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thdc

I like to think it went like this

1. Interviewer: If you're a good software engineer, you can answer basic algorithmic questions.

2. Interviewees: Practice algorithmic questions so you appear to be a good software engineer.

3. Interviewer: People are just studying leetcode to get jobs, what can we do? Ask harder leetcode questions.

4. Other companies: Let's copy them since they're successful.

In short, the questions used to be reasonable until people specifically prepared for them. No one knew what to do about it so they just raised the difficulty, which made it even more unfair for people who don't specifically prep.

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FizzBuzz as an example of 2/3: people used to occasionally talk about how interviewees were just memorizing the answer, and when they tweaked it slightly (like adding a 3rd number), a bunch of them could no longer solve it.

“if a flag of truth were raised we could watch every liar rise to wave it”

I heard this lyric at a formative time, and I’ve seen it be proven true many times. Including tech interviews. People continually seek out those signals that imply knowledge and experience and even shared culture, but those signals inevitably become too small (smaller = quicker and easier to weed people out) and then they become the very things that people practice in order to look like they have the knowledge, experience, or shared culture they need in order to get through the doors and secure the opportunities.

Then those signals get burned and the cycle starts again (in fact, in my experience the cycles concurrently overlap).

It's actually great on the hiring side — you can skip all that bullshit and because tryhards are all prepping obscure CS questions just having a conversation about technical topics has become signal again. Measure something people aren't trying to game and you get a better assessment, go figure.

Yes, I explicitly do the opposite and have the most pragmatic exercises, questions.

Another thing is an exercise for system design where hyperscaling is not required and the thing is actually quite simple. Many who have specifically prepared by leetcoding and reading "cracking the coding interview" 10 times over will naturally overengineer everything trying to fit this exercise to those book patterns dropping all common sense, all the while not having actually built anything meaningful.

I think these people will mostly try to rest and vest anyway. Truly passionate people will pass since they have actually built something and will understand the exercise.

When I get a system design question I always tell the interviewer "I'd just run it on a single server with an SQLite backend, that will be plenty for the median software service and you haven't told me any numbers that suggests this needs more" and then it turns out they wanted it to run at the scale of WhatsApp.

Usually it is expected that you ask yourself what is the expected traffic, but I usually answer with a number that technically one box could handle.

"So what scale are we talking about? A few million monthly users? So like hackernews? I would use a single server... "

You really need two in physically different locations (ideally ASes) with some form of failover, assuming you want a reasonable guaranteed uptime

Does 99.995% [1] of hackernews sound reasonable enough to you?

The reality is a lot of systems (especially simple ones) run perfectly fine on a single server with next to no downtime and all the additional redundancies we introduce also add additional points of failures and without the scale that makes these necessary you might actually end up reducing your availability.

[1] https://hn.hund.io/

HN is on a pair of servers.

The second one is just a standby though and not in another region. And if I recall correctly dang mentioned at an outage that the failover to the standby is manual. But I'm not sure.

https://news.ycombinator.com/item?id=16076041

I can't see how hackernews is 99.995% if I get at least 30-40 "Can't serve your request" error pages a year.

> Does 99.995% [1] of hackernews sound reasonable enough to you?

How did you come up with that number? I looked at the link and just one of the outages listed on January 10 was 59 minutes. That alone makes the uptime worse than 99.99% for the entire year before it was halfway through January.

(99.995% means at most 26.3 minutes of downtime per year. See https://en.wikipedia.org/wiki/High_availability#Percentage_c...)

it's the 30 day uptime statistic displayed on the website I linked.

if you click the history it says 98.452% over 365 days.

That’s a pretty low level. That’s lower than my pi hole. But I wouldn’t consider my pihole to be anything other than best endeavours (99.1%). Two would be fine, but there are common points of failure which would limit the solution

This so much this! Experience is such a wonderful thing.

Add a static caching layer and you’re ready for traffic spikes.

We've run 375,000 self-service employees ERP system (so much heavier single transaction than HN) on a single (large:) db2/aix box with no downtime over last 8 years. That's well within published specs for that hardware / software combo.

Yes we do have a DR box in another data centre now, in case of meteorite or fire.

This used to be the norm. A single hardware / software box CAN be engineered for high uptime. It's perfectly fine when we choose to go the other way and distribute software over number of cheap boxes with meh software, but I get pet-peeved when people assume that's the ONLY way :).

I’m paranoid about environmental situations so always have a failover, but then my DR plans include events such as “Thames barrier fails”.

For what it's worth if I ever had a candidate give me this answer on a systems design problem I'd probably immediately stop evaluating them and start selling them on the role.

The highest correlation I see to success in my field is a background of PC gaming. They tend to do better on interviews in the technical regard, all the flashy certificates go out the window of you cant tell me what you would do if a computer wont post.

absolubtely! One of the best jobs I ever worked at asked me what CPU I had in my computer at home, I talked about how i'd built my own pc and the parts that went into it and why, and they (much) later when I was settled at the role said they could see I was a good candidate from that point onward. I think its useful to show a curiosity about your tools, about the boundaries of your world, which is useful when things arent going to plan

Do you really think it made you a better candidate, or did this person just feel a connection due to a similarity in interests or in your approach to computing? Was it even relevant for the job?

I find basic pc troubleshooting skills to be highly relevant to working in a data center. I learned about isolation testing and minimum config when I was like 13 trying to play MMOs, these things come relatively naturally to me due to exposure at a young age. That interest has prevailed well into my adulthood now, having no formal education I run circles around the relatively disinterested comptia kids.

As to being a better candidate, there is little I doubt less* than simple observations I can make at work. We could split hairs over causality, but there is a clear distinction between the people who go home to delid their CPU and the people who have devoted their time to certs instead.

Of course there will always be those sages that dont really care much for videogames and have transcended the street knowledge, those people 1. Have better jobs to work 2. Are harder to find with little benefit.

> due to a similarity in interests or in your approach to computing?

It's hard to say for sure - both of these things are also part of being a good candidate and working well in a team.

But I do think that this experience is both because of and forms part of who I am, a certain troubleshooting & optimizing mindset and curiosity with machines. Is it strictly necessary, or will all people with this shared hobby/past be this way? I don't know. I do think its a useful or good fuzzy signal, to be best used alongside other signals.

Was it relevant for the job? Not for the job description. There were times when I used related experience to solve problems or smooth things over though, such as figuring out why a QA engineer's setup was bluescreening (faulty ram), or in having familiarity with tools built into windows for performance profiling and debugging memory & storage problems with programs

Sadly, we can’t defer to stack overflow for interview success like we can with code. GPT will/may help break it up but until we stop with the sociology questions and get back to technical delivery, we’ll continue to see people try to game a system and then try to game that system they gamed. It’s real life NPM.

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