Nokia BL0-220 Nokia Bell Labs Distributed Cloud Networks Exam Practice Test

Answer : B

On-Boarding of a Network Service requires both NS and NF templates. NS stands for Network Service, which is a logical grouping of network functions and resources that provide a specific functionality or service to the end user. NF stands for Network Function, which is a software component that performs a specific task or function within the network. Templates are files that describe the characteristics, requirements, and dependencies of network services and network functions. On-Boarding is the process of registering and validating network services and network functions in the cloud platform, so that they can be instantiated and managed.

Nokia Bell Labs 5G Professional Certification - Distributed Cloud Networks, Unit 5: New Services Automation, slide 7

Module by Module - Self Study Note Guide, DC5.1-- New Services Automation, page 19

On-boarding a Network Service typically involves Network Service (NS) and Network Function (NF) templates. NS templates define the overall structure and requirements of a network service, including its composition of various NFs and their interconnections. NF templates specify the configurations for individual network functions that are part of the service. Together, they enable the automated deployment and management of complex network services in a standardized manner.

Answer : A, C

Cloud resource management provides management of the resources quota and the ability to scale resources up and down. Resource quota is the limit on the amount of resources that a tenant can use in a cloud environment, such as CPU, memory, storage, network, etc. Resource quota helps to prevent overconsumption of resources by a single tenant and to ensure fair allocation of resources among multiple tenants. The ability to scale resources up and down means that the cloud can dynamically adjust the amount of resources allocated to a tenant based on the demand and availability. Scaling resources up and down helps to optimize the performance and efficiency of the cloud, as well as to reduce the cost and waste of resources.Reference:Nokia Bell Labs Distributed Cloud Networks,Cloud Resource Planning

Answer : B

Multi-tenancy network connectivity provides dedicated resources throughnetwork slicing. Network slicing is a technique that allows operators to create multiple logical networks over a shared physical infrastructure. Each network slice can have its own characteristics, such as bandwidth, latency, security, and quality of service, to meet the specific requirements of different applications and customers. Network slicing enables operators to offer customized and differentiated services to various tenants, such as enterprises, industries, and public sector organizations, while optimizing the utilization of network resources. Network slicing is one of the key features of 5G networks, as it supports the diverse and dynamic use cases of 5G, such as enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communications.Reference:Nokia Bell Labs 5G Professional Certification - Distributed Cloud Networks, Unit 4: Operating Your Cloud, Section 4.2: Network Slicing.

Answer : A, C

Microservices are a design principle for cloud-native applications, where each application is composed of a set of small, independent, and loosely coupled services that communicate with each other through well-defined interfaces1.Microservices have the following characteristics2:

Microservices arechainedin order to build an application, meaning that they are connected by a network and exchange messages or data to perform a specific function or task.

Microservices aredifferentiatedby function, meaning that each microservice has a single responsibility and performs a distinct function within the application.

Microservices arederivedfrom monolithic applications, meaning that they are created by breaking down a large and complex application into smaller and simpler pieces that can be developed, deployed, and scaled independently.

Microservices arescalableandresilient, meaning that they can handle variable workloads and recover from failures without affecting the whole application.

Therefore, the correct statements are A and C, while B and D are incorrect.Reference:1:Nokia Bell Labs Distributed Cloud Networks, Unit 2: Cloud Technologies and Features, Topic: Microservices and Containerization2:Module by Module - Self Study Note Guide, DC2.4-- Microservices and Containerization

Answer : A, C

The properties related to a public cloud arefor users, there is no cloud infrastructure operationandeasy scaling.A public cloud is a cloud service that is offered by a third-party provider over the public internet, and is available to anyone who wants to use or purchase it1.Users of public cloud do not need to operate or maintain the cloud infrastructure, as it is the responsibility of the cloud provider2.Public cloud also offers easy scaling, as users can quickly and dynamically provision or release resources according to their needs2.Public cloud is suitable for applications that have unpredictable or variable demand, or that do not require a high level of security or customization3.Reference:1:Nokia Bell Labs Distributed Cloud Networks, Unit 1: Cloud Ecosystem, Section 1.1: Cloud Types2:Nokia Bell Labs Distributed Cloud Networks, Unit 2: Cloud Technologies and Features, Section 2.1: Cloud Computing3:Nokia and DISH to deploy first 5G standalone core network in the public cloud with AWS, Press Release

Answer : A, C

The characteristics of traditional monolithic services are low scalability and fixed capacity. Monolithic services are applications that are built as a single unit, where all the components are tightly coupled and run in the same process. This makes them hard to scale, as they require more resources and coordination to handle increased demand. Monolithic services also have fixed capacity, as they are designed for a specific workload and cannot adapt to changing requirements or traffic patterns. Monolithic services are often slow to deploy, as they require updating the entire application for any change or improvement.Reference: [Cloud Native applications design], [Microservices and Containerization]

Answer : B, C

Habana and EyeQ are two examples of AI hardware solutions that are designed to accelerate deep learning and computer vision applications.Habana is a company that produces AI processors for both training and inference workloads1.EyeQ is a family of system-on-chips (SoCs) developed by Mobileye for advanced driver-assistance systems (ADAS) and autonomous driving2. DataLake and Sparks are not AI hardware solutions.DataLake is a term that refers to a large-scale data storage architecture that can store structured, semi-structured, and unstructured data from various sources3.Sparks is a misspelling of Spark, which is an open-source distributed computing framework for large-scale data processing and machine learning4.Reference:1: Nokia Bell Labs Distributed Cloud Networks, Unit 4: AI/ML in Cloud Networks, Section 4.2: AI Hardware2: Nokia Bell Labs Distributed Cloud Networks, Unit 4: AI/ML in Cloud Networks, Section 4.2: AI Hardware3: Nokia Bell Labs Distributed Cloud Networks, Unit 2: Cloud Technologies and Features, Section 2.4: Cloud Storage4: Nokia Bell Labs Distributed Cloud Networks, Unit 4: AI/ML in Cloud Networks, Section 4.3: AI Software