Cloud Computing
Cloud computing is a delivery model where software, storage, and compute run on a provider's internet-hosted infrastructure instead of on hardware the customer owns.
Definition
Cloud computing is a delivery model where software, storage, and compute run on a provider's internet-hosted infrastructure instead of on hardware the customer owns. In the Salesforce context, it is the architectural and commercial foundation of the whole platform. Customers reach Salesforce through a browser or an API, the vendor runs every server and database, upgrades arrive automatically several times a year, and billing follows a per-user subscription rather than a one-time perpetual licence.
Salesforce launched in 1999 as one of the first enterprise Software-as-a-Service applications, built around a "No Software" message. The point was not that code disappeared, but that customers stopped installing and patching it themselves. Cloud computing is the lens that explains most of how Salesforce behaves: multi-tenancy creates governor limits, the hosted model drives the three-releases-a-year cadence, and the API-first design makes every integration possible. Sales Cloud, Service Cloud, Data Cloud, and Agentforce all sit on the same shared cloud platform.
How the cloud model shapes Salesforce
Software-as-a-Service, not installed software
Software-as-a-Service means an application is delivered over the internet and consumed as a service, with the vendor owning the servers, the database, and the operating system. Salesforce describes it plainly: "Everything we offer resides in the trusted, multitenant cloud." Customers do not download an installer, provision a server, or schedule a patch window. They sign in through a browser or call an API, and the running software is identical for everyone on that release. The commercial shape follows the technical one. Instead of buying a perpetual licence and paying separately for maintenance, customers pay a recurring subscription, usually per user per month. That model lowers the upfront cost of starting and shifts the burden of uptime, scaling, and security onto Salesforce. It also changes the incentives. Because the vendor keeps charging only if customers keep renewing, the platform has to stay current and reliable rather than coasting on a one-time sale. SaaS is now the default for business software, but in 1999 it was a genuine bet, and Salesforce was an early proof that mission-critical work could run this way.
Multi-tenancy and the apartment analogy
Multi-tenancy means many customer organizations share the same underlying database and application servers, while each org sees only its own data. Salesforce teaches the idea with an apartment building. Your company has its own space in the cloud, but you have many neighbours, from small shops to global enterprises, all in the same structure. Everyone draws on the same plumbing and power, and a small tenant gets the same computing horsepower and features as the largest one. Isolation is enforced in software, not by giving each customer a separate machine. Every row of data carries an organization identifier, and the platform filters every query by it, so one tenant can never read another's records. The payoff is efficiency and speed. Salesforce maintains one set of infrastructure instead of thousands of private installs, which keeps the service affordable and lets improvements reach everyone at once. The constraint is that no single tenant can be allowed to hog shared resources. That single rule is the reason governor limits exist, a point the next sections return to.
The metadata-driven runtime
Salesforce calls metadata "data about data", and it is the engine that makes a shared platform endlessly customizable. Your custom objects, fields, page layouts, validation rules, permission sets, and automation are not separate code that ships to a server. They are metadata rows that describe how your org should look and behave. At runtime the platform reads that metadata and materializes your application on demand from the same kernel that serves every other tenant. The architecture keeps three things cleanly separated: the compiled runtime engine, the tenant's data, and the metadata that describes each application. Because those boundaries are firm, Salesforce can update the shared kernel without touching your configuration, and you can change your configuration without risk to the kernel or to other tenants. This is why an admin can add a field in minutes with no deployment outage, and why a three-times-a-year upgrade does not break custom work. The same design lets partners build managed packages that install as metadata and benefit from future platform improvements automatically.
Why governor limits are built in
Governor limits are the per-transaction ceilings the platform enforces on things like SOQL queries, DML statements, CPU time, and heap size. In an on-premise system a runaway loop slows down only the company that wrote it. In a multi-tenant cloud, that same loop runs on hardware shared with hundreds of neighbours, so an unbounded process would degrade everyone. Limits are the mechanism that stops any one tenant from consuming more than its fair share. This reframes how developers should treat them. Governor limits are not edge-case exceptions to catch after the fact, they are design constraints to build around from the first line of code. The practical consequence is bulkification: writing Apex that processes records in batches, queries outside loops, and respects the per-transaction budgets. Solution architects who internalize the cloud model design for limits up front, because the limits are load-bearing. Almost every Salesforce performance and scalability rule traces back to the simple fact that the infrastructure is shared, and shared infrastructure needs guardrails.
Three releases a year, delivered to everyone
Because Salesforce hosts the software, it can upgrade every customer on a fixed schedule rather than waiting for each one to install a new version. Major releases ship three times a year, named Spring, Summer, and Winter. The cadence is faster than the multi-year cycles of traditional enterprise software, yet slower than continuous delivery, which gives customers a predictable rhythm for change management. Every org receives every release, and skipping one is not an option. That predictability is a feature, but it puts a responsibility on the customer. New behaviour can surface in your org three times a year whether or not you asked for it, so teams test against a sandbox on the preview release before it reaches production. Salesforce publishes detailed release notes ahead of each cycle, and most changes are additive or gated behind a setting. The metadata-driven separation is what makes this safe at scale: the shared kernel can move forward while your configuration stays intact, so an upgrade rarely breaks custom work that was built within the rules.
APIs make the platform programmable
An API-first design means every capability in the platform is reachable through a programmatic interface, not just the screens. Salesforce exposes a wide family of APIs, including REST, SOAP, Bulk, Streaming, Pub/Sub, Metadata, Tooling, and Connect REST. The browser experience is essentially one more client of those same interfaces, which is why anything a user can do in the UI can usually be done by an external system too. This is what turns a hosted application into a true platform. Integrations move data in and out, the Bulk API loads or extracts millions of records, Pub/Sub streams events to other systems in near real time, and the Metadata API lets teams deploy configuration between orgs and run proper version control. Cloud delivery and the API surface reinforce each other: because Salesforce runs the infrastructure, it can offer stable, documented endpoints with their own limits and security model, and customers can build on them with confidence. For most organizations, the APIs are where Salesforce stops being a CRM product and becomes the backbone of a connected system.
Trust, data residency, and Hyperforce
Moving to the cloud means trusting a vendor with uptime and security, so Salesforce makes that accountable in public. Status, performance, and maintenance information live on trust.salesforce.com, which the company frames around the line "Trust is our top priority." Customers can check the live health of their instance and review historical reliability rather than taking it on faith. Security guardrails extend to newer capabilities too, where the Einstein Trust Layer protects generative AI usage without compromising data privacy. Where data physically lives is the other cloud concern, and Hyperforce is the modern answer. Hyperforce is Salesforce infrastructure rebuilt for the public cloud, composed of code rather than owned hardware, and it currently runs on Amazon Web Services. Each region is deployed across at least three availability zones for resilience, and the model spans more than twenty regions worldwide. That gives customers in regulated industries real choice and control over data residency, using least-privileged access, zero-trust principles, and encryption of data at rest and in transit. Hyperforce gradually replaces the original first-party data centres while expanding where Salesforce can run.
Trust & references
Cross-checked against the following references.
Straight from the source - Salesforce's reference material on Cloud Computing.
- Platform Multitenant ArchitectureSalesforce
- Hyperforce Data ResidencySalesforce
Hands-on resources to go deeper on Cloud Computing.
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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