> “That doesn’t invalidate their mission or overall contribution to the world at large;”

Give me a break. Ends to not justify all means. This is a completely appropriate response by the state department.

Why aren't they banning Signal?

As a Hacker News user and commenter, you are not the type of user he’s referring to.

To what end?

Are you pitching or complaining? Because I can't tell.

Mostly aiming to share my anecdote about being too close to a problem for others to learn from, and to pitch - to validate the security thesis.

He doesn't know what he's talking about. Don't feed the trolls.

Absolutely. I’ve had a very similar experience where a bunch of the paddles broke off that push the coffee into the hopper only a couple weeks after we bought it. It was completely our own fault, we had been grinding more coffee than the hopper could handle. I took the thing apart and got in touch with support and they just sent me an entirely new grinder so I didn’t wait to wait to get the one part replaced

Seems like a question you could simply ask the interviewers up front. Establishing expectations about the task is useful anyway.

> Let me flip your quote back on you: how can intelligent people still believe in unbiased meritocracy being the default? Very few people I think would argue that systems based on meritocracy have zero bias. This is not the point. The point is that today’s conventional wisdom by the progressive left is that these biases must be resolved by a system of affirmative action where every sub culture or group somehow is proportionally representative of the overall population based on race, gender, etc. For some reason, that outcome is thought to be the best way to affirm that no bias exists in a group. Personally I think that premise is just very flawed. Meritocracy is not a perfect system. No one is saying that. But it’s the best system we have for engaging with the actual content that is relevant to any given group. As far as bias is concerned, the best we can do is call out specific instances of it and try to squash and correct those (and maybe this case in this blog post is one). There is no commonly understood way to measure bias or racism that everyone agrees with and so why would we think that measuring representation would somehow be the best solution?

You’re ascribing affirmative action to this when that wasn’t what was suggested.

The person in question called out bias and then asked what could be done.

That’s exactly the same as you suggested. The person I replied to then spun that out as reverse racism.

Which is a very common tactic to squash actual discussion on the topic of biases in the industry.

I agree with you though about the cries about reverse racism. Not helpful to the discussion.

But I also believe that when someone cries out bias or discrimination by some group because of underrepresentation or lack of diversity, they are implying that affirmative action is the way to solve it. Maybe I'm putting words into people's mouths there, but it's just anecdotal

“They are implying” is putting words in their mouths like you say.

There’s a whole field of nuance in between “do nothing” and “affirmative action”. People deserve the benefit of not having someone else’s argument ascribed to them.

I understand the HN mods changing titles of sensationalist clickbait, but can we agree that maybe titles of articles in scholarly journals should not be changed?

It's true that with Datadog, a spike in your usage can have a dramatic impact on your bill. This feels true though of any usage model. We've all read stories about out of control AWS bills. Datadog does at least provide some guardrails to prevent things from getting out of control: https://docs.datadoghq.com/account_management/billing/usage_...

With these usage metrics and a little bit of automation (for example the Webhooks integration: https://docs.datadoghq.com/integrations/webhooks/), you could stop shipping telemetry at a certain threshold.

Disclosure: I work at Datadog.

My issue isn't necessarily that a usage spike impacts the bill, that's fine!

The problem is that because of the billing complexity, it's hard to predict how billing will scale with usage. There are just too many axes. Even steady-state billing is hard to price out before signing up, so much so that the answer we received from sales was to just try it and see what the bill is.

This becomes a road block. "I'd like to move us to Datadog! – Oh yeah, how much does it cost? – I won't know until after we've moved." – these conversations are hard to have internally.

The product is fantastic, I'm a big fan. And the total price isn't necessarily bad, it's just opaque, and required a lot of work on my side to model out the pricing, present the business case, get sign-off, and manage the contract over the years. Not something that I, as one of ~8 engineers, wanted to spend my time doing.