Learn ]vocabulary related to hyperscalers

Hyper Scaler

A massive, global-scale cloud service provider (e.g., AWS, Azure, GCP) that owns and operates a vast network of data centers, offering huge economies of scale.

A cloud computing model where a hyperscaler makes resources, like virtual machines (VMs) and storage, available to the general public over the internet.

A cloud computing environment dedicated to a single organization. It can be hosted on-premise or by a third-party, but it is not shared.

A strategy that combines a private cloud with one or more public cloud services, allowing data and applications to be shared between them.

A strategy that uses two or more public cloud providers. This is a key trend to avoid vendor lock-in and optimize for cost or features.

A situation where a customer using a product or service (like a specific hyperscaler's database) cannot easily transition to a competitor.

The foundational cloud model where a hyperscaler provides basic computing infrastructure: virtual servers, storage, and networking.

A cloud model that provides a platform for customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure.

A cloud model where software is licensed on a subscription basis and is centrally hosted by the provider (e.g., Salesforce, Google Workspace).

The cost advantage that hyperscalers achieve due to their massive size, allowing them to provide computing power at a lower cost than any single company could.

A market trend where a company moves an application or workload off the public cloud and back to an on-premise or private cloud, often to save costs.

An approach to building and running applications that are specifically designed to leverage the advantages of the cloud computing model (e.g., using microservices and containers).

A cloud model where the hyperscaler manages the server infrastructure, and the customer is only billed for the precise compute time used when their code runs.

A key battleground for hyperscalers. These are integrated PaaS offerings that allow companies to easily build, train, and deploy machine learning models at scale.

A market trend and legal requirement that data must be subject to the laws and regulations of the country in which it is located, forcing hyperscalers to build data centers in many regions.

A market trend that involves moving compute and data storage closer to the source of the data (e.g., IoT devices, a factory) to reduce latency, rather than sending it all to a central hyperscaler data center.

The delay in data transfer. Reducing latency is a critical market trend, driving the adoption of edge computing to supplement hyperscale clouds.

An online store operated by a hyperscaler (e.g., AWS Marketplace) where third-party software vendors can sell their services directly to the hyperscaler's customers.

A specific application, service, or amount of computing work that runs on the cloud. Companies plan their "workload migration" to the cloud.

The process of moving a company's digital assets, applications, and data from on-premise infrastructure to a hyperscaler's cloud.

A growing market trend and business practice that brings financial accountability to the variable, on-demand spending model of the public cloud.

A financial estimate used to compare the complete cost of an on-premise data center versus running the same workloads on a hyperscaler.

The ability to instantly add or remove computing resources as needed. This is the core value proposition of hyperscalers.

A distinct data center location within a hyperscaler's "Region." Using multiple AZs is a key trend for building high-availability applications.

The generic term for a company that offers cloud computing services. A hyperscaler is the largest and most dominant type of CSP.