NFV

Network Functions Virtualization

Core Network →
Introduced in Rel-13 Also in: Services, Security

NFV is a network architecture paradigm that decouples network functions from proprietary hardware by implementing them as software instances on commercial servers, enabling agility, scalability, and cost reduction.

Category
Core Network
Introduced
Rel-13
Where
Management
Also touches
2 segments
Specifications
18 specs
NFV Description Purpose Detected Changes Specifications

Description

Network Functions Virtualization (NFV) is a transformative architectural framework for telecom networks that replaces dedicated, proprietary hardware appliances with software-based virtualized instances running on standardized high-volume servers, switches, and storage. A Network Function (NF), which is a functional block within a network infrastructure (e.g., a Mobility Management Entity (MME), a Session Management Function (SMF), or a firewall), is implemented as a Virtual Network Function (VNF). This VNF software is deployed on a virtualized infrastructure, typically managed by a hypervisor or container orchestration platform like Kubernetes, which abstracts the underlying compute, storage, and network resources.

The NFV architecture, as standardized by ETSI and adopted by 3GPP, is composed of three main layers. First, the NFV Infrastructure (NFVI) provides the virtualized resources—virtual compute, virtual storage, and virtual networks—pooled from physical COTS hardware. Second, the Virtual Network Functions (VNFs) are the software implementations of the network functions that consume these virtual resources. Third, the NFV Management and Orchestration (MANO) framework is the brain of the operation. MANO includes the Virtualized Infrastructure Manager (VIM, e.g., OpenStack), which controls the NFVI; the VNF Manager (VNFM), which handles the lifecycle (instantiation, scaling, termination) of individual VNFs; and the NFV Orchestrator (NFVO), which orchestrates resources and services across multiple VNFs to create end-to-end network services.

How it works involves the orchestration of these components. When a new network service is required (e.g., deploying a slice for a new enterprise customer), the NFVO receives the request and consults a catalog of available VNFs and network service descriptors. It then instructs the VIM to allocate the necessary virtual resources (VMs or containers) from the NFVI pool. Subsequently, it directs the appropriate VNFMs to instantiate and configure the required VNFs (e.g., a UPF and an AMF) on those resources, and finally, it establishes the virtual network links between them. This entire process is automated, enabling rapid service deployment, elastic scaling based on load, and efficient resource utilization. In 3GPP's 5G Core (5GC), the concept of Cloud-Native Network Functions (CNFs), often implemented as containers and aligned with NFV principles, is a fundamental tenet, making the core network agile and service-based.

Purpose & Motivation

NFV was created to address critical inefficiencies in traditional telecom networks, which were built on vertically integrated, proprietary hardware appliances from a single vendor. This model led to long innovation cycles (hardware development takes years), high capital and operational expenses (power, space, cooling for many boxes), and severe vendor lock-in. The primary problem NFV solves is this inflexibility; it makes it difficult for operators to launch new services quickly or scale existing ones efficiently in response to market demands, such as the data explosion driven by smartphones and IoT.

The historical motivation for NFV emerged around 2012 from an industry consortium of telecom operators who published a white paper outlining the vision. They were inspired by the agility and economies of scale seen in IT cloud data centers. The goal was to leverage standard IT virtualization technologies to consolidate many network equipment types onto industry-standard servers, switches, and storage, which could be located in data centers, network nodes, or at the edge. This shift promised to reduce costs, accelerate time-to-market for new services, and foster a more vibrant multi-vendor ecosystem. NFV directly enables key 5G concepts like network slicing and edge computing by providing the underlying infrastructure elasticity and automation needed to instantiate and manage logical networks and functions on-demand.

Release Timeline

Detected Changes Across Releases

from 3GPP Change Requests

Specific changes extracted from the „Change history“ tables of 3GPP specifications (6 CRs across 4 releases). Complements the general historical overview above with the evidence-based evolution of this function.

Rel-15 1 change

In Release 15, new interactions between network slice management and the NFV Management and Orchestration (MANO) framework were introduced. Specifically, this addition defined procedures to support network service priority handling within the NFV environment. This enhancement allows for coordinated management between network slicing and virtualized network functions.

  • Add network slice management interactions with NFV MANO for network service priority TS 28.531CR0010
Rel-16 1 change

In Release 16, the primary update for NFV was the correction of references to the ETSI NFV standards. This maintenance change ensured alignment between 3GPP and ETSI specifications.

Rel-17 1 change

In Release 17, the primary update for NFV was the administrative removal of references to a deprecated external specification. Specifically, the standards work involved cleaning up normative text by eliminating all citations to the obsolete ETSI GS NFV MAN001 document.

  • Remove references to deprecated ETSI GS NFV MAN001 TS 28.500CR0010
Rel-18 3 changes

In Release 18, the NFV enhancements specifically defined new interactions with NFV-MANO within the core network function (NF) lifecycle. The standardization introduced explicit procedures for NF instance creation and deletion that involve NFV-MANO. Furthermore, the release updated normative references to align with the current ETSI NFV IFA 013 specification.

  • Add the interactions with NFV-MANO in NF instance creation procedure TS 28.531CR0209
  • Add the interactions with NFV-MANO in NF instance deletion procedure TS 28.531CR0210
  • Update references from TS 28.526 to ETSI NFV IFA 013 TS 28.531CR0231

Explore further

Broader topics and technologies where NFV plays a role.

Defining Specifications

3GPP specifications that define or reference NFV, with the latest known release. Sourced from the 3GPP document catalog — see methodology.

SpecificationTitleRelease
TS 23.700 vk00 XR Services Application Enablement Layer Rel-20
TS 23.722 vf10 Common API Framework (CAPIF) for 3GPP Northbound APIs Rel-15
TS 26.804 vj10 5G Media Streaming Extensions Study Rel-19
TR 26.942 vj00 Study on Media Energy Consumption Exposure & Evaluation Rel-19
TS 28.500 vj00 Management of Virtualized Network Functions Rel-19
TS 28.531 vk00 Management and Orchestration Rel-20
TS 28.541 vk00 5G Network Resource Model (NRM) Stage 2/3 Rel-20
TS 28.801 vf10 Management and Orchestration of Network Slicing Rel-15
TR 28.834 vi01 Technical Report Rel-18
TS 28.890 vg00 ONAP-3GPP 5G Management Compatibility Study Rel-16
TS 32.103 vj00 3GPP Management IRP Overview Rel-19
TS 32.426 vj00 EPC Performance Measurements Specification Rel-19
TS 32.842 vd10 Management of Virtualized 3GPP Core Networks Rel-13
TR 32.972 vj00 Energy Efficiency Study for 5G Networks Rel-19
TS 33.127 vj50 Lawful Interception Architecture and Functions Rel-19
TR 33.818 vh10 SECAM/SCAS for 3GPP Virtualised Network Products Rel-17
TR 33.848 vi00 Technical Report on Virtualisation Security Rel-18
TR 33.927 vj00 Security Assurance for Virtualized Network Products Rel-19
Patrick Zandl

About the author: Patrick Zandl (b. 1974)

Telecommunications specialist, technology journalist (founder of the Mobil server), and developer who has been running since 2025 — the largest Czech-language resource on AI-assisted programming. Formerly Chief Wizard Architect at Prusa3D and head of development for Turris at CZ.NIC; currently a consultant and instructor on AI implementation in companies.