Patent classifications
G06F11/203
AUTOMATICALLY PREDICTING FAIL-OVER OF MESSAGE-ORIENTED MIDDLEWARE SYSTEMS
Methods, apparatus, and processor-readable storage media for automatically predicting fail-over of message-oriented middleware systems are provided herein. An example computer-implemented method includes obtaining one or more message-oriented middleware parameter values for at least a portion of multiple message-oriented middleware systems; detecting one or more fail-over-related anomalies associated with at least one of the multiple message-oriented middleware systems by processing at least a portion of the one or more message-oriented middleware parameter values using one or more machine learning techniques; and automatically migrating, based at least in part on the one or more detected fail-over-related anomalies, at least a portion of data associated with the at least one message-oriented middleware system associated with the one or more detected fail-over-related anomalies to at least one of the other of the multiple message-oriented middleware systems.
Systems and methods for transitioning from legacy computer systems
A method may include receiving a communication from a user device, determining whether to forward the communication to a first computer system or a second computer system and forwarding the communication to the first computer system based on the determining. The method may also include generating, by the first computer system, a first response to the communication, determining whether an error occurred when processing the communication at the first computer system and forwarding the communication to the second computer system, in response to determining that an error occurred. The method may further include generating, by the second computer system, a second response to the communication and comparing the first response from the first computer system to the second response from the second computer system.
DATA MIGRATION METHOD AND APPARATUS FOR DATABASE
In one example method, a second memory stores data in a database, and the second memory is a memory independent of a first device and a second device. When determining that a database service needs to be switched, the first device may migrate a redo log of the database from a first memory of the first device to the second memory. The second device migrates the redo log from the second memory to a third memory of the second device, and the first device and the second device perform operating system status migration online.
MIGRATION OF VIRTUAL COMPUTE INSTANCES USING REMOTE DIRECT MEMORY ACCESS
A virtual compute instance is migrated between hosts using remote direct memory access (RDMA). The hosts are equipped with RDMA-enabled network interface controllers for carrying out RDMA operations between them. Upon failure of a first host and copying of page tables of the virtual compute instance to the first host's memory, a first RDMA operation is performed to transfer the page tables from the first host's memory to the second host's memory. Then, second RDMA operations are performed to transfer data pages of the virtual compute instance from the first host's memory to the second host's memory, with references to memory locations of the data pages specified in the page tables. The page tables of the virtual compute instance are reconstructed to reference memory locations of the data pages in the second host's memory and stored therein.
Proactive cluster compute node migration at next checkpoint of cluster upon predicted node failure
While scheduled checkpoints are being taken of a cluster of active compute nodes distributively executing an application in parallel, a likelihood of failure of the active compute nodes is periodically and independently predicted. Responsive to the likelihood of failure of a given active compute node exceeding a threshold, the given active compute node is proactively migrated to a spare compute node of the cluster at a next scheduled checkpoint. Another spare compute node of the cluster can perform prediction and migration. Prediction can be based on both hardware events and software events regarding the active compute nodes.
Real-time communication processing system and real-time communication processing method
In a real-time communication processing system of the present disclosure, at least one computer transmits a notification to a management apparatus when a virtual machine on the computer has the possibility of experiencing unstable operation related to real-time communication processing. When a virtual processor is free, the management apparatus instructs the computer to allocate the virtual processor to the virtual machine that has the possibility of experiencing unstable operation. When a virtual processor is not free, the management apparatus instructs the computer to allocate a virtual processor, secured by live migration of a virtual machine capable of live migration, to the virtual machine that has the possibility of experiencing unstable operation.
System and method for scaling resources of a secondary network for disaster recovery
A system and method for scaling resources of a secondary network for disaster recovery uses a disaster recovery notification from a primary resource manager of a primary network to a secondary resource manager of the secondary network to generate a scale-up recommendation for additional resources to the secondary network. The additional resources are based on latest resource demands of workloads on the primary network included in the disaster recovery notification. A scale-up operation for the additional resources is then executed based on the scale-up recommendation from the secondary resource manager to operate the secondary network with the additional resources to run the workloads on the secondary network.
Automated discovery of databases
A networked computing system comprises a backup node cluster of a backup service in communication with a host database node cluster of a host, a host database at least initially undiscovered by the backup node cluster, one or more processors coupled with memory storing instructions that, when executed, perform operations comprising at least installing a backup agent on at least one node of the host database node cluster, registering the host at the backup service, based on the host registration, triggering a host database discovery process to discover the undiscovered database automatically, the discovery process including a discovery call, in response to the discovery call, receiving metadata relating to the discovered database, and communicating with the discovered database.
Network virtualization policy management system
Concepts and technologies are disclosed herein for providing a network virtualization policy management system. An event relating to a service can be detected. A first policy that defines allocation of hardware resources to host the virtual network functions can be obtained, as can a second policy that defines deployment of the virtual network functions to the hardware resources. The hardware resources can be allocated based upon the first policy and the virtual network functions can be deployed to the hardware resources based upon the second policy.
Machine learning to predict container failure for data transactions in distributed computing environment
Inflight transactions having predictable pod failure in distributed computing environments are managed by integrating a transaction manager into pods having containers running applications in a distributed computing environment, wherein the transaction manager records a transaction log having data indicative of historical pod failure. A pod health check that is also integrated into the pods determines predictive pod failure scenarios from the data of historical pod failure in the transaction log. Pod health can be tracked using the pod health checker by matching the predictive pod failure scenarios to transaction calls. Calls may be sent to a load balancer for recovery of pod failure for transaction calling match the predictive pod failure scenarios. Pods can be configured recover for the predictive pod failure.