As an SRE/ops (and I'm talking some years ago) it was often a pain point, especially with devs with a "works on my machine" attitude ; you would never get the exact requirements from them, I even saw a team of 2 who worked together with different versions of stuff on their respective machines. I also worked in some "offline" environments where once in prod you cannot pull anything from the internet, and you cannot install a compiler too, so it's quite hard to ship because some pip packages require to be built.
I found a way using (can't remember the tool name) which if you loop through the imports and gives it to the tool you get the package name, then I would build wheels to have all binaries and build a container or a VM with all that's needed, thus working completely around python package managers. This was a good enough workflow for the kind of deployment we needed.
Jupyter added a layer of complexity, I deployed it alongside RStudio as browser IDEs in docker swarm. Everybody wants a different set of deps and versions, so you have to keep track of everything, and also people may use things just for development that must not be shipped to prod, so you have to keep track of that too. Also some would develop notebooks on windows and expect them to work in linux VMs/containers and even in prod.
Nowadays devs ship container images anyway through a CI so it is less of an issue. In this era docker was far from being the de-facto everywhere, some people were still afraid of this, security didn't like it, etc.
I'm glad that my country is doing this. On one hand, we have free healthcare and there is the argument that we don't need this and that it's just a way to save money on the weakest of us all. But in practice it is not the case.
I have 2 grandfathers who have been denied certain surgeries because they are too old, not because it would be dangerous, but because there are waiting lists of several years and they never get priorities. Now, none of them are in a hurry to use this procedure of course (only one mentionned going to Switzerland when he almost lost total mobility, but of course cannot afford it), but both of them are in pain, and when it will become excruciating and quality of life will converge to 0, I feel it is a much better prospect than staying for weeks in a hospital room, suffering despite the morphine, with the spouse having to book taxis for visits because of course nobody is going to pay for that.
We are talking about people who have enjoyed near 40 years of happy retirement and a slow but very steady health decline at the end, with lots of time to think and discuss this topic. To me it's a relief to think that I will have this option for myself eventually.
What if the market expected 25% more then reported ? Nobody "knows" what the market expects. People infer it by looking at forward valuation, company guidance, investor expectations, and many many other things happening in the world, in competition, in the value chain. And of course the market does its thing and figures that this company has x% chance of beating (or missing) by $y, and when it's wrong the moves can be huge.
Ah there is liquidity too, but your brother comment makes my point clearer.
About liquidity, yes most people with a million net worth actually have more than half in their house, so technically it is much harder for them to throw cash than somebody with a billion and a much smaller % of their worth in illiquid assets such as property or unlisted companies. I wish I had made this point too.
A few things to note. 1 billion isn't a thousand times a million. If you make a conservative 5% let's say out of your net worth, you still need to work with a million, whereas you don't with a billion. So, technically, $400 with a million is some amount of work hours, whereas $400k with a billion is just pocket change taken out of more than most people lifetime's of earnings that is just 1 year of your interest.
Also, a lot more people (more than 1000x) have $400 to give than $400k so in a sense if people with $400 to give were all being very generous, they could amount to a lot more than what billionnaires could give.
I give a counter example to a general statement, in logic, it is enough to debunk the original statement. My point is, SOME things wouldn't run predictably inside the cluster (in that case without pinning to nodes, which the article says isn't necessary, and which in general defeats the purpose), so you'd need to run some things outside of it.
As per standardized knowledge, I can't see how somebody even proficient with kube, could jump into any app and troubleshoot bad behavior. Apps each have their quirks and subtleties, specific components that behave a certain way. The layers still exists, the kube cluster itself (which again has many component options at every layer of the stack ; hard to know them all), and the app (which will require at least some specialty knowledge).
If it's just about pushing helm charts we wouldn't need SRE anymore, just a CI.
Uniformity ? Try deploying openbao inside kube, if kube decides to restart your pods, you're in for unsealing them at 3am, waking up everybody who owns a Shamir key. So bao stays out of the cluster, or pinned to certain nodes, defeating the purpose entirely. Also, with the ultra wide variety of tools at every layer of the stack, uniformity is a joke ; there are no 2 kube cluster deployment that are the same really.
Standardized knowledge ? The operating system is standardized knowledge. Any competent SRE should be able to login into a Linux box and figure out what's running there. And if you let your previous ops shadow it all you're just a pretty bad CTO.
Tracing who does what ? First of all anybody with admin access can run one time jobs just like anybody with sudo can run one time commands. That's like chapter 01 of the kube doc. Also again at the kube layer itself, below the helm chart, the ops who set that up or updates it can and will change stuff that breaks stuff.
Kube isn't necessarily bad and has it's purpose but it's not a product. It's like Linux, a complex piece of tech that requires a lot more knowledge than "just push this helm chart" to work.
I'd be happy to try some more, I used to play this seriously (even studying with solvers) and I also know and trust a couple of pros, will share with them as well.
Alpine is (was ?) a Renault brand, which is a French company, so it is a little less exotic than a Japanese police force buying a German car (Japan being such a massive car exporter themselves).
Tried daily puzzles on pokerchallenges.com ; 2nd one is "jam or fold" 5bb deep, from the big blind. But no information on what other players do, and we are last to act on this spot, so the question doesn't make sense.
Edit : another one didn't make sense, it asked for my equity with A5o on KK7 or something, but I have no information on opponent's hand or range or betting pattern. Apparently it assumed villain had any2, but pretty much nobody has any 2 here.
I work with junior ops "engineers". Even though some of them won't admit it, they want to do everything with AI, and they do not care much about testing. Even their peer review is done by AI, you can tell by the way the comments are written. They want to deploy stateful clusters, manage VM lifecycles, and even deploy our own Kube cluster, probably entirely vibe coded.
One of them tried to use tabs in yaml instead of spaces, didn't know what a virtualenv was, and didn't know why Kube jobs asked for xp in writing operators ; yet he is pushing multi-files features in less than a day that are meant to manage our backups, and is pushing for managing our own kube clusters in front of management (which finds that it is a lovely idea). At this point I am not sure what to do but it won't end very well I feel.
I functionned this way for a very long time, plain vim with 5-6 options in .vimrc, no plugin (aside for the very occasionnal syntax highlighting like jinja.vim iirc). I kept this setup for more than 10 years mainly to stay compatible with multiple systems (in my case Solaris/Illumos, Linux, MacOS and even Windows).
But I made the switch to nvim / LazyVim. And it is actually pretty good. I had in mind those endless hours of config and lua scripting. At the end of the day all I needed actually was to remove a plugin (folke, which messes with my 's' key) and learn to use the package manager to setup the languages I wanted.
Having things like GrugFAR or lazygit at the tip of my finger is actually a quality of life improvement. I could do without those for sure but they fit my workflow and muscle memory well.
Still wish there was something better for ansible ; I should have gone with pyinfra with my current job's project but I only learned about it after writing 12k LoCs of ansible :'(
I found a way using (can't remember the tool name) which if you loop through the imports and gives it to the tool you get the package name, then I would build wheels to have all binaries and build a container or a VM with all that's needed, thus working completely around python package managers. This was a good enough workflow for the kind of deployment we needed.
Jupyter added a layer of complexity, I deployed it alongside RStudio as browser IDEs in docker swarm. Everybody wants a different set of deps and versions, so you have to keep track of everything, and also people may use things just for development that must not be shipped to prod, so you have to keep track of that too. Also some would develop notebooks on windows and expect them to work in linux VMs/containers and even in prod.
Nowadays devs ship container images anyway through a CI so it is less of an issue. In this era docker was far from being the de-facto everywhere, some people were still afraid of this, security didn't like it, etc.