Chaos Controller for Distributed Container Event Orchestration
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Solution Overview
Problem
Current container orchestration systems in distributed environments, such as Kubernetes across cellular networks, face challenges in efficiently simulating and assessing the resilience and performance under disruptive events, which are crucial for identifying bottlenecks and improving system reliability.
Innovation Solution
A chaos controller is deployed in a management cluster to monitor and orchestrate simulated events across multiple workload clusters, using chaos resource objects to inject controlled disruptions like outages or churn, allowing for precise evaluation of system responses and performance bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simulated events are orchestrated across multiple workload clusters using a chaos controller, then system resilience assessment capability is improved, but system complexity increases
Solution Approach 1:
A chaos controller is introduced as an intermediary component that centralizes the management of simulated disruptive events across multiple workload clusters. The chaos controller receives event specifications, determines orchestration plans, and coordinates event injection, thereby improving resilience assessment capability while managing system complexity through centralized control rather than distributed coordination overhead
Solution Approach 2:
The system is segmented into distinct functional components: the chaos controller for event orchestration, workload clusters for event execution, and event specifications for event definition. This segmentation allows each component to specialize in its function, improving overall system resilience assessment while maintaining manageable complexity through clear separation of concerns
2Measurement precision
If extensive real-world testing is conducted to assess system performance under disruptive events, then measurement precision is improved, but loss of time increases
Solution Approach 1:
Disruptive events are pre-defined and specified in event specifications before actual testing. The chaos controller pre-determines orchestration plans for these events across workload clusters. This preliminary preparation enables precise performance measurement under controlled disruptive conditions without requiring extensive ad-hoc testing time
Solution Approach 2:
Instead of conducting extensive real-world testing with physical systems, the invention uses simulated disruptive events that replicate real-world failure conditions in a controlled environment. The chaos controller orchestrates these simulated events that copy the essential characteristics of real disruptive events, providing accurate performance measurement without the time cost of extensive physical testing
3Productivity
If specialized hardware is deployed to meet 5G requirements for high throughput and low latency, then system performance is improved, but device complexity increases
Solution Approach 1:
The system uses simulated workload clusters that replicate 5G network environments with required performance characteristics without deploying extensive specialized hardware. The chaos controller orchestrates events on these simulated clusters, providing a cost-effective alternative to physical 5G hardware deployment while maintaining relevant performance validation capabilities
Data Source
AI summary
The disclosure provides a method for orchestrating simulated events in a distributed container-based system. The method generally includes monitoring, by a chaos controller deployed in a management cluster of the container-based system, for new objects generated at the management cluster, wherein the management cluster is configured to manage a plurality of simulated workload clusters in a simulation system, based on the monitoring, discovering, by the chaos controller, a new object generated at the management cluster providing information about events intended to be simulated for one or more simulated workload clusters of the plurality of simulated workload clusters, determining a plan for orchestrating a simulation of the events in the one or more simulated workload clusters based on the information provided in the new object, and triggering the simulation of the events in accordance with the plan.