Dell Products Inc.

Nisan Haimov

Boris Shpilyuck

Igor Dubrovsky

Maxim Balin

Ofir Ezrielev

Methods and systems for managing the operation of data processing systems are disclosed. To manage the operation of the data processing systems, containerized services may be deployed. Once deployed, desired services may be provided. Prior to deployment, images and metadata used in the deployment may be analyzed. The analysis may reduce threats presented by the deployment of the containerized services. During the analysis, the integrity of the images and metadata may be verified, and the privilege of containerized services based on the metadata and images may be reviewed.

Managing deployment of services to data processing systems

Methods and systems for managing operation of a deployment are disclosed. The deployment may be managed by employing redundant devices within the deployment. The redundant devices may serve to replace operation of failed devices. Despite replacement of operations of a failed device, the redundant device may not have similar functionality as the failed device. To make the functionality similar to the failed device, a correction factor may be applied to the redundant device. In applying the correction factor, the output from the redundant device may be expected to match output from the failed device. In matching output from the failed device, the redundant device may operate in place of the failed device.

Employing redundant devices in a deployment

Methods and systems for prioritizing resources are disclosed. The resources in a deployment may be prioritized by training machine learning models for use in repairing impaired devices with failures of operation. The trained machine learning models may learn differences in operation. Differences in operation may pertain to output between each device of the set of devices and the digital twin in the deployment. The differences in operation may be used to prioritize a list of impaired devices that may be repaired. The prioritized list of impaired devices may be followed when available resources may be expended to repair the impaired devices.

Prioritizing resources for addressing impaired devices

Methods and systems for managing operation of a deployment are disclosed. The operation of the deployment may be managed by simulating devices with a digital twin within the deployment. The digital twin may serve to replace operation of failed devices. By replacing failed devices with the digital twin, cooperative processes requiring participation of the failed devices may be continued while the failed devices are unable to participate.

Simulating devices with a digital twin in a deployment

The technology described herein is directed towards combining multiple sidecar (e.g., Envoy-based) proxies into a single sidecar or reduced number of sidecars for use in association with a service. Described is identifying sidecars for merging, grouping by version compatibility, and determining their functions and configuration data. Any conflicts in the configuration data are resolved. A merged sidecar is built by combining functional code and configuration data. The merged sidecar is deployed along with its relevant service, e.g., deployed as a container in a Kubernetes environment. The merging facilitates reduction of resource utilization by having only a merged sidecar, instead of multiple sidecars, support a service.

Cloud proxy-based sidecar coalescence

Methods and systems for managing the operation of data processing systems are disclosed. To manage the operation of the data processing systems, access control standards for software may be enforced during development and/or deployment of software. The access control standards may indicate the extent of access controls for data that are to be in place for various pieces of software. The access control standards may also indicate a level of consistency in the sources of truth for permissions enforced by the access controls.

Access control management for systems

Methods and systems for managing operation of a distributed system comprising a data center and edge devices. The operation of the distributed system may be managed by monitoring the edge devices. The edge devices may be monitored by identifying the health state of an edge device. The health state of the edge device may be identified by collecting data from operation of similar edge devices and the edge device and comparing the differences in between the data. If the differences between the data from the operation of the similar edge devices and operation of the edge device may exceed criteria for deviation, then the edge device may be determined to be in an unhealthy health state.

Identifying the health state of edge devices

Methods and systems for managing trust in distributed are disclosed. To manage trust, a behavior and characteristic based trust model may be used. The trust model may utilize similarity between devices and public activity of devices over time to ascertain levels of trust that should be afforded devices of the distributed system. The levels of trust may be used to ascertain whether requests from devices of the distributed systems should be honored, or rejected. The trust models may facilitate establishment of trust in environments where physical intrusion based threats are present.

Trust management in distributed systems

Methods and systems for device shutdown in a deployment are disclosed. Device shutdown may be considered to conserve energy and simplify processes in a deployment. To conserve energy and simplify processes, all devices within a deployment may undergo a redundancy analysis and qualification analysis. The redundancy analysis may produce lists of redundant and non-redundant devices. All redundant devices may be candidates for device shutdown. Next, qualification analysis may qualify devices for shutdown by energy consumption and output data accuracy and uncertainty qualification. Devices that may not meet prescribed qualifiers may also be candidates for shutdown. With all devices that may be candidates for shutdown assembled in a list, device shutdown may commence in the deployment.

Device shut down in a deployment

A system can receive, at an integration and deployment component, a changeset for an updated microservice and an identifier of a user account that is configured to access the updated microservice, wherein a current version of the microservice is deployed to a service mesh that comprises a group of microservices. The system can instantiate the updated microservice to the service mesh. The system can update routing rules for the service mesh to indicate that any traffic in the service mesh that is associated with the user account and that is directed to the current version of the microservice is to be routed to the updated microservice. The system can, in response to receiving traffic determined to be associated with the user account and directed to the current version of the microservice, route the traffic to the updated microservice instead of routing the traffic to the current version of the microservice.

Isolated environment provisioning in service mesh-based microservices systems

A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: identifying a plurality of process flows; identifying a plurality of microservices associated with each of the plurality of process flows; mapping each of the plurality of microservices associated with each of the plurality of process flows; calculating a centrality value for each of the plurality of microservices associated with each of the plurality of process flows based upon the mapping; and, testing at least some of the plurality of microservices based upon the centrality value for each of the plurality of microservices.

Smart microservice testing based on centrality prioritization

Methods and systems for managing pods and containers that provide computer implemented services are disclosed. The pods and containers may be managed to improve efficiency of resource use and reduce exposure to threats to operation of systems that host the pods and containers. To ascertain how to manage the pods and containers, the pods and containers may be monitored and analyzed. The results of the monitoring and analyzation may be used to select how to change the pods and containers over time.

Resource allocation management in distributed systems

A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: identifying a plurality of process flows, each of the plurality of process flows having a trace identifier and a corresponding weighted priority; identifying a plurality of microservices associated with each of the plurality of process flows; mapping each of the plurality of microservices associated with each of the plurality of process flows; and, calculating a centrality value for each of the plurality of microservices associated with each of the plurality of process flows based upon the mapping.

Data center monitoring and management operation including microservice centrality calculation operation

A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: identifying a plurality of process flows executing on a system, each of the plurality of process flows having a trace identifier and a corresponding weighted priority; identifying a plurality of microservices associated with each of the plurality of process flows; determining when the system does not have enough system resources to execute all of the plurality of process flows; and, automatically scaling each of the plurality of microservices associated with each of the plurality of process flows when the system does not have enough system resources to execute all of the plurality of process flows.

Data center monitoring and management operation including a microservice autoscaling operation

A system can receive a changeset for an updated microservice and an identifier of a user account, wherein the updated microservice is relative to a current version of a microservice. The system can instantiate the updated microservice. The system can, in response to determining that a first instance of a dependent microservice depends on the current version of the microservice, instantiate a second instance of the dependent microservice. The system can update routing rules for the service mesh to indicate that any traffic that is associated with the user account and that is directed to the current version of the microservice is to be routed to the updated microservice, and any traffic directed from the updated microservice to the first instance of the dependent microservice is to be routed to the second instance of the dependent microservice.

Growing community of inventors

Beer Sheva, Israel

Nisan Haimov