Companies are often insane. I’m working in one who has this one guy build a super complicated architecture, because he don’t know aws. So instead of just using a message queue on aws, he is building Java programs and tons of software and containers to try and send messages in a reliable way. Costs the company huge money, but they don’t care, since he is some old timer who has been there for like 10 years and everyone let’s him do what he wants.
What the company likes about the old timer is that because he has been there for 10 years, he will likely be there for the next 10 years to support the complicated system he is creating now. If a younger team member creates something using a modern approach, there is the risk they will leave in a years time and no one knows how the system works.
No one knows how to use a well documented, publicly available service? No, I’d argue that no one knows how to use a private, internal only, custom solution.
That because you’re an engineer (I assume). The people signing off on these kinds of projects don’t know enough themselves, so they go to someone they trust (the old timers) to help them make the decision. The old timers don’t keep up with new tech, so we keep reinventing the wheel.
“keeping up with new tech” is often just re-inventing the wheel. If it isn’t broke, and can still be maintained, then why break it because you like the flavor of the week?
So he’ll rip an even bigger hole, when he is retiring because the company never bothered to get a new solution running. Then they get a hydra of legacy code that is poorly documented and probably using some old hacks based on even older forum posts, nowhere to be found again.
Oh god. I do a lot of PowerShell scripting at my place, and less than half my team is proficient in it. My co-workers who are almost never write comments in their scripts. Meanwhile, if it’s anything that will live longer than ~5 manual runs, I spemd more time on comments and documentation than scripting.
That effort is valued, but I’m shocked that my team isn’t more aware of the need for documentation. We literally experienced the “bus factor” situation a few years ago.
My current company is comparatively young and only really grew above the 100 people mark a few years ago. There are people who only worked here for 10-15 years, but are so integral as head-monopoly, that they might as well have been there forever.
In my old company, there were developers retiring that worked literally their entire lives for the same company.
Aside: Back in my day, we could use the term “relatively” to mean “in relation to” some other thing. Over time it became “in relation to the average thing” instead of a specific thing. Now it just means “a little bit”/“sort of”. Now people use “comparatively” to convey what “relatively” used to mean. Except… you just now seem to be making that same “relatively” transition with the word “comparatively”. I just find language interesting, and wonder what the next “relatively” will be once that meaning has been lost even to “comparatively”.
That may be an artifact of my native language. In German the term vergleichsweise (Vergleich meaning comparison) is used like that and sometimes these constructions spill over to my English writing.
no no no, its not a critique specifically of you. Native english speakers do this all the time. And I’m sure its inevitable that “comparatively” will make that transition too.
I’m interested: is there a german word to replace "vergleichsweise " to more explicitly mean “comparison”?
I personally always try to engineer away from cloud services. They cost you ridiculous amounts of money and all you need is documentation afterwards. Then it can be easier and faster than AWS or GC
Got to agree with @Zushii@feddit.de here, although it depends on the scope of your service or project.
Cloud services are good at getting you up and running quickly, but they are very, very expensive to scale up.
I work for a financial services company, and we are paying 7 digit monthly AWS bills for an amount of work that could realistically be done with one really big dedicated server. And now we’re required to support multiple cloud providers by some of our customers, we’ve spent a TON of effort trying to untangle from SQS/SNS and other AWS specific technologies.
Clouds like to tell you:
Using the cloud is cheaper than running your own server
Using cloud services requires less manpower / labour to maintain and manage
It’s easier to get up and running and scale up later using cloud services
The last item is true, but the first two are only true if you are running a small service. Scaling up on a cloud is not cost effective, and maintaining a complicated cloud architecture can be FAR more complicated than managing a similar centralized architecture.
I worked in operations for a large company that had their own 50,000 sq ft data center with 2000 physical servers, uncountable virtual servers, backup tape robots, etc… Their cooling bill would like to disagree with your assessment about scaling. I was unpacking new servers regularly because, when you own you own servers, not only do you have to buy them, but you have to house them (so much rented space), run them, fix them, cool them, and replace them.
Don’t get me wrong, I’ve also seen the AWS bill for another large company I worked for and that was staggering. But, we were a smaller tech team and didn’t require a separate ops group specifically to maintain the physical servers.
You are paying aws to not have one big server, so you get high availability and dynamic load balancing as instances come and go.
I agree its not cheaper than being on prem. But it’s much higher quality solutions.
Today at work, they decided to upgrade from ancient Ubuntu version to a more recent version. Since they don’t use aws properly, they treat servers as pets. So to upgrade Ubuntu, they actually upgraded Ubuntu on the instance instead of creating a new one. This led to grub failing and now they are troubleshooting how to mount disks etc.
All of this could easily be avoided by using the cloud properly.
I used to work on an on premise object storage system before, where we required double digits of “nines” availability. High availability is not rocket science. Most scenarios are covered by having 2 or 3 machines.
I’d also wager that using the cloud properly is a different skillset than properly managing or upgrading a Linux system, not necessarily a cheaper or better one from a company point of view.
where we required double digits of “nines” availability
Do you mean 99% or 99.99999999%? Because 99.99999999% is absurd. Even Google doesn’t go near that for internal targets. That’s 1/3 of a second per year of downtime. If a network hiccup causes 30s of downtime, you’ve blown through a century of error budget. If you’re talking durability, that’s another matter, but availability?
For ten-nines availability to make any sense, any dependent system would also have to have ten nines availability, and any calling system would have to have close to ten nines availability or it’s not worth ten nines on the called system.
If the traffic ever goes over TCP/IP, not even if it ever goes over the public internet, if it ever goes over Ethernet wires, ten nines sounds like overkill. Maybe if it stays within a mainframe computer, but you’d have to carefully audit that mainframe to ensure that every component involved also has approx ten nines.
If you mean 2 nines availability, that’s not high availability at all. That’s nearly 4 days of downtime a year. That’s enough that you don’t necessarily need a standby system, you just need to be able to repair the main one within a few hours if it goes down.
you can achieve a lot with a live/live system, or a 3 node system with a master election, or…
“A lot”, sure, but not say 5 nines. 99.9% (8 hours of downtime per year), is reasonable. That’s enough time to fire up an instance in another location if that turns out to be necessary.
99.99% (50 minutes of downtime per year) is harder. It means you need automatic systems doing the switchover, geographical separation, people on call 24/7 to diagnose and fix any issue in minutes.
99.999% is only 5 minutes of downtime per year. At that rate, you can’t even afford for someone on call to respond. You do still want them on call to verify the automated systems did the work, but you need to rely on automated systems fully handling any possible emergency. The system needs to fail over perfectly without any human intervention. For that, a 3 node system isn’t enough. You need geographical redundancy, as well as redundancy within each geographic region. You need to be able to do software upgrades without affecting that redundancy, so you need at least a secondary 3-node system so that you can do a blue/green deployment, testing out handing over traffic to the new system with the ability to instantly roll back if something doesn’t work.
Each “nine” you add reduces the “error budget” by a factor of 10, so as you start getting above 4/5 nines, you really do start to need specialized engineering which tends to come with high cost and complexity.
For a typical Lemmy instance, 3 nines is probably good enough. 2 nines might even be acceptable if people aren’t paying. But, for something like Netflix, 8 hours of downtime per year is far too much. For something like a high frequency trading platform, 8 nines might not even be enough. For them, the custom engineering and obscene cost of chasing 7+ nines is worth it because every second of downtime could cost millions.
Companies are often insane. I’m working in one who has this one guy build a super complicated architecture, because he don’t know aws. So instead of just using a message queue on aws, he is building Java programs and tons of software and containers to try and send messages in a reliable way. Costs the company huge money, but they don’t care, since he is some old timer who has been there for like 10 years and everyone let’s him do what he wants.
What the company likes about the old timer is that because he has been there for 10 years, he will likely be there for the next 10 years to support the complicated system he is creating now. If a younger team member creates something using a modern approach, there is the risk they will leave in a years time and no one knows how the system works.
No one knows how to use a well documented, publicly available service? No, I’d argue that no one knows how to use a private, internal only, custom solution.
That because you’re an engineer (I assume). The people signing off on these kinds of projects don’t know enough themselves, so they go to someone they trust (the old timers) to help them make the decision. The old timers don’t keep up with new tech, so we keep reinventing the wheel.
“keeping up with new tech” is often just re-inventing the wheel. If it isn’t broke, and can still be maintained, then why break it because you like the flavor of the week?
So he’ll rip an even bigger hole, when he is retiring because the company never bothered to get a new solution running. Then they get a hydra of legacy code that is poorly documented and probably using some old hacks based on even older forum posts, nowhere to be found again.
Oh god. I do a lot of PowerShell scripting at my place, and less than half my team is proficient in it. My co-workers who are almost never write comments in their scripts. Meanwhile, if it’s anything that will live longer than ~5 manual runs, I spemd more time on comments and documentation than scripting.
That effort is valued, but I’m shocked that my team isn’t more aware of the need for documentation. We literally experienced the “bus factor” situation a few years ago.
😬
Isn’t that a long time for corporate?
There are 2 types of people, the 2/3 year people, and the 20-life people. 10 is a lot to the 2/3 year people… but not to the others
It also depends on the age of the company.
My current company is comparatively young and only really grew above the 100 people mark a few years ago. There are people who only worked here for 10-15 years, but are so integral as head-monopoly, that they might as well have been there forever.
In my old company, there were developers retiring that worked literally their entire lives for the same company.
True, true…
Aside: Back in my day, we could use the term “relatively” to mean “in relation to” some other thing. Over time it became “in relation to the average thing” instead of a specific thing. Now it just means “a little bit”/“sort of”. Now people use “comparatively” to convey what “relatively” used to mean. Except… you just now seem to be making that same “relatively” transition with the word “comparatively”. I just find language interesting, and wonder what the next “relatively” will be once that meaning has been lost even to “comparatively”.
That may be an artifact of my native language. In German the term vergleichsweise (Vergleich meaning comparison) is used like that and sometimes these constructions spill over to my English writing.
no no no, its not a critique specifically of you. Native english speakers do this all the time. And I’m sure its inevitable that “comparatively” will make that transition too.
I’m interested: is there a german word to replace "vergleichsweise " to more explicitly mean “comparison”?
I personally always try to engineer away from cloud services. They cost you ridiculous amounts of money and all you need is documentation afterwards. Then it can be easier and faster than AWS or GC
You’re the guy 1984 was talking about…
Got to agree with @Zushii@feddit.de here, although it depends on the scope of your service or project.
Cloud services are good at getting you up and running quickly, but they are very, very expensive to scale up.
I work for a financial services company, and we are paying 7 digit monthly AWS bills for an amount of work that could realistically be done with one really big dedicated server. And now we’re required to support multiple cloud providers by some of our customers, we’ve spent a TON of effort trying to untangle from SQS/SNS and other AWS specific technologies.
Clouds like to tell you:
The last item is true, but the first two are only true if you are running a small service. Scaling up on a cloud is not cost effective, and maintaining a complicated cloud architecture can be FAR more complicated than managing a similar centralized architecture.
I worked in operations for a large company that had their own 50,000 sq ft data center with 2000 physical servers, uncountable virtual servers, backup tape robots, etc… Their cooling bill would like to disagree with your assessment about scaling. I was unpacking new servers regularly because, when you own you own servers, not only do you have to buy them, but you have to house them (so much rented space), run them, fix them, cool them, and replace them.
Don’t get me wrong, I’ve also seen the AWS bill for another large company I worked for and that was staggering. But, we were a smaller tech team and didn’t require a separate ops group specifically to maintain the physical servers.
If you really need the scale of 2000 physical machines, you’re at a scale and complexity level where it’s going to be expensive no matter what.
And I think if you need that kind of resources, you’ll still be cheaper of DIY.
You are paying aws to not have one big server, so you get high availability and dynamic load balancing as instances come and go.
I agree its not cheaper than being on prem. But it’s much higher quality solutions.
Today at work, they decided to upgrade from ancient Ubuntu version to a more recent version. Since they don’t use aws properly, they treat servers as pets. So to upgrade Ubuntu, they actually upgraded Ubuntu on the instance instead of creating a new one. This led to grub failing and now they are troubleshooting how to mount disks etc.
All of this could easily be avoided by using the cloud properly.
I used to work on an on premise object storage system before, where we required double digits of “nines” availability. High availability is not rocket science. Most scenarios are covered by having 2 or 3 machines.
I’d also wager that using the cloud properly is a different skillset than properly managing or upgrading a Linux system, not necessarily a cheaper or better one from a company point of view.
Do you mean 99% or 99.99999999%? Because 99.99999999% is absurd. Even Google doesn’t go near that for internal targets. That’s 1/3 of a second per year of downtime. If a network hiccup causes 30s of downtime, you’ve blown through a century of error budget. If you’re talking durability, that’s another matter, but availability?
For ten-nines availability to make any sense, any dependent system would also have to have ten nines availability, and any calling system would have to have close to ten nines availability or it’s not worth ten nines on the called system.
If the traffic ever goes over TCP/IP, not even if it ever goes over the public internet, if it ever goes over Ethernet wires, ten nines sounds like overkill. Maybe if it stays within a mainframe computer, but you’d have to carefully audit that mainframe to ensure that every component involved also has approx ten nines.
If you mean 2 nines availability, that’s not high availability at all. That’s nearly 4 days of downtime a year. That’s enough that you don’t necessarily need a standby system, you just need to be able to repair the main one within a few hours if it goes down.
Sorry, yes, that was durability. I got it mixed up in my head. Availability had lower targets.
But I stand by the gist of my argument - you can achieve a lot with a live/live system, or a 3 node system with a master election, or…
High availability doesn’t have to equate high cost or complexity, if you can take it into account when designing the system.
“A lot”, sure, but not say 5 nines. 99.9% (8 hours of downtime per year), is reasonable. That’s enough time to fire up an instance in another location if that turns out to be necessary.
99.99% (50 minutes of downtime per year) is harder. It means you need automatic systems doing the switchover, geographical separation, people on call 24/7 to diagnose and fix any issue in minutes.
99.999% is only 5 minutes of downtime per year. At that rate, you can’t even afford for someone on call to respond. You do still want them on call to verify the automated systems did the work, but you need to rely on automated systems fully handling any possible emergency. The system needs to fail over perfectly without any human intervention. For that, a 3 node system isn’t enough. You need geographical redundancy, as well as redundancy within each geographic region. You need to be able to do software upgrades without affecting that redundancy, so you need at least a secondary 3-node system so that you can do a blue/green deployment, testing out handing over traffic to the new system with the ability to instantly roll back if something doesn’t work.
Each “nine” you add reduces the “error budget” by a factor of 10, so as you start getting above 4/5 nines, you really do start to need specialized engineering which tends to come with high cost and complexity.
For a typical Lemmy instance, 3 nines is probably good enough. 2 nines might even be acceptable if people aren’t paying. But, for something like Netflix, 8 hours of downtime per year is far too much. For something like a high frequency trading platform, 8 nines might not even be enough. For them, the custom engineering and obscene cost of chasing 7+ nines is worth it because every second of downtime could cost millions.
That could be avoided by using on prem properly, too. People are very capable of making bad infrastructure whether on prem or cloud.
Quick and dirty as they like to say