machine learning.

Speakers

Brian Redmond

Principal Product Manager, Microsoft

I am a Principal Product Manager working on our Cloud Native Platforms and AKS. My role is to support our customer and community efforts. I have been working in technology for over 28 years and have a mixed background from application development to infrastructure. I am based in Denver... Read More →

Rita Zhang

Principal Software Engineer, Microsoft

Rita Zhang is a software engineer at Microsoft, based in San Francisco. She leads the Azure Container Upstream team building features for Kubernetes upstream and various CNCF projects. Rita is a Kubernetes SIG Auth co-chair, a maintainer of the Secrets Store CSI Driver project, and... Read More →

KubeCon China ML Lifecycle pdf

Wednesday November 14, 2018 11:05 - 11:40 CST
2F Room 1

Machine Learning & Data

Skill Level Intermediate

11:50 CST

Serverless Kubernetes Boosts AI Business - Jian Huang, Huawei

Kubernetes is becoming more and more popular in IT systems including running the AI workloads. Currently, ML/DL Services of Huawei cloud are running over Kubernetes clusters.

In order to make the AI services focus on their business without caring the underlayer infrastructure like physical machines and GPU offering. We provide the serverless Kubernetes services(CCI) in order to meet their requirements. And serverless Kubernetes is very suitable for the users to run the short-time jobs.

In this session, we try to introduce the effort we have make on this area. Such as use kata container to protect the container's security so multi-tenant's workload can run on the same physical machine; support AI jobs with multiple devices like Nvidia GPU, InfiniBand; experience of running DL frameworks like tensorflow over Kubernetes in Huawei and so on.

Speakers

Alfred Huang

General Manager of Cloud Native Services, Huawei

作为华为云云原生服务总监，负责云容器引擎，Serverless容器，服务网格，分布式云原生等多款云原生服务的研发、竞争力构建和业务成功。As the General Manager of Cloud Native Services at Huawei Cloud, Alfred is responsible for the research... Read More →

Serverless Kubernetes boosts AI Business pdf

Wednesday November 14, 2018 11:50 - 12:25 CST
2F Room 1

Machine Learning & Data

Skill Level Beginner

13:55 CST

A Year of Democratizing ML With Kubernetes & Kubeflow - David Aronchick & Fei Xue, Google

A year ago, we introduced the Kubeflow project to make end-to-end ML pipelines on Kubernetes composable, portable & scalable. Today, thanks to passionate contributors from all over the world, we have the most popular ML platform for Kubernetes.

At this Kubecon, we are announcing Kubeflow 1.0, graduating the project to generally available. In this talk, we will cover never before seen features: a web-based UI, simplified setup & sophisticated ML tooling including hyperparameter search and Google's TensorFlow Extended project.

Additionally, we will be demonstrating the newly integrated Pipelines project wiring together multi-cloud ML with continuous training and hosted services.

Thanks to Kubernetes native extensibility, we are able to bring ML to an entirely new audience, where as long as you can code, you can build complete end-to-end solutions.

Speakers

David Aronchick

Head of OSS Machine Learning, Microsoft

David leads Open Source Machine Learning Strategy at Azure. This means he spends most of his time helping humans to convince machines to be smarter. He is only moderately successful at this.Previously, he led product management for Kubernetes, launched Google Kubernetes Engine and... Read More →

Fei Xue

Product Manager, Ant Financial

Fei Xue is currently a product manager at Ant Financial working on ML and data platform. Fei was an early member of the Kubeflow team at Google, an open source effort to help developers and enterprise develop and deploy cloud-native machine learning everywhere. Fei comes from a distributed... Read More →

Wednesday November 14, 2018 13:55 - 14:30 CST
2F Room 1

Machine Learning & Data

Skill Level Any

14:40 CST

“KubeGene” a Genome Sequencing Workflow Management Framework - Shenjun Tang, Huawei

In the recent years, exponential growth of genetic data makes it hard for researchers to do analysis on a traditional computers. In this presentation, Tangshengjun will provide an overview of “KubeGene” a bio-genetic management framework built on top of Kubernetes platform for managing TB/PB of data deployed across a cluster with hundreds of nodes.

“KubeGene” supports data-processing pipelines for Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), liquid biopsy, single cell sequencing and other sequencing scenarios with best practices, like Genome Analysis Toolkit (GATK), on the Kubernetes cluster. Furthermore, “KubeGene” can easily deploy a cluster-based data-science platform for data-mining based on the processed data. In conclusion, “KubeGene” provides users with full-stack, easy-to-use, scalable bio-genetic cloud computing solution.

Speakers

Shengjun Tang

Senior Software Engineer 高级软件工程师, Huawei

Huawei Cloud architect, more than 10 years of work experience. At present, he is the technical leader of Huawei cloud application orchestration service and gene container field, leading cloud service catalog, application orchestration, and genetic container architecture design. He... Read More →

KubeGene，一种基因测序流程管理框架 pdf

Wednesday November 14, 2018 14:40 - 15:15 CST
2F Room 1

Machine Learning & Data

Skill Level Beginner

15:35 CST

A Hybrid Container Cloud With Kubernetes and Hadoop YARN - Jian He & Bushuang Gao, Alibaba

Hadoop YARN is a resource management platform to run big data applications such as MapReduce, Spark and it is architecturally different from Kubernetes which well suits long running services. Many organizations keep both of them to fulfill different types of workloads. However, this approach will incur staggering ops and hardware cost.

Looking at the differences in the 2 types of workloads, is it possible to let them share a single cluster while keeping both resource management systems working in harmony? What are the requirements and what hurdles do we need to overcome?

In this talk we will present a framework developed by Alibaba, that can seamlessly run both Kubernetes and Hadoop in a single cluster with the ability of elastic resource sharing. In addition, we will also share lessons we learned in managing both workloads in production to support Alibaba massive commercial platform.

Speakers

Bushuang Gao

Senior Software Engineer 高级软件工程师, Alibaba

Bushuang Gao is a Senior Engineer at Alibaba. He works in the container platform team and has extensive experience in Kubernetes and container area. Bushuang Gao 现任阿里巴巴高级工程师。他在容器平台团队工作，在 Kubernetes... Read More →

Jian He

Staff Engineer, Alibaba

Jian He is a Staff Engineer at Alibaba where he works on a container infrastructures to support Alibaba massive workloads globally. Prior to that, he worked at Hortonworks Hadoop team, and primarily contributes to the Hadoop open source community and is also the Hadoop committer and... Read More →

kubecon china 2018 pdf

Wednesday November 14, 2018 15:35 - 16:10 CST
2F Room 1

Machine Learning & Data

Skill Level Beginner

16:20 CST

Benchmarking Machine Learning Workloads on Kubeflow - Xinyuan Huang, Cisco Systems, Inc. & Ce Gao, Caicloud

Benchmarking is an essential part in machine learning research and productization, that provides useful performance information from the perspectives of both models and systems. While Kubernetes and Kubeflow give us a great platform for ML workloads to run on, they do not automatically provide a straightforward way to perform benchmark tasks, especially for complex ML workloads based on distributed jobs. In this talk we present Kubebench, an open sourced benchmarking tool based on Kubeflow, that helps us better understand the performance signature of our ML workloads on Kubernetes through automated and consistent benchmarks. We also show how we can leverage other benchmarking efforts from academia and industry like MLPerf and Dawnbench.

Speakers

Ce Gao

Engineer Intern 实习工程师, Caicloud

Ce Gao is an engineer intern in Caicloud and a maintainer of Kubeflow project focusing on distributed training and AutoML support on Kubernetes. He is currently pursuing the post-graduation degree with the School of Software, Shanghai Jiao Tong University, China. Ce Gao... Read More →

Xinyuan Huang

Technical Leader, Cisco

Xinyuan Huang is a Technical Leader at Cisco, where he leads the performance evaluations and optimizations in cloud and AI/ML systems. He is an active member in MLPerf and Kubeflow community.

Kubebench KubeCon2018China pdf

Wednesday November 14, 2018 16:20 - 16:55 CST
2F Room 1

Machine Learning & Data

Skill Level Intermediate

11:30 CST

Modern Data Science in a Cloud Native World - Samuel Kreter, Microsoft

We now live in 2018, where the meaning of Big Data keeps getting bigger. Yet, the tools most people are using with their data requires a huge amount of experience to understand and scale. We are also facing a time where it is necessary to track the flow of data for better understanding and compliance with GDPR.

I am going to walk through how to take advantage of Kuberentes and other Cloud Native technologies with the open source project Pachyderm to create data science pipelines that are easy to develop, test, deploy and scale. I will also cover how to use Data Versioning throughout the process to track data changes and understand exactly how your data is changing.

Talk Outline:
1. Introduce the basic concepts of Data Pipelines and Versioning.
2. Create and test a simple model.
4. Scale it up to a production sized workload and automatically have changes deployed in the pipeline.

Speakers

Samuel Kreter

Software Engineer 软件工程师, Microsoft

Sam Kreter is a software engineer at Microsoft working on the Cloud Native Compute Team focused on Azure Container Instances. Previously, he worked with an SOS Venture incubator company out of Shanghai, China developing a Bitcoin transferring technology. He also worked as a research... Read More →

KubeConAsia2018Final pdf

Thursday November 15, 2018 11:30 - 12:05 CST
2F Room 1

Machine Learning & Data

Skill Level Intermediate

12:15 CST

Operating Deep Learning Pipelines Anywhere Using Kubeflow - Jörg Schad & Gilbert Song, Mesosphere

Kubeflow makes it very easy for data scientist to build their own data science pipeline with Jupyter Notebooks, TensorFlow, TensorBoard and Model serving. In this talk we will walk through building a production grade data science pipeline using Kubeflow and open source data, streaming and CI/CD automation tools.

Audience will learn about need for data preparation (which is frequently performed using Apache Spark or Apache Flink), data storage (using HDFS, Cassandra), automation via CI/CD (using Jenkins) and request streaming (using Apache Kafka).

In this talk we look at building and operate a complete deep learning pipeline around Kubeflow for multiple tenants and topics such as:

* Data Preparation/Cleansing (using Apache Spark)
* Data and Model Storage
* Model Serving
* Distributed Training
* Monitoring
* Automation using CI/CD
* Infrastructure Management across multiple tenants

Speakers

Jörg Schad

CTO, ArangoDB

Jörg Schad is the CTO at ArangoDB. In a previous life, he has worked on or built machine learning pipelines in healthcare, distributed systems, including early Kubernetes code at Mesosphere, and in-memory databases. He received his Ph.D. for research about distributed databases and... Read More →

Gilbert Song

Staff Software Engineer, Mesosphere

Gilbert Song, Apache Mesos PMC/Committer, is a Tech Lead at Mesosphere. He has been contributing to Mesos for years and mainly focuses on Mesos Containerization. He holds a Master’s degree in Computer Engineering from University of California, Santa Barbara. He is passionate about... Read More →

Kubecon KubeFlow++ Summit pdf

Thursday November 15, 2018 12:15 - 12:50 CST
2F Room 1

Machine Learning & Data

Skill Level Intermediate

14:20 CST

Kubeflow From the End User’s Perspective: The Good, The Bad, and The Ugly - Xin Zhang, Caicloud

Kubernetes has become the most popular open-source container orchestration platform for managing cloud-native workloads. Furthermore, given the ubiquitousness of Artificial Intelligence (AI), Kubeflow has risen as a new open-source project tailoring Kubernetes to optimize for Machine Learning (ML) stacks, solving the devops chores and performance bottleneck usually plaguing a production ML system.

Despite the promise, we (as a contributor to Kubeflow) have identified glitches of Kubeflow when being applied in the wild. We have surveyed 50+ real Kubeflow users (both system administrators and machine learning developers) from our enterprise customers. We will share how Kubeflow solves their pain-points, what pitfalls and disappointments they encountered in daily usage scenario, and how to evolve Kubeflow to be more practical and generally applicable.

Speakers

Xin Zhang

CEO 首席执行官, Caicloud

Xin is currently CEO and co-founder of Caicloud (https://caicloud.io), a startup that fosters Kubernetes community in China (https://kubeacademy.caicloud.io) and provides Kubernetes-based products and services for Chinese enterprises. His team has helped tens of well-known Chinese... Read More →

Thursday November 15, 2018 14:20 - 14:55 CST
2F Room 1

Machine Learning & Data

Skill Level Any

15:05 CST

Machine Learning on Kubernetes Birds of a Feather - David Aronchick

A birds of a feather meeting discussing the best practices for getting machine learning solutions up and running, and managing them at scale. We will talk about the entire pipeline of machine learning, from data ingestion all the way to serving in production, and every step in between.

Speakers

David Aronchick

Head of OSS Machine Learning, Microsoft

Thursday November 15, 2018 15:05 - 15:40 CST
2F Room 1

Machine Learning & Data

Skill Level Any

16:00 CST

Discovering the Untold User Stories of Kubernetes With Applied Anthropology - Hippie Hacker & Indigo Phillips, ii.coop

Applying concepts of identity from indigenous cultures and societies around the world, we'll explore the unseen, yet interwoven patterns of real-world user journeys within the Kubernetes community.

If we listen closely, these valuable and inter-related stories can provide deep insight into how people interact with Kubernetes and beyond.

Integrating context and genealogy into our core software protocols, APIsnoop uses machine learning to produce actionable data driven analysis used to refine the definition of what it means to provide a Certified Kubernetes service.

Please join us as we learn something about our software ecosystem (and ourselves) by exploring definitions of individual and group identity from around the world, from Austin to Aotearoa, the Land of the Long White Cloud.

Speakers

Hippie Hacker

Chief Executive Hippie, ii.coop

Hippie Hacker's unique approach to storytelling includes practical application of technology with a focus on humanity as a whole. He has a lifelong interest in the creation of vehicles of viral generosity that everyone can ride.His travels starting in an avocado green Volkswagen took... Read More →

Indigo Phillips

Software Developer/Development Advocate, ii.coop / Arataki Systems

Indigo hails from the northern part of New Zealand where her deep cultural heritage and connection to the land drive her passion for diversity and inclusion of Māori women and youth in the tech industry. Awarded a Te Uru Rangi Māori Scholarship into Enspiral Dev Academy, she's using... Read More →

APISnoop pdf

Thursday November 15, 2018 16:00 - 16:35 CST
2F Room 1

Machine Learning & Data

Skill Level Any

16:45 CST

Apache Spark on Kubernetes: A Technical Deep Dive - Yinan Li, Google

Apache Spark is currently the most popular open-source large-scale data processing framework. Previously, users could run Spark applications on standalone, Yarn, and Mesos clusters. In the Spark 2.3.0 release, Kubernetes became a new scheduler backend for Spark. This new scheduler backend enables Spark applications to run natively on Kubernetes by leveraging the Kubernetes scheduler for scheduling and running Spark drivers and executors. In this talk, we will give a deep dive into the technical details of the Kubernetes scheduler backend and explore all the exciting new things that this native Kubernetes integration brings to Apache Spark. We will also go over the roadmap and features that the Kubernetes community has planned for the scheduler backend over the next several releases of Spark.

Speakers

Yinan Li

Software Engineer, Google

Yinan Li is currently a Software Engineer at Google. He focuses on work that enriches Kubernetes with enterprise-grade data management capabilities and work that enables large-scale data processing on Kubernetes, including the Kubernetes scheduler backend for Apache Spark. Yinan is... Read More →

Apache Spark on Kubernetes A Technical Deep Dive pdf

Thursday November 15, 2018 16:45 - 17:20 CST
2F Room 1

Machine Learning & Data

Skill Level Any