Cloud-native network function market to reach $72.49 billion by 2030

The cloud-native network function market is set to expand from $21.74 billion in 2025 to $27.73 billion in 2026, driven by 5G rollout, telecom modernization and cloud-native architectures. The Business Research Company says the market could hit $72.49 billion by 2030, with North America leading now and Asia-Pacific growing fastest.

Why it matters: - Cloud-native network functions are becoming a core layer for telecom and enterprise networks that need faster scaling, lower latency and more automation. - The market’s projected growth signals continued investment in 5G infrastructure, cloud-native telecom stacks and automated network operations.

What happened: - The Business Research Company released its Cloud-Native Network Function Global Market Report 2026 – Market Size, Trends, And Forecast 2026-2035. - The report estimates the market will rise from $21.74 billion in 2025 to $27.73 billion in 2026. - The report projects the market will reach $72.49 billion by 2030. - The report cites North America as the largest market in 2025. - The report projects Asia-Pacific as the fastest-growing region during the forecast period.

The details: - The 2025-to-2026 growth forecast implies a 27.6% CAGR. - The 2026-to-2030 outlook implies a 27.2% CAGR. - The report says growth is being driven by virtualization of network infrastructure, containerized workloads, network agility, telecom modernization and automated network management. - The report says future growth will come from 5G standalone deployments, dynamic network scaling, cloud-native telecom architectures, better network function portability and automated lifecycle management for CNFs. - The report highlights growing use of containerized network functions, Kubernetes-based orchestration, service mesh architectures and vendor-neutral interoperable CNF solutions. - Cloud-native network functions are software-based network components built on cloud-native principles and run in containerized environments managed by orchestration platforms such as Kubernetes. - CNFs allow network services to be deployed, scaled, updated and managed across cloud infrastructures with more flexibility. - The approach improves network agility, resource efficiency, automation, resilience and service reliability. - The report covers Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, the Middle East and Africa. - The 2026 report package adds market attractiveness scoring, total addressable market analysis, company scoring matrix graphics and tables, Excel-based forecasting dashboards, market hotspots infographics, key technologies and future trend analysis, plus updated graphics and tables. - The report offers a free sample and a full version through the company’s announcement: Download a free sample and View the full market report.

Between the lines: - The report ties demand for CNFs to the shift from legacy network hardware toward software-defined, cloud-managed telecom infrastructure. - 5G growth is a key demand signal because CNFs are designed to support the speed, automation and elasticity that newer networks require. - North America’s lead suggests earlier adoption, while Asia-Pacific’s forecast growth points to the next major expansion phase. - 5G Americas reported in March 2025 that 5G connections in North America increased from 196 million in 2023 to 289 million in 2024, a 67% year-over-year jump.

What's next: - Operators and vendors are likely to keep investing in cloud-native architectures that support scalable, automated network operations. - The market’s next growth phase will likely hinge on 5G standalone rollouts and broader adoption of interoperable CNF tooling. - Additional regional gains will depend on how quickly carriers in Asia-Pacific and other emerging markets modernize core networks.

The bottom line: - Cloud-native network functions are moving from a niche architecture choice to a mainstream telecom infrastructure play, with 5G rollout and automation doing most of the heavy lifting.