By: IBM Cloud Education

Distributed cloud enables a geographically distributed, centrally managed distribution of public cloud services optimized for performance, compliance, and edge computing.

What is distributed cloud?

Distributed cloud is a public cloud computing service that lets you run public cloud infrastructure in multiple different locations - not only on your cloud provider's infrastructure but on premises, in other cloud providers’ data centers, or in third-party data centers or colocation centers - and manage everything from a single control plane.

With this targeted, centrally managed distribution of public cloud services, your business can deploy and run applications or individual application components in a mix of cloud locations and environments that best meets your requirements for performance, regulatory compliance, and more. Distributed cloud resolves the operational and management inconsistencies that can occur in hybrid cloud or multicloud environments.

Maybe most important, distributed cloud provides the ideal foundation for edge computing - running servers and applications closer to where data is created.

The demand for distributed cloud and edge computing is driven primarily by Internet of Things (IoT), artificial intelligence (AI), telecommunications (telco) and other applications that need to process huge amounts of data in real time. But distributed cloud is also helping companies surmount the challenges of complying with country- or industry-specific data privacy regulations - and, more recently, providing IT services to employees and end-users redistributed by the COVID-19 pandemic.

For a closer look at distributed cloud and its benefits, watch What is Distributed Cloud? (8:59)

How distributed cloud works

You may have heard of distributed computing, in which application components are spread across different networked computers, and communicate with one another through messaging or APIs, with the goal of improving overall application performance or maximize computing efficiency.

Distributed cloud goes a giant step further by distributing a public cloud provider's entire compute stack to wherever a customer might need it - on-premises in the customer's own data center or private cloud, or off-premises in one or more public cloud data centers that may or may not belong to the cloud provider. 

In effect, distributed cloud extends the provider's centralized cloud with geographically distributed micro-cloud satellites. The cloud provider retains central control over the operations, updates, governance, security and reliability of all distributed infrastructure. And the customer accesses everything - the centralized cloud services, and the satellites wherever they are located - as a single cloud and manages it all from a single control plane. In this way, as industry analyst Gartner puts it, distributed cloud fixes with hybrid cloud and hybrid multicloud breaks. 

Distributed cloud and edge computing

Again, edge computing refers to locating and running application workloads as physically close as possible to where data is created - for example, where users are interacting with devices such as mobile phones or barcode scanners, or where IoT devices such as security cameras or machine sensors are collecting and generating data. 

In layman's terms, edge computing lets you 'bring the math to the data' - put the computation where the data is created instead of moving the data to a centralized cloud data center for processing, and then back to where answers are needed for decision support or process automation. As a result edge computing is viewed increasingly as essential for applications that process huge volumes of data at high speeds or in real time, when low latency is critical. 

You could implement edge computing without a distributed cloud architecture. But distributed cloud makes edge application deployment and management a lot easier. 

Imagine you run multiple manufacturing plants, each with its own edge server hosted by different cloud service providers, processing data generated from thousands of sensors. With distributed cloud, you can control and manage everything - such as deploying and managing Kubernetes clusters, making security updates, monitoring performance - from a single control plane, one dashboard and one set of tools from one cloud. Without distributed cloud, these tasks and tools could differ depending on where the edge server is located.

Learn more about distributed cloud and edge computing.

Use cases for distributed cloud and edge computing

Distributed cloud and edge computing support everything from simplified multicloud management, to improved scalability and development velocity, to deployment of state-of-the-art automation and decision support applications and functionality.

  • Improved hybrid cloud/multicloud visibility and manageability: Distributed cloud can help any organization gain greater control over its hybrid multicloud infrastructure by providing visibility and management from one console, with a single set of tools.
  • Efficient, cost-effective scalability and agility: It's expensive and time-consuming to expand a dedicated data center, or to build out new data center locations in different geographies. With distributed cloud, an organization can expand to existing infrastructure or edge locations without physical buildout, and can develop and deploy anywhere in the environment quickly, using the same tools and personnel.
  • Easier industry or localized regulatory compliance:  Many data privacy regulations specify that a user's personal information (PI) cannot travel outside the user's country. Distributed cloud infrastructure makes it much easier for an organization to process PI in each user's country of residence. Processing data at its source can also simplify compliance with data privacy regulations in healthcare, telecommunications and other industries.
  • Faster content delivery: A content delivery network (CDN) deployed on a distributed cloud can improve streaming video content performance - and the user experience - by storing and delivering video content from locations closer to end-users.
  • IoT, (AI) and machine learning applications: Video surveillance, manufacturing automation, self-driving cars, healthcare applications, smart buildings and other applications rely on real-time data analysis that can't wait for data to travel to a central cloud data center and back. Distributed cloud and edge computing deliver the low latency these applications demand.

Distributed cloud and IBM

IBM Cloud Satellite helps you deploy and run applications consistently across all on-premises, edge computing and public cloud environments from any cloud vendor. It standardizes a core set of Kubernetes, data, AI and security services to be centrally managed as a service by IBM Cloud, with full visibility across all environments through a single pane of glass. The result is greater developer productivity and development velocity.

To learn more or get started with distributed cloud, sign up for an IBM Cloud account.