The points you highlight are very valid, but you cannot just say it had nothing to do with remote work.

>Long after Wall Street ordered its bankers back to the office, the California-based lender’s chief executive, Greg Becker, at times worked from Hawaii, president Mike Descheneaux decamped to Florida, chief risk officer Laura Izurieta was based in a suburb of Washington and general counsel Mike Zuckert worked mostly from New York, according to several people close to the bank.

I have noticed quite often that a lot of things to fall through the cracks irrespective of how many meetings you have on zoom. A lot of catch up happens offline in informal conversations. This might be mitigated on an IC level mostly given that a good team might have a well groomed backlog being fed to them. But at a leadership/design level things are still more informal and might take a few years to get to an efficient level. So dismissing that remote work could have led to a gap is probably being very narrow. The way I read this was the leadership did not handle remote work well and feedback did not flow bidirectionally well across multiple levels. When in person sometimes luck/chance just happens and might be enough to mitigate huge issues.

edit: from the downvotes looks like remote work is an untouchable topic and has nothing wrong with it. /s

If my bank requires luck to practice risk management then I am keeping gold bars under my bed.

I just meant any organization can/has an informal structure and has to mature into a remote work structure which is relatively new.

``` The way I read this was the leadership did not handle remote work well and feedback did not flow bidirectionally well across multiple levels. When in person sometimes luck/chance just happens and might be enough to mitigate huge issues. ```

got it, leadership relies on luck/chance to mitigate huge issues ... (O_O)

+1 Sometimes just because you can does not mean you should.

>Heck you could even say the Amazon Whole Foods Acquisition was a loser -- they haven't leveraged the store network like Walmart has.

As someone who was a regular at Whole Foods even before the Amazon acquisition, from my viewpoint, it has been a win-win.

1. The online shopping experience has been amazing from the Amazon site/app. Target comes close. 1.a. The free delivery for Prime members was an awesome perk while it lasted and definitely made me buy from WF more than the alternatives I have.

2. I get 5% from the Prime card, I actually am incentivized to shop more at WF.

3. Amazon wise I can safely pick up my packages from the nearest store.

I understand it is subjective. But I use a forked version of https://github.com/puckel/docker-airflow on our managed K8s cluster and it points to a cloud managed Postgres. It has worked pretty well for over 3 years with no-one actually managing it from an infra POV. YMMV. This is driving a product whose ARR is well in the 100s of Millions.

If you have simple needs that are more or less set, I agree Airflow is overkill and a simple Jenkins instance is all you need.

Definitely interesting to look at the Pay Gap charts. But it might be interesting to see what the pay gap is after looking at hourly wage. I often hear this argument that men work longer hours. Given how much data they have presented, will definitely be worth looking at that dimension too.

Edit: In S/W that might not matter at all, but some business functions hours might matter. More data the merrier.

Absolutely spot on! Glad to see I am not the only one pondering about it. It has gotten so bad that I try to log out or use incognito to find new stuff. Tiktok on the other hand is amazing at surfacing stuff that I am actually find interesting.

Personally I think YouTube is only showing me what it knows for sure I am interested in vs TikTok actually trying to explore and exploit what I might be interested in.

Youtube is showing me a lot of stuff I don't want to see. I frequent a bunch of genres, mostly tech and games. But I got a lot of recommendations for things like fashion and influencer type channels, which I find really weird because I always take "do not recommend channel" or "I don't want to see this" - yet I still get them.

I understand how the perusing the media gives this biased feeling, just feels like Tesla mentions make for a more engaged article. I ordered a MYLR without ever sitting in one due to how neat my friend's Model 3 was. After driving it for the first time, I doubt if I will buy another car. Tesla just makes amazing cars period. Much better than the 3 series I had before as a comparison.

Where does the acronym "MYLR" come from? (Not what it means, but where you got it from.)

I know I can slowly work out "Model Y, Long Range." But it's not intuitive and you kind of have to be a "Tesla insider" to get that far, or at least closely follow their options/trim levels.

It's a bit better than the "M3" I sometimes see thrown around, because an M3 is a BMW, through and through. The car is actually a Model 3, and there's no reason to abbreviate it further unless you're on a Tesla forum (in my opinion.)

Agreed, spent way too much time on the Tesla forums and did not consider the target audience :+1

Click fraud is very real, but the big players ploughing money into digital ad spend are not idiots. There is a huge shift towards conversion/action driven advertising. Advertisers can see how much of an effect a particular ad channel had on the final conversion e.g purchase of a shoe/add to cart. Just talking about click/ad fraud without talking about counter measures/best practices is just click-baity usually.

Dumb question. Where do fake clicks come from and how are they different from nonconverting clicks

No not a dumb question at all. Hard to give an exhaustive list. One example is say you are a Facebook/Insta influencer who is promoting a link to a product. You might have an incentive to inflate the engagement rate with that link. Just engagement will be likes/clicks on the post/link. By tracking conversions you can try to mitigate this type of behavior to an extent.

>My answer to anyone who asks for kafka: Show me that you can't do what you need with a beefy Postgres.

Sorry thats just a clickbait-y statement. I love Postgres, try handling 100-500k rps of data coming in from various sources reading and writing to it. You are going to get bottlenecked on how many connections you can handle, you will end up throwing pgBouncers on top of it.

Eventually you will run out of disk, start throwing more in.

Then end up in VACCUUM hell all while having a single point of failure.

While I agree Kafka has its own issues, it is an amazing tool to a real scale problem.

I think anotherhue would agree that half a million write requests per second counts as a valid answer to "you can't do what you need with a beefy Postgres," but that is also a minority of situations.

It's just hard to know what people mean when they say "most people don't need to do this." I was sitting wondering about a similar scale (200-1000 rps), where I've had issues with scaling rabbitmq, and have been thinking about whether kafka might help.

Without context provided, you might think: "oh, here's somebody with kafka and postgres experience, saying that postgres has some other super powers I hadn't learned about yet. Maybe I need to go learn me some more postgres and see how it's possible."

It would be helpful for folks to provide generalized measures of scale. "Right tool for the job," sure, but in the case of postgres, it often feels like there are a lot of incredible capabilities lurking.

I don't know what's normal for day-to-day software engineers anymore. Was the parent comment describing 100-500 rps really "a minority of situations?" I'm sure it is for most businesses. But is it "the minority of situations" that software engineers are actively trying to solve in 2021? I have no clue.

Note superyesh was talking about 100 to 500 thousand requests per second. Your overall question stands, but the scale superyesh was talking about is very different and I am quite confident superyesh's scale is definitely in the minority.

Oops, yes, was omitting the intended "k", totally skewing the scale of infrastructure my comment was intending to describe. Very funny, ironic. Unfortunately I can no longer edit that comment.

I’m not sure if you’re omitting the k in your numbers, or missed it in the other comment? Do you mean 100-500 and 200-1000, or 100 000-500 000 and 200 000-1 000 000?

Yes, quite ironically, I accidentally forgot the "k" in my numbers. Oops.

that seems like an awfully low number to be running into issues with RabbitMQ ?

at least for me, every system has its place.

i love posgresql, but i would not use it to replace a rabbitmq instance -- one is an RDBMS, the other is a queue/event system.

"oh but psql can pretend to be kafka/rabbitmq!" -- sure, but then you need to add tooling to it, create libraries to handle it, and handle all the edge cases.

with rmq/kafka, there already a bunch of tools to handle the exact case of a queue/event system.

I think having ad hoc query capabilities on your job queue/log (not possible with rabbit and only possible by running extra software like KQL with Kafka, and even then at a full-table-scan cost equivalent) is a benefit to using postgres that should not be overlooked. For monitoring and debugging message broker behavior SQL is a very powerful tool.

I say this as someone squarely in the "bigger than can work with an RDBMS" message processing space, too: until you are at that level, you need less tooling (e.g. read replicas, backups, very powerful why-is-it-on-fire diagnostics informed by decades of experience), and get generally higher reliability, with postgres as a broker.

Yeah, once you do have to scale a relational database you're in for a world of pain. Band-aid after band-aid... I very much prefer to just start with Kafka already. At the very least you'll have a buffer to help you gain some time when the database struggles.

Indeed! That sounds absolutely like it requires a real pub/sub. 'Actually needing it' is the exception in my experience though.

Hmmm not sure if this is an actual problem or bad configuration. Might be based on Org settings, my org locks this down since it uses ldap as source of truth for display names.

Same here, my org has it locked down. Your Slack display name must match your official name (which is also your email display name). And your Slack handle matches your official login.

There's no way to "hack" it and spoof someone else. If you want to change your display name, you change it officially at the company source (which is straightforward and quick, so "Joseph" can easily be "Joe" or whatever).