Abstract: Described is a system, method, and computer program product to handle unresponsive node communications between two nodes of a database cluster. A high availability monitoring module is provided to address unresponsive node communications before having to automatically evict nodes from the cluster simply for exceeding a communications timeout period threshold.

Abstract: Described is a system, method, and computer program product to handle unresponsive node communications between two nodes of a database cluster. A high availability monitoring module is provided to address unresponsive node communications before having to automatically evict nodes from the cluster simply for exceeding a communications timeout period threshold.

Abstract: Processes, computer-readable media, and machines are disclosed for reducing a likelihood that active functional components fail in a computing system. An active monitoring component receives metrics associated with different active functional components of a computing system. The different active functional components contribute to different functionalities of the system. Based at least in part on the metrics associated with a particular active functional component, the active monitoring component determines that the particular active functional component has reached a likelihood of failure but has not failed. In response to determining that the particular active functional component has reached the likelihood of failure but has not failed, the active monitoring component causes a set of actions that are predicted to reduce the likelihood of failure.

Abstract: Described herein are techniques for dynamically monitoring and managing resource usages of processes running on a node in a multi-node database system. High resource usages of processes can be proactively detected and alleviated, thereby making such a node to perform significantly better than otherwise.

Abstract: Processes, computer-readable media, and machines are disclosed for reducing a likelihood that active functional components fail in a computing system. An active monitoring component receives metrics associated with different active functional components of a computing system. The different active functional components contribute to different functionalities of the system. Based at least in part on the metrics associated with a particular active functional component, the active monitoring component determines that the particular active functional component has reached a likelihood of failure but has not failed. In response to determining that the particular active functional component has reached the likelihood of failure but has not failed, the active monitoring component causes a set of actions that are predicted to reduce the likelihood of failure.

Abstract: Processes, computer-readable media, and machines are disclosed for reducing a likelihood that active functional components fail in a computing system. An active monitoring component receives metrics associated with different active functional components of a computing system. The different active functional components contribute to different functionalities of the system. Based at least in part on the metrics associated with a particular active functional component, the active monitoring component determines that the particular active functional component has reached a likelihood of failure but has not failed. In response to determining that the particular active functional component has reached the likelihood of failure but has not failed, the active monitoring component causes a set of actions that are predicted to reduce the likelihood of failure.

Abstract: Processes, computer-readable media, and machines are disclosed for reducing a likelihood that active functional components fail in a computing system. An active monitoring component receives metrics associated with different active functional components of a computing system. The different active functional components contribute to different functionalities of the system. Based at least in part on the metrics associated with a particular active functional component, the active monitoring component determines that the particular active functional component has reached a likelihood of failure but has not failed. In response to determining that the particular active functional component has reached the likelihood of failure but has not failed, the active monitoring component causes a set of actions that are predicted to reduce the likelihood of failure.

Abstract: Described herein are techniques for dynamically monitoring process activeness of processes running on a computing node. Problems affecting processes to serve their designated functions on the computing node can be relatively quickly detected and dealt with, thereby making restoring process activeness on the computing node much more quickly than otherwise.

Abstract: Described herein are techniques for dynamically monitoring process activeness of processes running on a computing node. Problems affecting processes to serve their designated functions on the computing node can be relatively quickly detected and dealt with, thereby making restoring process activeness on the computing node much more quickly than otherwise.

Abstract: Described herein are techniques for dynamically monitoring and managing resource usages of processes running on a node in a multi-node database system. High resource usages of processes can be proactively detected and alleviated, thereby making such a node to perform significantly better than otherwise.