The real problem is that sticking an idempotency key onto an operation doesn’t make it idempotent.
It may improve efficiency where a protocol doesn’t assure exactly-once delivery of messages, but it cannot help you with problems other than deduplication of identical messages.
Creating a payment is not an idempotent operation. If the economics of the operation can differ when the “idempotency” key remains the same then you’ve just created a foot-gun in your API.
You can document that you’re going to ignore “duplicate” requests that share an idempotency key but that’s just user-hostile. The system as a whole is broken as designed.
I mean, the fundamental premise of formal methods is that assurance of correctness is achieved through unambiguous specification/modeling and mathematical proof. The extent to which you're dependent on dynamic testing of actual code to achieve assurance does speak to the extent to which you're really relying on formal methods.
"Soft" realtime just means that you have a time-utility function that doesn't step-change to zero at an a priori deadline. Virtually everything in the real world is at least a soft realtime system.
I don't disagree with you that it's a realtime problem, I do however think that "just" is doing a lot of work there.
I am not sure that static analysis is ever going to give answers to those questions. I think the best you can hope to do is surface knowledge about the tacit assumptions about dependencies in order to explore their behaviors through simulation or testing.
I think it often boils down to "know when you're going to start queuing, and how you will design the system to bound those queues". If you're not using that principle at design stage then I think you're already cooked.
Outside of a very narrow range of safety- or otherwise ultra-critical systems, no-one is designing for actual guarantees of performance attributes like throughput or latency. The compromises involved in guarantees are just too high in terms of over-provisioning, cost to build and so on.
In large, distributed systems the best we're looking for is statistically acceptable. You can always tailor a workload that will break a guarantee in the real world.
So you engineer with techniques that reduce the likelihood that workloads you have characterized as realistic can be handled with headroom, and you worry about graceful degradation under oversubscription (i.e. maintaining "good-put"). In my experience, that usually comes down to good load-balancing, auto-scaling and load-shedding.
Virtually all of the truly bad incidents I've seen in large-scale distributed systems are caused by an inability to recover back to steady-state after some kind of unexpected perturbation.
If I had to characterize problem number one, it's bad subscriber-service request patterns that don't provide back pressure appropriately. e.g. subscribers that don't know how to back-off properly and services that don't provide back-pressure. Classical example is a subscriber that retries requests on a static schedule and gives up on requests that have been in-flight "too long", coupled with services that continue to accept requests when oversubscribed.
Classic indications of a cartel (in the economic sense) are deliberate limitations of supply and fixing of prices through collusion. I don’t know about other cities, but NYC absolutely had a taxi cartel.
Corporations are not allergic to competence; they're allergic to bomb-throwing. Except in times of tremendous strife or revolution, incremental change is the best that can reasonably achieved in large organizations. The definition of competence in a large organization includes understanding the concept of Chesterton's Fence, and knowing what the Overton window is.
Windows NT 3.51 minimum hardware requirements were a i386 or i486 processor at 25MHz or better and 12MB of RAM for the workstation version. So the 600MHz machine with 128MB RAM is exceeding the minimum requirement by (conservatively) 24x in CPU speed and 10x in RAM, along with all the architectural improvements from going from the i386 to what's presumably a Pentium III-class machine.
If that's actually a Surface Go 2 running Windows 11 - well, it doesn't have a quad-core i5 as the tweet claims - the Surface Go 2 came with a Pentium Gold or a Core m3; both with only two cores and of those is an ultra-low power variant.
As such, that exactly meets the minimum CPU specification for Windows 11 and only doubles the minimum 4GB RAM requirement.
I'm not trying to apologize for the difference here, but it's not an entirely like-for-like comparison.
I mean, yes and no. If you're loathsome enough, the asking price is going to be non-commercial for you, even in a perfect and infinitely deep market of providers.
>The problem is when government and social media actively collude to side step the government’s responsibility to the first amendment
The government's responsibility to the First Amendment is "don't make laws that limit freedom of religion, speech or assembly". I don't know what it means for government to collude with a third party to side-step that responsibility.
Surely you don't think it would be legal for Congress to pass a law preventing newspaper publishers (whether persons natural or juridical) from, for example, endorsing presidential candidates?
It may improve efficiency where a protocol doesn’t assure exactly-once delivery of messages, but it cannot help you with problems other than deduplication of identical messages.
Creating a payment is not an idempotent operation. If the economics of the operation can differ when the “idempotency” key remains the same then you’ve just created a foot-gun in your API.
You can document that you’re going to ignore “duplicate” requests that share an idempotency key but that’s just user-hostile. The system as a whole is broken as designed.