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Authors: Irvin Lim, Hailin Xiang
2023-04-19

tldr - powered by Generative AI

The presentation discusses the implementation of a colocation system for Kubernetes and YARN workloads, as well as the importance of risk classification and release automation in software development. The presentation also emphasizes the need for comprehensive observability through capturing low and high-level metrics and using co-location cost to evaluate the effectiveness of the project.
  • Implemented a colocation system for Kubernetes and YARN workloads
  • Importance of risk classification and release automation in software development
  • Comprehensive observability through capturing low and high-level metrics
  • Use of co-location cost to evaluate the effectiveness of the project
Authors: Chen Wang, Abdul Qadeer
2021-10-13

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Load balancing and resource allocation in Kubernetes clusters using Trimaran plugins
  • Trimaran is a set of plugins for Kubernetes clusters that optimize resource allocation and load balancing
  • The Target Load Packing plugin aims to achieve high utilization across all nodes while maintaining a safe margin for CPU usage spikes
  • The Load Variation Risk Balancing plugin computes a risk score based on CPU and memory utilization and chooses the bottleneck resource score
  • Trimaran uses multiple metric sources and caches data to avoid overwhelming metric providers
  • Future work includes integrating Trimaran with other schedulers and incorporating additional resources like IO and network latency