CB2500 Chap.11 Cloud, Freeconomics and Emerging Technology
Cloud, Freeconomics and Emerging Technology
Four topics, one exercise
The last two weeks put data communication and the cloud beside freeconomics, then close on the Internet of Things, blockchain and a course summary. They look unrelated and are one exercise: given a technology everyone is excited about, decide whether it changes anything for a particular company, and say what evidence would settle it.
That is the shape of an applied examination question, so this chapter is built as rehearsal rather than as exposition.
Cloud moves responsibility before it moves cost
The cost argument is the one students reach for and the weakest to lead with, because rented capacity can easily cost more than owned capacity for a steady workload. The durable arguments sit elsewhere.
Capacity becomes changeable in an afternoon rather than a quarter, which matters where demand peaks. Responsibility for keeping a layer running moves to an organisation doing it at scale. And spending moves from capital to operating, which changes who approves it.
Against those sits a real dependency: availability, price and the exit route become somebody else's decisions, and a proposal should say what happens if any of the three changes.
Data communication is the constraint underneath all of it, and a business case should say whether it depends on cost per unit moved, on latency, or on the link simply being there.
Freeconomics asks who pays
When the cost of serving one more user approaches nothing, giving a service away and earning elsewhere becomes a structure rather than a stunt.
Four payers are possible: another product cross-subsidises, a third party such as an advertiser pays, a minority upgrade and cover the rest, or users pay in attention, data or contribution. The examinable move is naming which one operates and asking what happens if that payer leaves.
For this course the interesting consequence is the fourth: a free service acquires records at a scale a paid one does not, and those records are worth something only if an operation and a reader turn them into information worth what holding them costs.
Connected things and shared ledgers
For connected devices, ask what decision changes once a physical thing reports its own state; a sensor producing a reading nobody acts on has added a maintenance liability and no information.
For a distributed ledger the question is narrower still and most honest answers end in no: it answers a trust problem between organisations, and wherever a single trusted operator is acceptable an ordinary database is simpler, faster and cheaper.
What this chapter covers
- 01
Delivery models and what stops being yours to manage
- 02
Elasticity, responsibility and the capital to operating shift
- 03
The dependency a rented service creates
- 04
Cost per unit moved, latency, or presence of the link
- 05
Four payers behind a zero price
- 06
Free services as a data collection decision
- 07
What decision a sensor reading changes
- 08
Three gates before a shared ledger is worth pricing
Judge a proposal that names three technologies at once
- 3Judge the sensors by the decision they change.
- 3Judge the platform on the shape of the load, not on price.
- 4Take the ledger through the trust gates.
- 2State what you keep and what you replace it with.
Key terms
- Delivery Model
- How much of a computing stack an organisation runs itself, from everything on its own premises to renting finished software.
- Elasticity
- The ability to change capacity quickly, which matters where demand peaks rather than where it is steady.
- Latency
- The delay between a request and its answer, and the constraint that governs anything answered while a customer waits.
- Freeconomics
- Business structures that give a service away because serving one more user costs almost nothing, earning from another payer.
- Cross Subsidy
- A free offer paid for by the margin on a different product from the same seller.
- Internet Of Things
- Physical objects that report their own state, valuable only where the reading changes a decision.
- Distributed Ledger
- A shared record written by several organisations that do not trust one operator to hold it for them.
Cloud, Freeconomics and Emerging Technology FAQ
Is moving to a rented service always cheaper?
No, and leading with cost is usually the weakest available argument. A steady workload can cost more rented than owned. The durable arguments are elasticity where demand peaks, the transfer of operational responsibility to somebody doing it at scale, and the shift from capital to operating spending. The dependency created in exchange should be named rather than ignored.
When is a distributed ledger actually the right answer?
Only when more than one organisation writes to the record, those organisations have reason to distrust each other's copies, and no single trusted operator is acceptable to them. Most cases fail at the first or third gate, and where a trusted operator exists an ordinary database with append-only logging and independent review answers the same need far more cheaply.
How should I judge a proposal to add sensors?
Ask which decision is made differently once the object reports its own state, and who receives the reading. If no decision changes and nobody is rostered to act, the proposal has added a maintenance liability and produced no information in the sense this course defines. Where a decision does change, name it, name the threshold, and name who acts.
Exam move
Take three technology announcements from any business publication this month and run the same three blanks on each: the decision that is made differently afterwards, the person who makes it, and the evidence that would show it was worth its cost. Most announcements cannot fill all three, and noticing that quickly is the skill the final week is teaching.
For the cloud material, write one workload you know as either steady or peaked, because that single classification decides which argument you are allowed to make.
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