Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.

Abstract: Novel tools and techniques are provided for implementing intent-based multi-tiered orchestration and automation. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a macro orchestrator might send, to a micro orchestrator among a plurality of micro orchestrators, the received request for network services, where the macro orchestrator automates, manages, or controls each of the plurality of micro orchestrators, while each micro orchestrator automates, manages, or controls a plurality of domain managers and/or a plurality of network resources.

Abstract: Novel tools and techniques are provided for implementing intent-based orchestration using network parsimony trees. In various embodiments, in response to receiving a request for network services that comprises desired characteristics and performance parameters for the requested network services without information regarding specific hardware, hardware type, location, or network, a computing system might generate a request-based parsimony tree based on the desired characteristics and performance parameters. The computing system might access, from a datastore, a plurality of network-based parsimony trees that are each generated based on measured network metrics, might compare the request-based parsimony tree with each of one or more network-based parsimony trees to determine a fitness score for each network-based parsimony tree, and might identify a best-fit network-based parsimony tree based on the fitness scores.