Abstract: Techniques described herein relate to a method for deploying workflows.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, a weighted rank order of causal services associated with a service impairment; obtaining contextual information associated with the weighted rank order of causal services; identifying top causal services based on the weighted rank order of causal services; generating, using a causal symbolic engine, a ranked order of top root causes based on the top causal services and the contextual information; selecting remediation profiles associated with the top root causes; executing remediation profiles in ranked order of the top root causes; making a determination that the remediation profiles were successful; and in response to the determination: logging the service impairment and notifying a user associated with the service impairment.

Abstract: Embodiments of systems and methods for enhanced drift remediation with causal methods and online model modification are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect drift in an Artificial Intelligence (AI) or Machine Learning (ML) model configured to make a prediction or a causal reasoning graphical or structural inference based upon input data, identify a root cause of the drift, and tag the input data with an indication of the root cause.

Abstract: Techniques described herein relate to a method for distributed data management. The method may include obtaining data descriptors for an application executing on a data host, performing a dataset policy analysis using the data descriptors to determine a data placement for a dataset associated with the application using a global name repository, performing, based on the data policy analysis, the data placement, and based on the data placement, updating the global name repository.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, a DMC environment management request from a user, whereas the DMC environment management request is associated with scheduling an application in the DMC environment; and in response to obtaining the request: identifying target domains for tasks associated with the application based on the request; selecting scheduling policies for each target domain; obtaining fingerprints of previously provisioned applications associated with the request; performing case based reasoning using the fingerprints to generate scheduling packages for the target domains; sending the scheduling packages to local controllers associated with the target domains; obtaining application information from the local controllers; and providing the application information to the user.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, a DMC environment management request from a user; and in response to obtaining the request: making a first determination that the DMC environment management request is a create request, and the create request is associated with provisioning an application in the DMC environment; in response to the first determination: generating scheduling packages associated with target domains of the DMC environment based on the create request; sending the scheduling packages to local controllers associated with the target domains; obtaining application information from the local controllers; and providing the application information to the user.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by an endpoint controller associated with a device, scheduling assignments and a provisioning command package from a local controller; in response to obtaining the scheduling assignments and the provisioning command package: making a determination that the device is available for the scheduling assignments; in response to the determination: modifying configuration of the device based on the scheduling assignments and generating configuration information; executing the provisioning commands included in the provisioning command package to instantiate tasks included in the scheduling assignments; instantiating monitoring services to collect monitoring information associated with the device and the tasks; and sending the monitoring information and configuration information to the local controller.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, a set of correlated services associated with an anomaly; obtaining a service dependency graph associated with the set of correlated services; generating a causal variance for each service using the correlated services and the service dependency graph; generating a weighted rank order of causal services based on the causal variance associated with each service, and the weighted rank order of causal services includes a portion of the services associated with an application associated with the anomaly; and performing remediation based on the weighted rank order of the causal services.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes normalizing, by a local controller associated with an DMC domain, task resource demand dimensions for each task associated with a scheduling job; summing the resource demand dimension for each task to generate resource demand vectors; classifying tasks based on priority; sorting tasks based on associated resource demand vectors; obtaining critical path, earliest start time, and latest start time associated with each task; sorting tasks based on critical path and earliest start time; and generating scheduling assignments based on the priority, capacity of devices in a final candidate list, resource demand vectors, earliest start time, and the critical path.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes decomposing, by a local controller associated with an DMC domain, a service dependency graph associated with a scheduling job; assigning normalized compute units and normalized network units to tasks included in the service dependency graph; generating a Q-table using the service dependency graph and reinforcement Q-learning; calculating a critical path and a max learned path using the Q-table and the service dependency graph; calculating the earliest start time and the latest start time for each task using the service dependency graph and the max learned path to obtain a plurality of earliest start time and latest start time pairs for each task; and generating scheduling assignments using the plurality of earliest start time and latest start time pairs for each task.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, service level objective (SLO) metrics; applying the SLO metrics to a predictive anomaly detection transformer to perform anomaly detection; making a first determination that an anomaly is detected; in response to the first determination: attempting basic remediation to resolve the anomaly; making a second determination that the basic remediation is unsuccessful; in response to the second determination: making a third determination that the anomaly is associated with a silent failure; and in response to the third determination: performing service impairment isolation to obtain a collection of services correlated to the anomaly; and performing root cause analysis to identify causal services.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by an endpoint controller associated with a device, an initial resource buffer from a local controller; in response to obtaining the initial resource buffer: maintaining the initial resource buffer during task provision for the device; obtaining device metrics based on performance of tasks on the device; making a determination that a resource buffer change event is identified; and in response to the determination: updating the initial resource buffer based on the resource buffer change event.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes identifying, by a global controller, a load management prediction event; in response to identifying the load management prediction event: obtaining offline data from local controllers associated with a plurality of DMC domains of the DMC environment; generating load management predictions using the offline data; adjusting local controller scheduling policies based on the load management predictions; adjusting global controller scheduling policies based on the load management predictions; making a first determination that the load management predictions require infrastructure adjustments; and in response to the first determination: initiating infrastructure capacity adjustment based on the load management predictions.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, a weighted rank order of causal services associated with a service impairment; obtaining contextual information associated with the weighted rank order of causal services; identifying top causal services based on the weighted rank order of causal services; generating, using a causal symbolic engine, a ranked order of top root causes based on the top causal services and the contextual information; selecting remediation profiles associated with the top root causes; executing remediation profiles in ranked order of the top root causes; making a determination that the remediation profiles were successful; and in response to the determination: logging the service impairment and notifying a user associated with the service impairment.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes identifying, by a local controller associated with an DMC domain, a domain scheduling event associated with a scheduling job; and in response to identifying the domain scheduling event: identifying a candidate list of devices of the DMC domain to schedule tasks associated with the scheduling job based on a location and service level objectives; refining the candidate list of devices based on device configuration requirements, device management requirements, and security requirements to generate a final candidate list; scheduling tasks to devices using the final candidate list; generating scheduling assignments and provisioning command packages based on the scheduled tasks; providing the scheduling assignments and the provision command packages to the devices; and updating a graph based on the scheduling assignments.

Abstract: Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, an DMC environment management request from a user, and the DMC environment management request is associated with scheduling an application in the DMC environment; and in response to obtaining the request: providing acknowledgment that the request is received to the user; obtaining an order identifier and a manifest from the user; providing a correlation identifier associated with the request to the user; parsing the manifest to extract application deployment information; scheduling the application to target domains of the DMC based on the application deployment information; and providing the user with the correlation identifier, a success indicator, and application information.

Abstract: Techniques described herein relate to a method for using pipeline data for deploying workflows. The method may include determining that a pipeline testing trigger occurred for a workflow; decomposing a pipeline testing manifest of the workflow; generating a testing execution plan using the decomposed workflow; adding instrumentation to the testing execution plan; determining that the instrumented testing execution plan is valid; deploying computing devices within a CI/CD pipeline ecosystem for performing the instrumented testing execution plan; capturing deployment logs; initiating telemetry capture; executing pipeline testing of the workflow based on the instrumented testing execution plan; generating a pipeline deployment information set based on the pipeline testing; and providing the pipeline deployment information set to an orchestrator of a production device ecosystem.

Abstract: Techniques described herein relate to a method for optimizing workflow execution. The method may include receiving an event notification at a service controller, wherein the event notification is associated with a workflow deployed in a device ecosystem; performing, based on receiving the event notification, a workflow reconfiguration action comprising: providing a first workflow portion to a first platform controller in a first domain in the device ecosystem; transmitting a workflow reconfiguration action notification to a second platform controller in a second domain of the device ecosystem; identifying, by the second platform controller and in response to receiving the workflow reconfiguration action notification, a data transfer optimization action associated with data to be transmitted from the second domain to the first domain and used during execution of the first workflow portion; and transmitting the data from the second domain to the first domain using the data transfer optimization action.

Abstract: Self-provisioning a computer system is illustrated. Code in a secure base activation image implements an auto-connection service at the computer system. The auto-connection service attempts to perform a local activation by attempting to determine that a private port is open and using the private port, initiating an identification and attestation process with an activation service. The auto-connection service performs a remote activation by determining that the private port is closed, defaulting activation to a public port, and using the public port, initiating an identification and attestation process with the activation service.