In some examples, migration context and flow graph based migration control may include ascertaining an application that is to be migrated from a physical environment to a cloud environment, and determining a migration issue associated with the migration of the application. Migration context and flow graph based migration control may further include identifying, from a historical issue database, a plurality of historical issues, determining, for the migration issue and the plurality of historical issues, unified proximities, sorting, based on the determined unified proximities, the historical issues, selecting, from the sorted historical issues, a topmost historical issue, and determining, from the topmost historical issue, a resolution associated with the topmost historical issue. Further, migration context and flow graph based migration control may include executing the resolution to resolve the migration issue, and performing, based on the resolved migration issue, migration of the application from the physical environment to the cloud environment.

Methods and systems for implementing a highly available distributed queue using replicated messages are disclosed. An enqueue request is received from a client at a particular queue host of a plurality of queue hosts. The enqueue request comprises a message and a replica count greater than one. One or more copies of a replication request are sent from the particular queue host to one or more additional queue hosts. The replication request comprises the message. The quantity of copies of the replication request is determined based at least in part on the replica count. An initial replica of the message is enqueued at the particular queue host. One or more additional replicas of the message are enqueued at the one or more additional queue hosts. A quantity of the one or more additional replicas is determined based at least in part on the replica count.

Embodiments of the disclosure provide a method and system for task orchestration. A method may include: providing, by a task master control unit, an execution instruction of a task related to a module in an application container to a node agent service unit in an auxiliary application container bound to the application container, the auxiliary application container sharing a file system with the application container; and executing, by the node agent service unit, a command for completing the task, in response to acquiring the execution instruction of the task.

A technique is described for handling forks in operations mapped to direct access persistent memory (PMEM). In an example embodiment, access by a parent operation of an allocated portion of PMEM is monitored to determine a portion of the allocated PMEM that is in use by the parent operation. In response to a fork call indicating that the parent operation will copy itself to create a child operation, a clone of the portion of allocated PMEM is created to facilitate processing of the child operation. The cloned portion of PMEM can be created just before the child operation is created (i.e., pre-fork) or after the child operation is created (i.e., post-fork). To create the clone post-fork, a user-space page fault notification mechanism can be implemented to detect a next buffer access by the child operation and create the clone in response to the detected access.

The present disclosure is directed to systems and methods for container security using a hopping mechanism. Methods include the steps of selecting a first virtual container associated with one or more software processes; replicating the first virtual container to create a plurality of replicated virtual containers, each of the plurality of replicated virtual containers a duplicate of the first virtual container, and the plurality of replicated virtual containers configured to run synchronously; generating a randomized hopping set that defines a set of replicated virtual containers from the plurality of replicated virtual containers, the randomized hopping set establishing a sequence of the set of replicated virtual containers in which to run the one or more software processes; and running the one or more software processes across the set of replicated virtual containers based on the sequence of the randomized hopping set.

Methods, computer program products, and systems are presented. The methods include, for instance: analyzing resources of an edge device available for computing workloads of a cloud to which the edge device is operatively coupled various communication networks per locations of the edge device, wherein the edge device is mobile. A location of the edge device at an estimated time of delivery of an output of a cloud application is predicted prior to the estimated time of delivery. It is determined that the location of the edge device from the predicting is serviced by a communication network below a threshold connectivity. The cloud has the cloud application installed on the edge device at a current location according to an access permission on the edge device. The edge device continues processing the workloads of the cloud and the output of the cloud application generated.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for registering subscribable sub-states in blockchain are provided. One of the methods includes: obtaining a request for registering one or more sub-states of a state, wherein a registered workflow comprises the state; generating a blockchain contract comprising the one or more sub-states; and deploying the blockchain contract in a blockchain. The deployed blockchain contract is executable to update a current sub-state of the state corresponding to the workflow among the one or more sub-states.

Micro-architectural fault detectors are described. An example of storage mediums includes instructions for receiving one or more micro instructions for scheduling in a processor, the processor including one or more processing resources; and performing fault detection in performance of the one or more micro instructions utilizing one or more of a first idle canary detection mode, wherein the first mode includes assigning at least one component as an idle canary detector to perform a canary process with an expected outcome, and a second micro-architectural redundancy execution mode, wherein the second mode includes replicating a first micro instruction to generate micro instructions for performance by a set of processing resources.

A method for placement of processes in a distributed datacenter is described. The method includes receiving, by a first placement node, a placement request corresponding to a process; determining a load estimation for resources managed by the first placement node and a demand estimation for the process based on a process execution profile for the process; determining whether the placement request can be fulfilled with the resources managed by the first placement node based on the demand estimation of the process and the load estimation of the resources managed by the first placement node; executing the process with the resources managed by the first placement node in response to determining that the placement request can be fulfilled with the resources managed by the first placement node; generating an intermediate score based on the execution; and updating a performance score of the process execution profile based on the intermediate score.

A computing system that provides virtual computing services may generate and manage remote computing sessions between client computing devices and virtual desktop instances hosted on the service provider's network. A computing resource instance manager may monitor connections to and disconnections from a virtual desktop instance during particular time periods, and may apply a resource management policy to determine whether and when to shut down an underlying virtualized computing resource instance following a disconnection (e.g., immediately, after some period of time, or only between certain hours). A storage volume for the virtual desktop instance may be detached during a shutdown. In response to a reconnection request, the virtualized computing resource instance (or another such instance) may be restarted and the storage volume may be reattached. The computing resource instance manager may develop a model for predicting when to shut down or restart an instance based on historical data or machine learning.