Controlplane backup manual#

In the last step, the RCG is converted to a machine learning tool named irregular cellular learning automata (ICLA) that determines the number and locations of controllers as well as the switches they cover. In the next step, the RCG is developed by calculating the exact reliability between the central node and any other nodes in the resulting subgraphs. To construct the RCG, for each candidate node, a subgraph with the adjustable radius r is extracted from the network graph. In this paper, we introduce a new concept named reliability covering graph (RCG) that enables us to use the exact reliability measurement (ERM) methods in solving the RCPP with desired level of complexity. The high complexity of exact reliability measurement led researchers to use estimation techniques that results in overestimating the number of controllers and incorrect placement. One of the important challenges in designing software-defined networks (SDNs) is the reliable controller placement problem (RCPP) that is the problem of finding the number and locations of controllers to satisfy the reliability requirements. Software-defined networking is a new paradigm in network management that has received much attention in recent years. The occurrence of the controller overload during runtime is also significantly decreased. The experimental results show that, compared to the prior arts, the proposed framework reduces the isolation probability by up to 89% and increases the device connectivity by up to 34%. This mechanism dynamically manages the loading of the controller during the execution time so that the occurrence of the controller overload is minimized. In addition, a mechanism based on the State Behavior Tree is proposed in the runtime maintenance phase of the framework.

Moreover, these algorithms are designed by mitigating the problems of device isolation and controller overload such that the reliability and stability of the control plane can be enhanced. Novel algorithms are proposed in the network planning phase to estimate the required number of controllers in the network, to determine the nodes for placing the controllers, and to assign the switch to its managing controller. The proposed framework is comprised of a network planning phase and a runtime maintenance phase. This paper presents an integrated framework for a comprehensive multi-controller management in SDN. Furthermore, to deploy multiple controllers in the control plane of SDN is widely considered with the aim of improving the stability and reliability of the network. changes that weren't saved under the /manifests)Īny of the backup/restore related operations MUST be performed on the controller node.Software-defined networking (SDN) has become the technology of choice for designing the next-generation network infrastructure that is featured with high-volume traffics, rapidly increased scale, and dynamic nature.

Controlplane backup manual#

any configuration to the cluster introduced by manual changes (e.g.

datastore, in case something else than etcd or Kine/SQLite is used.

PersistentVolumes of any running application.

any image bundles located under the /images.

any custom defined manifests under the /manifests.

Kine/SQLite snapshot, if the Kine/SQLite datastore is used.

etcd snapshot, if the etcd datastore is used.

certificates (the content of the /pki directory).

The backups created by k0s backup command have following pieces of your cluster: The k0s backup utility is aiming to back up and restore k0s managed parts of the cluster. K0s has integrated support for backing up cluster state and configuration. Backup/restore a k0s cluster using k0sctl