Cloud, SDN & Production Architectures · Study deck

Cloud Deployment Models: Ownership and Risk

A cloud model sets who owns the service, hardware, and risk.

Cloud Clara is your guide for this deck.

cloudcomputingdeployment

Cloud Clara, the module guide, in a scene from this chapter.

After studying this chapter

Learning objectives

You will be able to:

Explain: Those rules matter when a model or configuration comes back from cloud to site, because local control and the data class still need an owner and a release check.
Explain: Edge is not one of the four classic cloud deployment models, but it is often the first boundary an IoT architect must decide.
Explain: A diagram location by itself does not settle responsibility; the selected boundary must also say who handles failure and later data review.
Explain: The edge should not be forced to store or analyze years of data when central systems can do that better.

Major section

Start With the Boundary That Must Hold

A private service may give the hospital more direct control.

Neither choice is safe until ownership, access, outage, and exit plans are clear.
The architect should begin with the data and decision.
Include how the team will leave the setting without losing needed records or breaking the service.
Each group sees a different risk.

Major section

Start With the Boundary That Must Hold (continued)

The best setting is the one that meets the stated need with risks the team can own and test.

A model name should never replace this shared decision.
A shared setting can still isolate work well.
A private setting can still be poorly run.
A contract may support a plan.

Major section

Start With the Boundary That Must Hold (continued)

A shared outside service may grow quickly and reduce local work.

An open item needs an owner and date.
The labels public, private, community, and hybrid do not prove control by themselves.
Practitioner records the boundary choices.
A deployment model is not a brand of cloud.

Major section

Minimum Viable Understanding

Public cloud fits elastic ingestion, dashboards, storage, and analytics when data can leave the site boundary under approved controls.

Private cloud fits workloads that need site control, strict isolation, local operations, or predictable local latency.
Community cloud fits a governed group that shares infrastructure, standards, and operating rules.
Edge placement is part of the same decision even though edge is not itself a cloud deployment model.

Major section

Deployment Models Are Boundary Choices

Private cloud gives a dedicated boundary with local governance over raw data.

Public cloud is provider-operated infrastructure shared across many customers.
Encryption and identity controls are necessary, but they do not replace a placement decision.
Private cloud is dedicated infrastructure operated for one organization, either on site or in a hosted environment.

Deployment models separate ownership, sharing, and operating control before any provider choice is made.

Major section

Deployment Models Are Boundary Choices (continued)

Community cloud is shared infrastructure for organizations with aligned requirements and common governance.

In IoT, this can appear in municipal services, research networks, utility collaborations, sector-specific testbeds, or shared infrastructure across related agencies.
Community cloud fails when the governance model is vague.
Hybrid is not "use everything." It is a design contract.

Major section

The Placement Route

Workload placement should follow evidence.

Access rules and retention controls then define who can use the data in each location.
The final evidence field names the tests, owners, and review record supporting the choice.
A diagram location by itself does not settle responsibility; the selected boundary must also say who handles failure and later data review.

A worked five-minute telemetry route starts with the workload and edge boundary, evaluates a cloud candidate, then records controls and validation evidence before accepting placement.

Major section

Edge Is The First Deployment Boundary

Edge is not one of the four classic cloud deployment models, but it is often the first boundary an IoT architect must decide.

A deployment model that ignores the edge usually becomes unreliable or expensive.
The cloud should not be in the critical path for a decision that must complete faster than the network can reliably support.
The edge should not be forced to store or analyze years of data when central systems can do that better.

Major section

Hybrid Boundary Pattern

In a strong hybrid design, raw events do not drift casually between zones.

The architecture defines a boundary and a transformation rule.
An approved summary can be filtered, summarized, or signed before public analytics receives it; raw sensitive data does not cross that boundary.
Those rules matter when a model or configuration comes back from cloud to site, because local control and the data class still need an owner and a release check.

Hybrid cloud IoT architecture: sensitive data stays in a private cloud with real-time processing while anonymized data flows to public cloud analytics, coordinated by a policy-driven workload router.

Deck summary

Key takeaways

A private service may give the hospital more direct control.

The best setting is the one that meets the stated need with risks the team can own and test.
A shared outside service may grow quickly and reduce local work.
Public cloud fits elastic ingestion, dashboards, storage, and analytics when data can leave the site boundary under approved controls.
Private cloud gives a dedicated boundary with local governance over raw data.

Retrieval practice

Recall check 1 of 2

Cloud Clara says: answer from memory, then check your reasoning.

Q1Public, private, community, and hybrid cloud deployment models are best understood as what kind of choice?

AWho owns, shares, and governs the cloud infrastructure and tenancy.

BA universal ranking from cheapest to most expensive deployment.

CInterchangeable names for one unchanged hosting and governance model.

DA product-marketing choice unrelated to infrastructure ownership.

Show answer

Answer: A Cloud deployment models are boundary choices about who owns, shares, and governs the infrastructure, not a price ranking.

Retrieval practice

Recall check 2 of 2

Cloud Clara says: answer from memory, then check your reasoning.

Q2A valve must close locally during an uplink outage, while long-term trends are analyzed remotely. What should placement analysis classify first?

AKeep all records on the valve controller, including long-term analytics.

BChoose a provider brand before tracing local control and remote paths.

CSeparate local valve control from trends, with owners and outage rules.

DMove valve closure to cloud even when the uplink is unavailable.

Show answer

Answer: C Timing and consequence determine which work can leave the site.

Print reference

Answers

Answer key.

A · Cloud deployment models are boundary choices about who owns, shares, and governs the infrastructure, not a price ranking.
C · Timing and consequence determine which work can leave the site.