Why Distributed Cloud Is a Top 2020 Strategic Technology Trend

Overview

Key Findings

Distributed cloud is the first cloud model that includes the physical location of services as part of its definition.

It repairs the discontinuities often found in hybrid‑cloud value chains, with providers adopting various approaches to address them.

Distributed cloud will appear in stages: initially as packaged, location‑constrained products, later involving third‑party telecoms and municipalities.

Advanced use cases increase the range of cloud services available to IT, each offering trade‑offs in proximity, control, scalability, and service breadth.

Recommendations

Target location‑related use cases and use the distributed‑cloud model to prepare for next‑generation cloud computing.

Leverage the on‑demand hybrid nature of distributed cloud to overcome shortcomings of private and hybrid cloud implementations.

Identify future‑stage use cases (e.g., low‑latency, limited scale, data residency) that can be enhanced by distributed‑cloud “substations.”

Investigate cloud‑provider‑responsible and internally‑deployed cloud operations to address current private‑cloud and hybrid‑cloud failures.

Strategic Planning Assumptions

By 2024, most cloud service platforms will offer at least some on‑demand distributed‑cloud services.

Analysis

Why Distributed Cloud Is a Top Trend

As more users adopt cloud computing, they demand increasingly sophisticated capabilities. Vendors are delivering cloud functions in finer‑grained, intelligent ways, creating new business value. The answer to “What is the future of cloud computing?” is distributed cloud , which distributes public‑cloud services to multiple physical locations while the provider retains responsibility for operation, governance, and evolution. Distributed cloud unifies public‑cloud regions, hybrid cloud, and edge computing into a single continuum (see Figure 1).

Because cloud computing is foundational, distributed cloud was identified as a 2020 top strategic technology trend, serving as the basis for the other nine trends.

Top Ten Use Cases for Distributed Cloud

This trend belongs to the “Intelligent Space” category and also includes empowered edge, practical blockchain, and AI security (see Figure 2).

Distributed cloud synergizes strongly with three other top trends:

Empowered Edge : Edge devices will leverage a ubiquitous distributed‑cloud system from gateway and micro‑data‑center to remote cloud regions.

Practical Blockchain : As blockchain matures, more processing will move to edge environments that rely on distributed‑cloud‑backed functions.

AI Security : Manual monitoring of massive future edge fleets will be impossible; AI‑driven security systems are essential for detecting anomalies via distributed capabilities.

Location is the key factor that enables these synergies.

Distributed Cloud Introduction

Distributed cloud spreads public‑cloud services across multiple physical locations, marking a shift from the traditionally centralized virtualization model. Gartner defines cloud computing as an Internet‑enabled, elastic, scalable IT service delivery model, without mentioning location. Distributed cloud adds location as a core dimension, allowing services to be placed near edge devices, communities, cities, or regions, thereby meeting latency, data‑sovereignty, and physical‑security requirements.

Origins: Public Cloud, Hybrid Cloud, Edge Computing

Public Cloud

In hyperscale public‑cloud deployments, the provider controls multiple global regions centrally. Although location was historically irrelevant, it now matters for data‑sovereignty and latency‑sensitive workloads, making distributed‑cloud services valuable.

Hybrid Cloud

The hybrid‑cloud concept aims to mix external provider services with internal workloads efficiently. True hybrid clouds face challenges such as responsibility transfer, elasticity, innovation pacing, cost economics, and provider expertise. Packaging hybrid cloud attempts to address these issues.

Transfer responsibility for hardware/software infrastructure to the cloud provider.

Leverage elasticity and cost benefits of shared resources.

Benefit from provider‑driven innovation.

Achieve cost economics of global hyperscale services.

Utilize provider expertise for operation and protection of world‑class services.

Packaged Hybrid Cloud

Next‑generation hybrid (and private) clouds are offered as bundled solutions that connect a vendor‑provided private‑cloud product to the public cloud. Two main methods exist: “on‑demand hybrid” (e.g., Microsoft Azure + Azure Stack) and “layered‑technology hybrid” (e.g., Google Anthos, IBM Red Hat OpenShift).

Examples: Microsoft Azure + Azure Stack represent the on‑demand hybrid approach. Azure Stack delivers a subset of public‑cloud services on customer‑owned hardware, with the provider retaining partial responsibility. AWS Outposts can be used in a hosted private‑cloud mode, where the provider supplies both hardware and software and assumes full responsibility for operation.

Layered‑Technology Hybrid Approach

Vendors such as Google and IBM build portable layers—often based on Kubernetes —that run across distributed environments. These layers abstract away underlying hardware ownership, allowing customers to treat services as “black boxes,” though some customers may dislike relinquishing control.

Distributed Cloud Delivery on Hybrid Cloud Promise

Distributed cloud extends beyond the provider’s data‑center footprint, restoring the cloud value proposition in hybrid scenarios by keeping the provider responsible for architecture, delivery, operation, governance, and updates, even when hardware resides at the customer site.

Edge Cloud

In distributed cloud, the public‑cloud provider designs, operates, and updates services, but may not own the entire stack at the edge. Edge‑focused services (e.g., AWS IoT Greengrass, AWS Snowball, Azure Stack Edge) are tailored for IoT or storage devices and require the provider to manage deployment, operation, and updates. This enables low‑latency execution close to demand points, improving performance and reducing network‑related interruption risk.

Distributed Cloud Evolution

Four Stages of Distributed Cloud

Stage 1 : Hybrid‑like model where providers deliver a subset of centralized services in a distributed fashion.

Stage 2 : On‑demand expansion with third‑party partners (e.g., telecoms) delivering subsets to meet data‑sovereignty needs.

Stage 3 : Community‑shared “substations” where multiple organizations use shared distributed‑cloud nodes, improving economics.

Stage 4 : Embedded and personal resources, such as local processing on personal devices or smart buildings.

Although distributed cloud reintroduces location importance to a location‑agnostic paradigm, it ultimately allows organizations to specify requirements (compliance, security, budget, capacity) and lets providers automate optimal configurations.

Path Forward

Distributed cloud is still early‑stage. Many providers aim to deliver most public services in a distributed manner but currently offer limited consumption models. They extend services to on‑premises data centers, third‑party sites, and the edge using products such as Microsoft Azure Stack, Oracle Cloud, Google Anthos, IBM Red Hat, AWS Outposts, AWS Local Zones, and AWS Wavelength. Each approach presents challenges like vendor lock‑in or delivering portable open‑source software.

Action

Identify location‑related use cases and adopt the distributed‑cloud model to prepare for next‑gen cloud computing.

Use the on‑demand hybrid features of distributed cloud to overcome private‑cloud and hybrid‑cloud shortcomings.

Determine future‑stage use cases (low latency, limited scale, data residency) that can be enhanced by distributed‑cloud “substations.”

Find scenarios where the distributed‑cloud model eliminates the need for traditional hybrid cloud.

Explore cloud‑provider‑responsible and internally‑deployed cloud operations to address current private‑cloud and hybrid‑cloud failures.