Job Description
About ByteDance
Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.
Why Join Us
Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us.
About the Team
Our team is dedicated to building cutting-edge cloud-native infrastructure to support ByteDance's diverse product lines. We specialize in Kubernetes cluster management, runtime resource optimization, multi-cloud and multi-cluster solutions, and ensuring the stability of cloud-native infrastructure. With projects such as Kubebrain and Katalyst, we focus on advancing core technologies around resource pooling and elasticity.
Responsibilities
- Build and Scale Kubernetes Clusters:
- Design and manage ultra-large-scale Kubernetes clusters.
- Drive the evolution and optimization of system architectures, ensuring high performance and reliability in scenarios like big data and machine learning.
- Define and Optimize Cluster SLOs:
- Establish Service Level Objectives (SLOs) for Kubernetes clusters.
- Analyze end-to-end latency, identify performance bottlenecks, and implement solutions to enhance system efficiency.
- Develop Observability Systems:
- Build and enhance Kubernetes observability tools to improve troubleshooting efficiency.
- Create a comprehensive observability data warehouse and leverage data-driven approaches to optimize cluster performance.
