NovemberWhiskey

Even for drones that are reusable: if there’s a substantial performance advantage to using a primary cell then you might just want to do that if you’re relatively price insensitive and have good logistics (say, the US Army). Or if you need to be self-sustaining in non-permissive environments (say, the US Army).

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.

The real world is full of relationships that may or may not exist. What’s the referent of “my spouse” if I’m unmarried?

Is your point here that every pointer type for which this can be the case should include an explicitly typed null value?

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.

Things can only be used securely if they have properties that can be reasoned about and relied upon.

This is why we don't usually have critical processes that depend on "human always does the right thing" (c.f. maker/checker controls).

"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.

When I saw the title here, my first thought was “wow, these RISC-V ISA extensions are getting out of hand”

Could you tell me why you think that?

In NYC, prior to Uber entering the market, taxi medallions changed hands for up to $1mm. Prices were fixed by the TLC.

If these are no strong indications of a cartel, I don’t know what is.

Last time I checked, neither Uber nor Lyft were profitable (at all!) before the 2023-2024 time period.

So - putting aside the other waffle and snide remarks - you’re agreeing with me that, in NYC at least, taxis were operated as a cartel?

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.

Isn’t this what Car2X was supposed to do?