Question

How did AT&T manage the technology–business–policy framework?

Answer 1

AT&T, ECOMP Policy Framework: Capturing Network Intelligence in Policies:

ECOMP is accountable for the look, creation, and life-cycle management of virtualized network functions (VNFs). in a veryll|one amongst|one in every of} its goals is to try and do this in a versatile, dynamic, policy-driven manner – belongings users dynamically management ECOMP’s behavior while not dynamical the system package. ECOMP’s policy element permits North American countries to specific, interpret and assess policies, so pass them on to alternative ECOMP elements or network components for social control.

Policies manage numerous aspects of ECOMP’s behavior, including:

1.Service style example: constraints concerning wherever to put VNFs
2.VNF modification management example: however package rollouts ought to be scheduled across VNFs and what health checks ought to be performed to validate changes
3. Management of the behavior of ECOMP elements – e.g., however and once ECOMP ought to collect information, and the way long ECOMP ought to retain that information

ECOMP’s policy framework consists of the subsequent modules:

Policy creation: Enables policies to be specified by services designers and network operators via computer program and arthropod genus
Policy evaluation: Evaluates/executes applicable policies reactively (response to a query) and proactively (evaluates a policy and triggers actions)
Policy call distribution: Distributes policy selections to be implemented in alternative ECOMP elements
Policy validation: Validates policies, designed to attenuate the danger of introducing unhealthy policies into the ECOMP platform.
The policy framework empowers operators and designers to manage ECOMP’s behavior. However, the domain information captured in ECOMP policies is usually distributed across several network operators and engineers, creating it a challenge to collate. Machine learning involves the rescue here by serving to service suppliers mechanically learn policies. within the case of management loops, machine learning permits signatures and responses to be mechanically captured.

When the software-centric network effort began, we have a tendency to had already been adopting cloud technology, totally on IT or company applications. Cloud technology provided the power to manage numerous workloads of applications dynamically, including:

1.Creating Virtual Machines (VMs) on hardware in close to period of time
2.Assigning applications and workloads to VMs in close to period of time
3.Dynamically moving applications and dependent functions to totally different VMs across numerous locations
4.Dynamically dominant resources on the market to applications (CPU, memory, storage).

AT&T has outlined 3 key objectives across our network virtualization initiatives:
1.Improve cycle time
2. Open our network
3.Increase potency
Policy: Modifiable Rules, Assertions and/or Conditions to change period of time higher cognitive process on corrective actions and configuration changes within the software-centric network system.

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