Methods and systems for implementing division of process resources of running processes into individually locked partitions, and indirect mapping of keys to process resources to locks of each partition, are provided. In computing systems implementing concurrent processing, applications may generate and destroy concurrently running processes with high frequency. Real-time security monitoring may cause the computing system to run monitoring processes collecting large volumes of data regarding system events occurring in context of various other processes, causing threads of processes of the security monitoring application to make frequent write access and read access to resources of those processes in memory. Indirect mapping of lock acquisition across locks provides scalable alleviation of lock contention and thread blocking that result from computational concurrency, while handling read and write requests which arise at unpredictable times from kernel-space monitoring processes, and which request unpredictable resources of monitored user-space processes.

The current document is directed to methods and systems that automatically instantiate complex distributed applications by deploying distributed-application instances across the computational resources of one or more distributed computer systems and that automatically manage instantiated distributed applications. Automatic deployment of multiple instances of a distributed application across computational resources, such as distribution of microservices of a microservice-based application across one or more distributed computer systems, and scaling of instantiated distributed applications are computationally difficult optimization problems that are not amenable to traditional centralized approaches. The current document discloses decentralized, distributed automated methods and systems that instantiate and manage distributed applications. Reinforcement-learning-based agents are installed within the computational resources of one or more distributed computer systems. Distributed-application instances are initially distributed to one or more agents. The agents then exchange distributed-application instances among themselves in order to locally optimize the set of distributed-application instances that they each manage.

Methods, apparatus, systems, and articles of manufacture are disclosed to facilitate content generation for cloud computing platforms. An example apparatus includes model definition circuitry to generate model definitions representative of one or more undefined target system objects in a target system, and generate instructions that cause a developer environment to provide the model definitions during a generation of content files, generation order circuitry to generate a processing order of the content files, the content files having one or more defined model objects, and object processing circuitry to convert the one or more defined model objects to defined target system objects for deployment and execution at the target system.

In some embodiments, a computer cluster system comprises a plurality of nodes and a software package comprising a user interface and a kernel for interpreting program code instructions. In certain embodiments, a cluster node module is configured to communicate with the kernel and other cluster node modules. The cluster node module can accept instructions from the user interface and can interpret at least some of the instructions such that several cluster node modules in communication with one another and with a kernel can act as a computer cluster.

The present invention is to solve the breaking of memory consistency caused by disturbance of packet arrival order in an environment in which a plurality of computers are interconnected via a plurality of data links and the plurality of computers perform communication synchronization by MBCF with each other. A transmission-side process includes a transmission number-counting unit that counts the number of transmission of the operation request packet for each reception-side process and attaches a count number before or after counting-up of the operation request packet to the operation request packet, a reception-side process includes a reception number-counting unit that counts the number of reception of the operation request packet for each transmission-side process, and a transmission destination computer performs processing of the operation request packet when a count number of the reception number-counting unit and the count number attached to the operation request packet are consecutive.

The techniques described herein provide a system for executing a service that helps cloud resource providers manage unused cloud resources. Moreover, the service helps cloud resource consumers identify an optimal cloud platform to select for execution of an application. The service aggregates cloud resource information from multiple cloud providers and stores the cloud resource information in a data structure. The service then accesses the data structure to generate cloud resource offerings that can be published for review by different consumers. This process enables the consumers to see and compare cloud resource information, aggregated from multiple different cloud providers, in a single place (e.g., a complete and comprehensive user interface view into cloud resource information). More importantly, a consumer can make an efficient and informed decision as to which cloud provider and cloud platform to use for execution of an application.

One example method includes receiving an orchestration automation request for an asset, identifying an ethics rule that applies to the asset, comparing the ethics rule to asset values contained in an AI ethics datastore, based on the comparing, identifying a list of assets that conform to the ethics rule, and when the asset appears in the list of assets that conform to the ethics rule, automatically placing the asset at an entity of a computing infrastructure.

A method for selective performing a validation in one or more technical operations by a cloud based validation framework is provided. The method includes identifying a job task to be performed, identifying technical operations associated with the job task; receiving user configurable input data for performing validation on at least one technical operation associated with the job task; and submitting the user configurable input data into the cloud network based validation framework. The method further includes determining, by the cloud network based validation framework, at least one technical operation specified for performing a validation function among the technical operations; generating a dictionary file for the at least one technical operation specified for performing the validation function; and performing the validation function specified by the dictionary file.

The disclosure relates to processing application programming interface (API) requests. Embodiments include receiving, at an API wrapper, from a first caller, a first call to an API and sending the first call to the API. Embodiments include receiving, by the API wrapper, from one or more second callers, a second one or more calls to the API prior to receiving a response from the API to the first call. Embodiments include receiving, by the API wrapper, the response from the API to the first call and responding to the first call from the first caller with the response from the API to the first call. Embodiments include responding, by the API wrapper, to the second one or more calls from the one or more second callers with the response from the API to the first call without sending the second one or more calls to the API.

An example method of creating an autonomous cluster of hosts in a virtualized computing system includes: enabling, by a virtualization management server executing a cross cluster control plane (xCCP), an infravisor in a seed host of the hosts, the infravisor a component of a hypervisor executing on the seed host; running, by the infravisor, a cluster control plane (CCP) pod on the seed host executing a CCP; providing, by the infravisor, a CCP configuration to the CCP pod; applying, by an initialization script of the CCP pod, the CCP configuration to the CCP to create the autonomous cluster having the seed host as a single node thereof; and extending the autonomous cluster with remaining hosts of the hosts other than the seed host as additional nodes thereof, the CCP applying a cluster personality to each of the remaining hosts derived from the seed host.