The feedback loops behind Kubernetes

Kubernetes is a powerful framework for running workloads at scale, operating as a system of feedback controllers similar to those used in control theory, such as a thermostat or cruise control. The essential function of a Kubernetes operator is to maintain the desired state of a system—like a database—by continually observing its current state, identifying discrepancies, and taking corrective actions. This process is achieved through a closed feedback loop, where events act as triggers for state evaluation rather than dictating specific actions. Kubernetes components like kubelets, schedulers, and the Container Storage Interface (CSI) handle various operational tasks, while custom operators can be developed to manage specific applications like databases by leveraging tools like controller-runtime. These operators follow level-triggered logic, which helps them remain resilient to disruptions and maintain system stability, ensuring that the current state is aligned with the desired state, even after failures or interruptions. This approach in Kubernetes exemplifies the application of control theory principles in software engineering, allowing for the creation of scalable, self-healing systems that operate autonomously.