GCRI · Data and Compute
Cloud and edge systems
Computing now spans hyperscale cloud regions, national and private data centres, and processing at the edge of networks, near sensors and users. The arrangement decides latency, cost, control over data, resilience and dependence on a few providers. This page sets out how cloud and edge systems are organised and where they concentrate risk, how they are measured, and what evidence serves the public institutions choosing among them.
Cloud and edge systems on the record.
Cloud and edge systems: how the risk develops.
Hybrid, local and sovereign computing options. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Scale concentrates in few providers
Economies of scale give a small number of providers most of the cloud market. Public bodies gain capability and inherit shared dependencies.
Location matters for law and latency
Where data are stored and processed affects which laws apply, who can compel access and how quickly services respond.
Edge computing brings processing closer
Processing at base stations, gateways and devices reduces latency and bandwidth, but adds many distributed systems to secure and maintain.
Switching is costly
Proprietary services, data egress charges and skills tie customers to providers. Portability and interoperability reduce lock-in but take deliberate design.
Connected activity in the contiguous United States.
Night lights, population density and true-colour imagery over the contiguous United States, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Connected activity, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Connected activity, framed on the contiguous United States.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA HLS S30Sources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
Cloud and edge systems carry data from sensors in every domain.
Findings are designed for the Exponential Technology series. The EU Data Act (2023) addresses switching between data processing services; the Global Centre for Risk and Innovation (GCRI) rates no provider.
- Field deployment lessons.
- Studies of offline-first design.
Model cloud and edge systems as a system. Run the cascade.
Assembled from the Nexus Standards area profile Digital, telecom and platforms: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-ice loss
- Coastal erosion (set off downstream)
- Biodiversity loss (set off downstream)
- Arctic winter sea-ice collapse (set off downstream)
- Polar vortex disruption (set off downstream)
Systems and couplings
- Digital, telecom and platforms
- Energy utilities and grids Coupling
- Media and information Coupling
- Finance, insurance and capital markets Coupling
- Defence and civil protection Coupling
Controls
NS-0Constitution and principlesNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H86Hazard family: Telecom and data-centre failure (NHS-1 infra.digital)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H93Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-T8Software and supply-chain integrity riskNRS-X6Cyber and digital security risk
Observation
- ITU DataHub ICT indicators (listed for reference)
- World Development Indicators (listed for reference)
- WMO Alert Hub and Register of Alerting Authorities (listed for reference)
- Proportion of population covered by a mobile network, by technology
- Fixed broadband subscriptions per 100 inhabitants, by speed
- Individuals using the Internet (% of population)
- Number of people per 100,000 that are covered by early warning information through local governments or through national dissemination mechanisms
Example geography
- North America: 243 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Public sector workloads in cloud | percent of workloads | annual | Government digital strategy reporting | REPORTED |
| Cloud market share of largest providers | percent | annual | Market studies | ESTIMATED |
| Cloud regions per country | count | annual | Provider documentation | DECLARED |
| Workloads with tested exit plans | percent of critical workloads | per assessment | Exit plan records | REPORTED |
| Data egress charges | currency per gigabyte | per change | Provider price lists | DECLARED |
| Edge sites deployed | count | annual | Operator reports | REPORTED |
How cloud and edge systems is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Datasets and provenance
The data classes behind cloud and edge systems and what is recorded about each before it is used.
| Data class | Provenance recorded | Resolution stated | Licence checked |
|---|---|---|---|
| Satellite imagery, optical and radar | sensor, processing level, acquisition date | pixel size and revisit | per scene |
| Reanalysis and climate model output | model, experiment, member, version | grid and time step | per release |
| In-situ sensors and gauges | station, instrument, calibration record | point and sampling rate | per network |
| Population and asset exposure | method, vintage, input sources | cell size and unit | per release |
| Boundaries and reference geography | producer, edition, date | scale | per edition |
- Lineage
- W3C PROV record from source to figure
- Principles
- FAIR: findable, accessible, interoperable, reusable
- Gaps
- shown as missing, never filled silently
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Competition authority cloud market investigations | Market structure, switching barriers and remedies | Public records, licence per authority |
| Provider region and service documentation | Locations and services offered | Public, terms per provider |
| Government cloud strategies and frameworks | Public sector cloud policies and procurement | Public records, licence per government |
| OECD digital economy reports | Cloud adoption by firms and governments | Public, OECD terms |
| Eurostat cloud computing usage in enterprises | Share of enterprises using cloud services | Open, Eurostat reuse policy |
Who decides, and what the evidence serves.
Data and Compute prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Government digital and procurement agencies | Which workloads to move to cloud and under what terms | Dependency analyses; exit assessments |
| Competition and data protection authorities | Whether market structure or data transfers need intervention | Market and jurisdiction evidence |
| Network operators and city authorities | Where edge computing serves public needs | Edge trade-off studies |
Outputs this topic produces
- Cloud dependency and concentration analyses for public services
- Data location and jurisdiction reviews
- Exit and portability assessments
- Edge deployment trade-off studies
What architects ask.
- Which workloads and data must stay within a jurisdiction or under an institution's direct control?
- What happens to a service if its cloud region, network link or provider becomes unavailable?
- Which processing should happen at the edge to reduce latency, bandwidth or exposure of raw data?
- How portable are workloads between providers, and what would moving cost?
- Who is responsible for which security controls when a service spans an institution and one or more providers?
- Can essential services keep running in a degraded mode if connectivity to the cloud is lost?
Trade-offs along the continuum.
No point on the continuum is best for everything. The same institution often runs sensitive records on its own systems, bursts large analyses to cloud, and processes sensor data at the edge. The risk lies less in any single choice than in dependencies that accumulate without anyone deciding on them.
Scale and concentration
Elastic capacity and managed services, with dependence on a few large providers and their regions.
Control and cost
Direct control and jurisdiction, with responsibility for operation, security and refresh.
Proximity
Low latency and local resilience, with challenges in management, security and power at many small sites.
How options are assessed.
- 01
Workload placement analysis
Matching requirements for performance, data residency and resilience to locations. Limits: requirements change and are often unclear at the start.
- 02
Dependency and concentration mapping
Identifying reliance on specific providers, regions and services. Limits: providers' internal dependencies are not fully visible.
- 03
Security architecture
Threat modelling and controls across the continuum, using cybersecurity and cryptography. Limits: shared responsibility models can leave gaps.
- 04
Total cost analysis
Comparing lifetime costs including staff, energy and exit. Limits: sensitive to assumptions about use and pricing.
How it is studied, and what the methods cannot say.
- 01High-performance, cloud and edge computingWorkload characterisation · Porting codes to new architectures · Hybrid cloud and HPC workflowsApplied here
- 02Cybersecurity and cryptographySecure research environment design · Federated identity securityApplied here
- 03Data engineering, interoperability and stewardshipFAIR data assessment · Interoperable catalogues · Data quality pipelinesApplied here
- 04Optimisation and operations researchJob scheduling policies · Carbon-aware workload shifting · Capacity planningApplied here
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
What is edge computing?
What is cloud lock-in?
What is data residency?
Is local computing more secure than cloud?
What does data residency settle?
Does the platform operate edge systems?
Contribute evidence from this page.
Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
Bring a method, a dataset or a question.
Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.
Legal documents.
Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.