Right-Sizing and Auto-Scaling of MySQL Containers in Kubernetes

Explore techniques for optimizing MySQL container resources in Kubernetes environments through this conference talk. Learn how JD.com developed a system combining statistical analysis, forecasting, and optimization algorithms to dynamically adjust container resource allocations and reschedule containers via Kubernetes and Vitess APIs. Discover methods for workload characterization, right-sizing CPU resources, and implementing auto-scaling strategies. Examine multi-resource balance approaches for host selection and correlation-aware techniques. Gain insights into experimental evaluation setups and key results that demonstrate significant improvements in resource efficiency and cost reduction for large-scale MySQL deployments supporting e-commerce services.

Intro
JD Elastic Database
Problems and Challenges
Workload Characterization
Right Sizing Estimate the worldoad demand
Right Sizing of CPU Resources
Auto Scaling and Rescheduling
Auto-Scaling: Overview and Cost Models
Host Selection: Multi-Resource Balance
Experimental Evaluation Setup
Host Selection: Resource Availability
Host Selection: Correlation-awareness
Key Results
Conclusions