Key Details
India is expanding the infrastructure used to host public services, process data and develop AI applications. The reported figures describe different parts of that effort: government cloud adoption, data-centre capacity and access to computing power.
Government cloud: By September 2026, 2,330 government departments were using the MeghRaj cloud ecosystem, launched in 2014 to provide shared infrastructure for public digital services.
Cloud providers: India had 30 empanelled cloud service providers as of September 2026, including Indian and international companies.
Data centres: Installed capacity reached 1.57 GW in August 2026. A projection puts it at nearly 8 GW by 2030; that expansion has not yet occurred.
AI computing: More than 45,000 graphics processing units (GPUs) had been onboarded under the IndiaAI Mission’s shared computing initiative.
Hosting decisions: MeitY’s Cloud Selection Framework, issued in March 2026, guides central ministries and departments in choosing cloud services according to the sensitivity and criticality of applications and data.
Shared Cloud Infrastructure Supports Public Services
MeghRaj and its newer iteration, MeghRaj 2.0, allow government departments to use shared computing and storage rather than build separate facilities for every application. The ecosystem supports platforms including DigiLocker, MyGov and the National Scholarship Portal. NIC also operates four National Data Centres and 24 Mini Data Centres that provide hosting and cloud services for government use.
A practical example is the migration of BHASHINI, India’s language-technology platform, to an Indian-operated cloud in February 2026. MeitY reported improved performance, lower costs and high availability after the move. Those are reported results for one platform, not a measure of how every government cloud service performs.
Data Centres and AI Computing Expand Capacity
Data centres house the equipment on which cloud services run. India’s reported 1.57 GW of capacity reflects the scale already available, while the nearly 8 GW projection for 2030 points to substantial planned expansion. Growth in physical capacity, however, is distinct from how much capacity is commissioned, used or accessible to smaller organisations.
The IndiaAI Mission is addressing a related constraint: access to the computing power needed to develop AI tools. Its shared GPU facility is intended to give start-ups and researchers an alternative to purchasing expensive equipment themselves.
Cloud Choice Depends on the Data Being Hosted
The Cloud Selection Framework makes cloud procurement a governance decision as well as a technical one. It directs central ministries and departments to classify applications and data before selecting suitable hosting arrangements. An application handling sensitive records, for example, may require different controls from a public information website.
Domestic hosting can support jurisdictional control, but the location of a server alone does not ensure security or reliable service. Access controls, cybersecurity, backup arrangements and clear responsibility for failures remain necessary.
Policy Relevance
The next test for government cloud adoption is service performance, not simply the number of departments onboarded. Reliability, recovery after outages, security incidents and the cost of running applications will show whether shared infrastructure improves public-service delivery.
MeitY’s selection framework gives departments a basis for matching cloud arrangements to risk. As data-centre and AI capacity expand, implementation will also require attention to electricity and water needs, affordable access to computing, and whether procurement preserves adequate control over sensitive public data.
Relevant Question for Policy Stakeholders: How will ministries assess whether cloud choices improve the security, reliability and cost of public services as more applications move onto shared infrastructure?
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