The convergence of technological advancements and emerging business needs has led to the evolution of cloud computing over the past few years. Start ups, unburdened by legacy systems, are now building cloud-first strategies from day one. They leverage software-as-a-service (SaaS) and platform-as-a-service (PaaS) solutions to innovate quickly and scale without heavy infrastructure investments. In contrast, established enterprises are developing complex environments that span private, public and edge domains. Their focus is on integration, governance and optimising costs while ensuring security and compliance. This duality reflects the diverse priorities and challenges faced by organisations at different stages of digital maturity. A look at the key technological trends shaping cloud connectivity…
Telco cloud reinvention
Telecommunications networks are shifting from legacy physical and virtual network functions (VNFs) to cloud-native network functions (CNFs). According to industry estimates, the Indian cloud-native applications market garnered a revenue of $351.4 million in 2024 and is likely to reach $1,593.6 million by 2030, growing at a compound annual growth rate (CAGR) of 29.1 per cent from 2025 to 2030. Within this segment, platforms (deployed through private and hybrid cloud) were reportedly the top revenue-generating component in 2024, while going forward, the services segment (deployed through public cloud) is poised to be the most promising component as it is expected to register the fastest growth during the forecast period.
The transition to CNFs empowers telcos to offer advanced services at the network edge, such as real-time analytics, immersive media streaming and large-scale internet of things (IoT) connectivity. It also reduces operational complexity and costs, making networks more flexible and responsive to changing demands. Unlike legacy VNFs, which are network functions deployed in virtual machines on a hypervisor layer, CNFs are cloud-native network functions installed in containers in an architecture rooted in microservices. Containerisation refers to packaging software and its dependencies in an isolated unit, while microservices refer to a collection of small and autonomous software services. Another common cloud native technology is dynamic orchestration, that is, automating the administration and coordination of these services. However, both VNFs and CNFs deploy a container-as-a-service platform on top of the virtual infrastructure manager to run.
Private, hybrid and multi-cloud strategies
Modern orchestration tools and cloud-native platforms have made it easier to manage these complex, distributed environments. As a result, enterprises are orchestrating workloads across private clouds, public clouds and edge environments. This approach offers several advantages, including the freedom to choose the best platform for each application or workload, improved resilience and business continuity by preventing dependence on a single provider, and enhanced compliance and data sovereignty by keeping sensitive data where it is needed.
In private cloud environments, all hardware and software resources are dedicated exclusively to, and accessible only by, a single customer. It enables firms to securely move confidential workloads to public cloud with ease. Industry estimates indicate that India’s private cloud market is expected to reach a projected revenue of $35,235.5 million by 2030, registering a CAGR of 16.2 per cent. They also highlight that while SaaS was the largest revenue-generating service in 2023 and infrastructure-as-a-service is the most promising service segment.
In parallel, hybrid and multi-cloud strategies are becoming the norm for organisations seeking to balance cost, control and performance. Studies project that India’s hybrid cloud market generated a revenue of $4,798.8 million in 2023 and is expected to reach $13,313.7 million by 2030, rising at a CAGR of 15.7 per cent. Meanwhile, the multi-cloud management market generated a revenue of $156.8 million in 2022 and is anticipated to reach $1,498.5 million by 2030, recording a CAGR of 32.6 per cent. Further, cloud automation was the top revenue generator in 2022, while the security and risk management segment has the most promising growth prospects.
AI in edge, cloud WAN and GPU PaaS
Artificial intelligence (AI) can dynamically allocate resources, predict failures and manage workloads more efficiently, making it indispensable for resilient cloud infrastructures. Leveraging tools such as Kubernetes, cloud-native AI creates scalable infrastructure that is secure and capable of supporting large workloads. Further, automated machine learning (ML) provided by cloud providers and generative AI models deployed directly on edge devices and servers facilitate instant decision-making.
AI-powered capabilities are also being integrated into cloud wide area networks (WANs) and graphics processing unit (GPU)-optimised platform services. Cloud WAN is a uniform architecture to ease enterprise networking. It reduces costs and delivers high performance securely across diverse geographies as organisations do not need to manage makeshift software-defined WANs, erratic security stacks, and expensive multiprotocol label switching links or colocation-based architectures. Parallelly, cloud GPUs offer the computational power required for dense operations. Cloud providers are making these GPUs compatible with multiple cloud environments, including the Managed Kubernetes Service, AI and ML solutions, in an energy-efficient way. Taking this concept a step further, GPU PaaS, enables enterprises to bring AI inference to the edge. Its key features are stable low-latency performance, optimised resource allocation and scale economics.
India’s cloud AI market shows promising growth prospects. It is estimated that this market generated a revenue of $4,501.1 million in 2024 and may reach $56,828.9 million by 2030, registering a CAGR of 52.6 per cent.
5G connectivity
The 5G market in India is expected to register a staggering growth from 270 million subscribers in 2024 to 970 million by 2030. The roll-out of 5G networks is transforming the relationship between cloud, edge and end users. With its promise of high-speed, ultra-low-latency connectivity, 5G is enabling a new class of applications that were previously impossible. Key impacts include support for immersive augmented and virtual reality experiences, the ability to connect and manage billions of IoT devices efficiently and reliable low-latency performance, which is critical for sectors such as healthcare, manufacturing and transportation. By dramatically reducing the time it takes for data to travel between devices and the cloud, 5G is making real-time processing and instant feedback a reality. This connectivity is the backbone for innovations that demand both speed and reliability. Further, as 5G adoption gains traction within the country, solutions such as intent-based service management are being explored by telcos. This approach combines technologies such as AI and automation with service management to adjust network resources for cloud computing and storage.
Serverless computing
Serverless computing is redefining how developers build and deploy applications on cloud. Contrary to its name, serverless does not eliminate servers but abstracts the underlying infrastructure, allowing developers to focus exclusively on writing and deploying code. In this model, cloud providers automatically manage the provisioning, scaling and maintenance of servers, charging users only for actual execution time.
The core benefit of serverless lies in its scalability and cost efficiency through a pay-per-use model. Functions-as-a-service (FaaS) platforms allow developers to write lightweight functions triggered by specific events, ranging from HTTP requests to database updates, without worrying about infrastructure provisioning.
Beyond agility, serverless computing promotes modular development and accelerates time-to-market. It is particularly effective for microservices architectures, real-time data processing and IoT applications. However, challenges remain in debugging, cold-start latency and vendor lock-in. As tooling improves, serverless computing is poised to become a default approach for building scalable, event-driven applications in the cloud-native era.
India’s serverless computing market generated a revenue of $1.3 million in 2024 and is expected to reach $3.4 million by 2030, with a 17.9 per cent CAGR between 2025 and 2030. In terms of segment, FaaS was the largest revenue-generating service model in 2024, and it is expected to maintain its dominance going forward.
Quantum cloud computing
Quantum computing promises to revolutionise problem-solving in fields such as cryptography, materials science and complex optimisation. However, due to the high cost and complexity of building quantum systems, access to quantum capabilities remains limited. This is where quantum cloud computing comes into play, bringing quantum processing power to users over the cloud. It democratises experimentation, allowing researchers, developers and businesses to run quantum algorithms without investing in specialised hardware.
Quantum cloud computing combines classical and quantum resources through hybrid models. Users can prototype quantum circuits, use quantum-inspired algorithms and integrate quantum steps into classical workflows. Although today’s systems are largely in the noisy intermediate-scale quantum era, progress is being made toward fault-tolerant machines.
As quantum hardware matures, cloud access will be crucial in fostering ecosystems, developing quantum programming languages and onboarding talent. Quantum cloud services represent a bridge between today’s digital infrastructure and tomorrow’s quantum breakthroughs.
Blockchain technology
Originally developed to support Bitcoin, blockchain’s potential extends far beyond cryptocurrencies. Its decentralised nature enhances trust and reduces dependency on intermediaries. In cloud and data ecosystems, major cloud providers are now offering blockchain-as-a-service solutions to secure multi-party data sharing, verify transactions in edge computing environments and create transparent audit trails. Combining blockchain with technologies such as IoT and AI unlocks new possibilities, such as self-regulating devices or automated compliance frameworks. As industries embrace decentralised models of trust and verification, blockchain is transitioning from a disruptive concept to a strategic component of modern digital infrastructure.
Stumbling blocks
An industry report highlighted that understanding app dependencies (54 per cent), evaluating on-premises versus cloud costs (46 per cent) and assessing technical feasibility (45 per cent) are the top cloud migration challenges for enterprises. Additionally, downtime, network outages and latency issues can affect business operations and user experience. Further, cloud computing has a significant carbon footprint, as data centres and contribute up to 3.7 per cent of global carbon emissions.
Moreover, there are technology-specific challenges. For instance, despite its promise, blockchain faces challenges in scalability, energy efficiency (especially with proof-of-work models) and regulatory uncertainty. Serverless computing is associated with limited execution time, security concerns, and complicated monitoring and debugging. Further, the key challenges pertaining to the use of AI in cloud computing are related to the complexity of integration, ethical bias, latency and performance.
Conclusion
The cloud computing landscape is more dynamic and interconnected than ever before. Organisations that embrace these trends are better positioned to deliver smarter, faster and more resilient services. As technology continues to evolve, cloud will remain the foundation for innovation, enabling businesses to adapt, compete and thrive in a rapidly changing world.
