An embodiment of the invention may include a method, computer program product and system for deployment of microservices within a shared pool of configurable computing resources. An embodiment may include creating a dependency map for a plurality of microservices of an application deployed on the shared pool of configurable computing resources. An embodiment may include identifying attributes, with associated values, for each microservice of the plurality of microservices and identifying eligible deployment locations within the shared pool of configurable computing resources. An embodiment may include creating a bipartite graph based on the plurality of microservices and the identified eligible deployment locations. An embodiment may include applying bipartite matching to the shared pool of configurable computing resources based on the created bipartite graph. An embodiment may include, based on the applied bipartite matching, relocating one or more microservices within the shared pool of configurable computing resources.

Disclosed aspects include managing asset deployment for a shared pool of configurable computing resources having a set of virtual machines associated with a deployment server. A set of deployment topology data is collected for the shared pool of configurable computing resources. Using the set of deployment topology data, it is determined to establish a dynamic management server communicatively connected with both the deployment server and the set of virtual machines. Based on the set of deployment topology data, the dynamic management server is established communicatively connected with both the deployment server and the set of virtual machines.

Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may need to operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. Similarly, the managed system may need access to certain hardware resources (e.g., and also software resources such as drivers, firmware, etc.) to provide the desired computer implemented services. To improve the likelihood of the computer implemented services being provided, the managed systems may be managed using a subscription based model. The subscription model may utilize a highly accessible service to obtain information regarding desired capabilities (e.g., a subscription) of a managed system, and use the acquired information to automatically configure and manage the features and capabilities of the managed systems by powering and depowering select components as well as deploying dynamically composed management entities.

A method of selectively allocating a plurality of deployment units among a plurality of clouds. The method can include identifying a first context of a first deployment unit of a workload and identifying a second context of a second deployment unit of the workload. Based on the first context, a first of the plurality of clouds that satisfies at least one requirement indicated by the first context can be identified and the first deployment unit can be automatically allocated to the first cloud. Based on the second context, a second of the plurality of clouds that satisfies at least one requirement indicated by the second context can be identified, wherein the first cloud does not satisfy the requirement indicated by the second context, and the second deployment unit can be automatically allocated to the second cloud.

In one embodiment, a method according to the present disclosure includes receiving a topology change advertisement at a remote core edge node and performing a network address information removal operation. The topology change advertisement is received from a core edge node that is in communication with an access network. The topology change advertisement indicates that a topology change has occurred in the access network. The network address information removal operation removes network address information stored by the remote core edge node. The network address information is used by the remote core edge node in participating in communications with the core edge node.

A method to enable defining of a profile of a service through manipulation of graphical representations of abstractions of resources in a data center is disclosed. The profile of the service is accessed. A graphical representation of an abstraction of the first resource type is presented. A graphical representation of an abstraction of a second resource type is presented. A manipulation of the graphical representation of the abstraction of the second resource type is detected with respect to the graphical representation of the abstraction of the first resource type. Based on the manipulation, a correspondence between the abstraction of the second resource type and the profile of the service is identified and a relationship between the abstraction of the second resource type and the abstraction of the first resource type is identified. The profile of the service is updated to include information identifying the correspondence and the relationship.

A network element (NE) in a network, comprising a memory configured to store time-based traffic engineering (TE) information associated with network resource reservations on a link attached to the NE in a series of time intervals each having a predetermined start time and a predetermined end time, and a processor coupled to the memory and configured to reserve, at a first current time, a network resource for a temporal tunnel service (TTS) on the link to carry traffic during a scheduled time interval subsequent to the first current time, wherein the scheduled time interval comprises a scheduled start time and a scheduled end time, and update, at the first current time, the time-based TE information in the scheduled time interval according to the network resource reserved to produce a first updated TE information in the scheduled time interval.

Systems and methods described herein for automatic limit service increase in a multi-tenant cloud infrastructure environment. The systems and methods described herein provide for automatic approval of limit service increase requests that are either automatically generated based upon a tenant's usage of resources within the cloud infrastructure environment, or are received via, e.g., a user portal. Such automatic approval can be based upon a set of maximal limits that are computed based upon the tenant's current usage, level of subscription, or hard limit values.

Techniques are described herein for deploying, monitoring, and modifying network topologies comprising various computing and network nodes deployed across multiple workload resource domains. A deployment system may receive operational data from a network topology deployed across multiple workload resource domains, such as public or private cloud computing environments, on-premise data centers, and the like. The operational data may be provided to a trained machine-learning model, and output from the trained model may be used, along with constraint inputs and resource inventories of the workload resource domains, to determine updated topology models which may be deployed within the workload resource domains.

A management apparatus includes: a service information acquisition unit that acquires resource information indicating an available resource of a computer, and acquires service information including a target sensor that acquires data to be used by a target service, a required resource for the target service, and a target controller that executes control by the target service; and an arrangement measurement unit that set a computer that covers the required resource by the available resource as a candidate computer, calculates, for a candidate course, which is a combination of an input course from the target sensor to the candidate computer and an output course from the candidate computer to the target controller, a total cost for causing data to be used by the target service to flow, by considering a path through which the data to be used by the target service is caused to flow by a co-existing service.