Abstract: Example techniques for execution of functions by clusters of computing nodes are described. In an example, if a cluster does not have resources available for executing a function for handling a service request, the cluster may request another cluster for executing the function. A result of execution of the function may be received by the cluster and used for handling the service request.

Abstract: Example implementations relate to proactively protecting service endpoints based on deep learning of user location and access patterns. A machine-learning model is trained to recognize anomalies in access patterns relating to endpoints of a cloud-based service by capturing metadata associated with user accesses. The metadata for a given access includes information regarding a particular user that initiated the given access, a particular device utilized, a particular location associated with the given access and specific workloads associated with the given access. An anomaly relating to an access by a user to a service endpoint is identified by monitoring the access patterns and applying the machine-learning model to metadata associated with the access. Based on a degree of risk to the cloud-based service associated with the identified anomaly, a mitigation action is determined. The cloud-based service is proactively protected by programmatically applying the determined mitigation action.

Abstract: Embodiments described herein are generally directed to a creation of an HA private cloud gateway based on a two-node HCI cluster with a self-hosted HMS. According to an example, a request to register a private cloud to be supported by on-premises infrastructure is received by a SaaS portal, which causes a base station to discover servers within the on-premises infrastructure. The base station is then instructed to prepare a server as a deployment node for use in connection with creation of a cluster of two HCI nodes of the servers to represent the HA private cloud gateway, including installing a seed HMS on the deployment node. The base station is further instructed to cause the seed HMS to create the cluster, install a self-hosted HMS within the cluster to manage the cluster, register the cluster to the self-hosted HMS, and finally delete the seed HMS from the deployment node.

Abstract: A system (e.g., one or more computer systems) of synchronous orchestration may store and/or replay one or more operations of a synchronous orchestration operation if one or more issues impair the synchronous orchestration operation. For example, the system may replay and/or reproduce a task of the synchronous orchestration operation after an amount of time transpires and/or after receiving a notification that indicates an impairment has been overcome. For instance, a replay and/or reproduction process to begin from a point where an orchestration layer was impaired. In one or more embodiments, one or more efforts in repeating an entire synchronous orchestration operation may be reduced.

Abstract: In some examples, a method includes: (a) reading a manifest file containing information regarding an application running on one or more Virtual Machines (VMs), wherein the information includes application topology, credentials, and configuration details; (b) receiving instructions to re-deploy the application from the one or more VMs to a container environment; (c) discovering, based on information in the manifest file, application consumption attributes including attributes of storage, computer, and network resources consumed by a workload of the application; (d) deploying the application on the container environment to produce a containerized application; (e) copying configuration details from the manifest file to the containerized application; (f) migrating, based on information in the manifest file and the discovered application consumption attributes, stateful data to the containerized application; and (g) validating the containerized application functionality.

Abstract: A system to facilitate a container orchestration cloud service platform is described. The system includes a controller to manage Kubernetes cluster life-cycle operations created by each of a plurality of providers. The controller includes one or more processors to execute a controller micro service to discover a provider plugin associated with each of the plurality of providers, and perform the cluster life-cycle operations at a container orchestration platform as a broker for each of a plurality of providers.

Abstract: In some examples, a system may include a processing resource and a memory resource. The memory resource may store machine-readable instructions to cause the processing resource to create a migration plan, defining characteristics of a migration of an application from a native computing data center to a computing cloud of a plurality of distinct candidate computing clouds, based on: a first migration constraint for the application determined from an analysis of historical behavior of the application executed on the native computing data center; a second migration constraint for the application determined from an analysis of administrator cloud migration preferences for the application; and a cloud computing characteristic of each of the plurality of distinct candidate computing clouds.

Abstract: A system and method for automated resolution of events in a computing environment is provided. Problem types are identified from the events which are associated with configuration items (CIs) at issue. Further, domains of the CIs at issue are identified. Domains represent types of the CIs at issue. Existence of diagnosis and resolution sequences is checked which is based on identified problem types and domain associated with the CI types. Thereafter, diagnosis and resolution sequences are fetched, where sequences fetched at a first instance are at least in part updated with one or more new sequences. Fetched sequences are executed iteratively such that a next step of the executed diagnosis and resolution sequence is based on an output of a first step of the executed diagnosis and resolution sequence.

Abstract: Examples of error remediation in SaaS portals is disclosed. In an example, activity data in a SaaS portal is monitored, where the SaaS portal is from amongst a plurality of SaaS portals grouped in a portal group. The activity data includes a record of events associated with a service request processed by the SaaS portal, an alert notification on occurrence of an error in the SaaS portal, and user information relating to credentials provided by a user accessing the SaaS portal. A runtime error in the SaaS portal may be detected based on the monitored activity data. The runtime error is based on faults in a service or an Application Programming Interface (API) associated with the SaaS portal, a security vulnerability, and non-compliance with a configuration policy governing the SaaS portal. A remediation measure for the runtime error is determined and implemented in the portal group.

Abstract: In some examples, a method includes identifying, via the use of a Representational State Transfer (REST) Application Programming Interface (API) call, a modification of persistent data for a Cloud Management Platform (CMP); storing, in a persistent log for the CMP, information about the data modification, including an operation that modified the data, a component of the CMP that modified the data, and the time of modification; determining, as a result of a failure of the CMP, a restoration point for the CMP based on the persistent log; and restoring the CMP to the determined restoration point using an independent restoration system of the component that modified the data.

Abstract: A system (e.g., one or more computer systems) of synchronous orchestration may store and/or replay one or more operations of a synchronous orchestration operation if one or more issues impair the synchronous orchestration operation. For example, the system may replay and/or reproduce a task of the synchronous orchestration operation after an amount of time transpires and/or after receiving a notification that indicates an impairment has been overcome. For instance, a replay and/or reproduction process to begin from a point where an orchestration layer was impaired. In one or more embodiments, one or more efforts in repeating an entire synchronous orchestration operation may be reduced.

Abstract: In some examples, a method includes: (a) reading a manifest file containing information regarding an application running on one or more Virtual Machines (VMs), wherein the information includes application topology, credentials, and configuration details; (b) receiving instructions to re-deploy the application from the one or more VMs to a container environment; (c) discovering, based on information in the manifest file, application consumption attributes including attributes of storage, computer, and network resources consumed by a workload of the application; (d) deploying the application on the container environment to produce a containerized application; (e) copying configuration details from the manifest file to the containerized application; (f) migrating, based on information in the manifest file and the discovered application consumption attributes, stateful data to the containerized application; and (g) validating the containerized application functionality.

Abstract: In one or more embodiments, a system (e.g., one or more computer systems) of synchronous orchestration may store and/or replay one or more operations of a synchronous orchestration operation if one or more issues impair the synchronous orchestration operation. For example, the system may replay and/or reproduce a task of the synchronous orchestration operation after an amount of time transpires and/or after receiving a notification that indicates an impairment has been overcome. For instance, a replay and/or reproduction process to begin from a point where an orchestration layer was impaired. In one or more embodiments, one or more efforts in repeating an entire synchronous orchestration operation may be reduced.

Abstract: Example implementations relate to executing software on a remote computing system. In an example, an apparatus includes a memory and a processor to execute instructions from the memory to provide software to a first storage medium, cause the remote storage medium to replicate the software to a second storage medium, and cause the remote computing system to retrieve the software from the second storage medium over a network and to execute the software. In an example, the second storage medium is closer to the remote computing system than the first storage medium.

Abstract: In one or more embodiments, a system (e.g., one or more computer systems) of synchronous orchestration may store and/or replay one or more operations of a synchronous orchestration operation if one or more issues impair the synchronous orchestration operation. For example, the system may replay and/or reproduce a task of the synchronous orchestration operation after an amount of time transpires and/or after receiving a notification that indicates an impairment has been overcome. For instance, a replay and/or reproduction process to begin from a point where an orchestration layer was impaired. In one or more embodiments, one or more efforts in repeating an entire synchronous orchestration operation may be reduced.

Abstract: In one implementation, a system for providing resource information can comprise a spider engine, a discovery engine, an ontology engine, and a publication engine. The spider engine can crawl a resource provider. The discovery engine can discover a resource of a resource provider. The ontology engine can map the resource to an ontology term. The publication engine can provide the ontology term as part of a resource directory. In another implementation, a method for providing resource information can comprise configuring a crawler with an ontology and an interface associated with a resource provider, crawling a network of storage mechanisms, mapping a resource of the network of storage mechanisms to the ontology, and providing a directory of available resources.