Public cloud adoption in India to rise 30% to $7.3 bn in 2022: Gartner

The sector has accelerated since the onset of the pandemic, which was a tipping point for Indian businesses to realise its true value, says Gartner

End-user spending on public cloud services in India is forecast to total $7.3 billion in 2022, an increase of 29.6% from 2021, according to a recent forecast by Gartner, Inc.

“Public cloud services adoption has accelerated since the onset of the global pandemic. The pandemic was a tipping point for Indian businesses to realise the true value of public cloud,” said Sid Nag, research vice president at Gartner.

“In India, the policy infrastructure is emerging as an important contributor to public cloud growth. For example, the recently launched public cloud government initiatives Meghraj and Cloud Vision for India 2022 will prove useful for small and medium businesses or those who are in early stage of cloud adoption to benefit from this technology,” said Nag.

Additionally, initiatives targeted towards building a skilled cloud workforce in partnership with private IT service providers will contribute to the government’s effort of strengthening the public cloud ecosystem in the country.

While still on the rise, Indian end-user spending on public cloud next year will be slower than the 34.6 per cent growth forecast in 2021. Indian CIOs are expected to focus their cloud investment on cloud system infrastructure services (IaaS). This segment is forecast to total $2.4 billion in 2022, up 40 per cent from 2021. IaaS will make up 32.3 per cent of the total investments in public cloud services in 2022.

“Public cloud growth continues to be driven by organizations that want to modernize their IT and reduce their capital expenditure spend. The desire for agility and innovation in both business transformation and IT operations is also fueling the growth of public cloud,” said Nag.

The next step in the growth of cloud in India will be the adoption of cloud native technologies. Indian CIOs will look to reimagine and refashion their applications and workloads using containers and microservices as well as artificial intelligence (AI) and machine learning (ML).