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Comment by terpans | Hacker News Reader

2005: your infrastructure is automated using a handful of Bash, Perl and Python scripts written by two system administrators. They are custom, sometimes brittle and get rewritten every 5 years.

2022: your infrastructure is automated using 10 extremely complex devops tools. You automated the two system administrators away - but then had to hire 5 DevOps engineers paid 2x more. The total complexity is 10x.

They wrote YAML, TOML, plus Ansible, Pulumi, Terraform scripts. They are custom, sometimes brittle and get rewritten every 3 years.

EDIT: to the people claiming that today's infra does more things... No, I'm comparing stuff with the same levels of availability, same deployment times, same security updates.

View on HN

Not pictured:

2005 your average box served some php and static assets, connecting to some generic relational database. Reading logs means grepping files over ssh.

2022 your architecture runs in the cloud, has multiple flavors of databases, queues, caches, and so on. You have at least two orders of magnitude more complexity because you aren’t just serving a web page anymore - you handle payments, integrate with other services, queue tasks for later, and so on. Your automation may be an order of magnitude more complex than 2005, but it enables two orders of magnitude more functionality.

My classic C programmer curmudgeon take is that the root of the problem, as with everything else in this industry, is bad software built on top of bad software built on top of bad software... and on it goes.

The systems in your 2022 world are hard to test and maintain because they are bad, and the tools we built to test and maintain them are largely built on the same foundational ideas and technologies, so they are even worse.

We're going to have to rip everything back down to the foundation in order to make progress beyond finger-pointing (X is DevOps but Y is software engineering and Z is IT admin).

What software is bad precisely? The modern browsers? The tools we use to build modern browser apps? Perhaps your gripe is with something else entirely, like modern databases? Or is it the OS that you don't like?

Really not sure what you're commenting about here

They said that the world is bad software on top of bad software, so it’s not one thing. It’s everything being bad and working around everything else being bad.

Yea but they didn’t explain why its bad. Software devs complaining about “bad software” is basically an industry trope at this point but often it just means “Its too complex and I don’t understand why that complexity is probably necessary” or “Its not written the way I would have written it”.

> They said that the world is bad software on top of bad software, so it’s not one thing.

I don't know about OP, but I personally feel like software like GCC/clang/MSVC and Debian/Ubuntu and Docker and SSH and Git are pretty great, and were never better.

Heck, the whole dotnet ecosystem is turning some significant problems in developer experience into at most minor nuisances.

Even Firefox+Chrome are stellar, and extremely solid as-is.

Where exactly is this bad software OP is talking about?

In my experience it's the custom scripts in an attempt to separate infra from developers.

If you are using one of the major cloud providers and instead of just using a native IaC scripts, you have decided that it would be better if the developers only had access to your custom kubernetes operators to manage their infrastructure then you are the problem.

If you are using a deployment pipeline that developers have zero involvement in, and they just "import your Jenkins scripts" then you are the problem.

If you are using major cloud provider and rather than just using their managed kubernetes, you have decided to deploy your own, then the chances are that you are the problem.

Rarely have these approaches ever been stable, in my 20+ year experience they have never been stable. And they are the reason that "real DevOps" came along because developers could do a better job with less downtime if people actually engaged them.

Why not all of the above?

Some people feel anything not written or created by them is "bad".

It doesn't matter to me who turned the wrench, but in my career I've encountered these types where it's only good enough if it's theirs. And IMHO their output is generally quite atrocious. Root cause: Psychological issues.

Shit most of the stuff I write is bad too.

What’s missing a lot is empathy, and that takes slowing down and observing.

The sad part is when encountering this situation and the person who you wish could develop some empathy is completely unreachable and hostile. Terminal.

It’s fine. Works as expected. Closed due to no activity for 30 days. File a PR if you’re so smart.

I wish I got to work with you everyday!

In my past at $medalyaorwherever it was a fucking nightmare everyday, the Architect wouldn't let the PR close.

Honestly it's not always a gift to have someone point out to you the 'movie continuity errors' to you all the time.

I tell my boss you want 2-3 people like me on the project. If everyone was like me we'd make each other miserable. I have worked on trying to frame these things in a positive manner. Unfortunately the guy who would have been the best mentor in that regard went into semi-retirement.

We have way too much empathy for bad software. Honestly, it's almost all total shit. If my care was as bad as the median level of software, it would last 30 days and then be broken down in my driveway until the scrapper hauls it off.

What part of the stack you think of? Because my experience is that the underlying stuff Just Works^TM. Sure, it does have the occasional hiccup, but 1 out of 1000, it is some higher level tool that has a bug.

Just to share the terminology, under underlying stuff I mean the linux kernel, the JVM, etc, while higher level stuff could be certain build tools (khm, looking at you npm), and of course end user tools that are unfortunately way too buggy. Like I have a hard time listing end user applications where I didn’t notice a bug yet.

I feel like there's an opportunity missed here with the transition to clustering for us to build a small kernel for running simple services and moving things over to run on top of these things.

Give me a tight, highly coherent API, with a culture of avoiding feature factory work. At least get "Make it work, make it right, make it fast" to not skip "make it right" anymore. That's sort of the core illness in software today.

Open source doesn't have to be pushed by business concerns. There's a degree of regulatory capture, but the biggest problem is that we just don't know any better. We repeat what we see, and make sure our own pain points are handled. I've seen this play out in API design where an awful API is introduced, and each person who fixes it only fixes 20% of the pain, and so it's 10 years before we get from a mediocre library to one you could actually call 'good', because nobody made 'good', they made better than better than better than ridiculous.

Talk about a low-effort take on the state of modern software. You know what’s also “just bad”? Most systems software written in C.

We could do a case study or something, but that would be a blog post or a book, not an HN comment. How much effort are you looking for here?

I was put off by the low effort take as well.

Personally, I’ve worked through having this mindset myself. I “grew” up with the C and tots descendant family of languages. I wrote shellcode in C and ASM as an exploit dev. I later learned python and now ruby, arguably some of the most abstracted languages.

At each iteration I openly opined at how “C would let me do X without the handcuffs I put myself in by using Language Y”. It’s really just senseless complaining. There is a reason why someone chose Ruby over PHP. PHP over pascal, Pascal over Ada and so on. The point is, to scoff at the product as a bystander is just immature. Throwing shade on an entire industry based off some weird pet purist outlook is just immature :/.

Of course, the irony here is that this type of mindset is no different from the apprentice carpenter who scoffs at every new house he walks through that he didn’t build. It’s no different from the wine snob who cringes at what his mom puts out when company is over. It’s no different from the tens of submissions HN accumulated in a week with something of the tune “I rewrote X in Rust”.

Expecting all software in a properly written stack to be "good" is a particularly bad take, and one that leads to brittle software. Best to accept reality, deal with it and move on.

Your classic C programmer take comes from a time and place where servers were pets and nobody had to, or could, scale very big.

The fact is that businesses either are or are converting to cloud-first because why incur the risks of maintaining the one special-snowflake server that runs your business when you can turn a crank and spin up as many instances as you need -- theoretically very many as you take on more customers and transactions and need to handle the load? And ypu can just restart them if they go down?

Stop thinking technology and start thinking BUSINESS. The cloud may be more janky and complicated than what you're used to but it serves the business's needs better.

Lots of companies excel at playing big business without actually being a big business (or having a remote chance of becoming one). They simply lug around the kind of infrastructure that might be suitable for a company ten times their size. Ironically, it isn't rare that that extra infrastructure and the cost and effort to maintain it limit them in the marketplace.

> The fact is that businesses either are or are converting to cloud-first because why incur the risks of maintaining the one special-snowflake server that runs your business when you can turn a crank and spin up as many instances as you need -- theoretically very many as you take on more customers and transactions and need to handle the load? And ypu can just restart them if they go down?

I'm pretty certain you can do the same with software written in C (or any other language) without resorting to AWS/Azure/GCP/etc.

You can do the same cranking on your own hardware, except you keep the hardware after the peak has passed and you need to plan for the peak.

Or, you can simply get a DO droplet, and crank out as many new instances as you need, and turn them off when you don't, with software written in C (or anything else).

There's no need to go all-in on the AWS/Azure/GCP solution, with the ability to orchestrate instances as cattle, when you have, at peak, 3 instances[1].

[1]If you wrote your software in C, or Rust, or Go instead of Python, or Ruby, you could potentially get away with fewer instances than you need, thereby reducing to treating the system as a system of pets because there are so few of them.

The reason is this: To make money in a gold rush, sell shovels.

Everyone wants to bank on the software craze, and so everyone develops pointless middleware solutions.

That's a bit disingenuous to actual engineers trying to solve problems and genuinely believing their solution can make things better.

Also, looking at principles over tooling, DevOps has a lot to offer that trivially make sense.

You're forgetting the conferences, books, trainings, consulting gigs.

You are not alone in thinking that, see 'The Thirty Million Line' talk by Casey Muratori.

(Long, but worth it, assuming you haven't seen it already)

https://www.youtube.com/watch?v=kZRE7HIO3vk

I don't think we need to muddy the water by saying bad software. Just write the word software. It's multiple layers upon layers. This isn't automatically bad.

There's so much more going on. I don't know if the complexity is all required but we're doing more now. There's just more going on. That's how it is. We need the abstractions. Maybe not all of them. But we need more abstractions and tools running now. There's so much to manage.

I don't see us reducing this complexity that much other than consolidation and some simplification to clean things as they get sorted further. But there is still a need for the layers. It's not 2005. Things are more complex.

The nearest analogy is would you like to code everything in line numbered BASIC or would you like to do it using some modern equivalent? Even with the additional layers there has been real progress in the tools. Improvements across a multitude of metrics. It's not all complexity for the sake of complexity.

Smile. It's another stage of progress. The old mess will fall away. At the next stage what we see as an improvement now will be the next stage's mess. There's a whole slew of problems that will need even newer tools.

We haven't even scratched the surface of the automation we'll require in ten years time.

> We're going to have to rip everything back down to the foundation in order to make progress beyond finger-pointing (X is DevOps but Y is software engineering and Z is IT admin).

1. Never going to happen unless everything collapses, which is extremely unlikely.

2. We are progressing. AR, VR, GPUs with raytracing, complex web applications and global services, global cloud, etc.

To whom does "we" refer. The classic C programmer curmudgeon. Those commenting on HN frequently use the term "we" but reading HN one can see that, amongst those commenting, there is a divergence of opinions about software. Who is "we".

Asking prospective "DevOps", "software engineer" and "IT admin" candidates to program in C is an effective way to weed out those who are not truly capable of writing "good" software. It is easy to find mistakes and expose the incompetent. That may offend the incompetent who believe they are "good" programmers. Thus there are new programming languages created every year, more people using them to write "bad" software, and more people who feel emboldened to attack C as the source of problems, instead of "bad" programmers.

C is truth serum. It is difficult for people programming in C to pretend they are "good" programmmers. They will be found out. It is funny how people on HN attack the language for exposing so many "bad" programmers. Under this theory, programmers are absolved of all responsibility for their mistakes. The language is at fault. "Good" programmers do not blame languages for their own mistakes.

IMHO, there is sometimes a benefit to languages that make it more difficult, not easier, to create and sustain Rube Goldberg complexity. Not to mention languages that compile to smaller, faster programs. "Programmer productivity" is ambiguous. For example, it could be a positive for a programmer trying to justify the expense their salary presents to an employer or it could be a negative to people who are forced to use an ever-increasing quantity of "bad" software. It could be a positive to a programmer who wants to keep implementing new "features" or it could be a negative to a software user who dislikes "feature creep".

The dichotomy of good versus bad software is such a subjective topic that the term "we" really needs to be defined. Different groups of people have different interests and therefore different opinions.

Hey, I've written more C code than anything else and was generally considered pretty competent.

> The language is at fault. "Good" programmers do not blame languages for their mistakes.

I also know that my time to get something functional in higher level languages is often 10x less, and my probability of having very subtle bugs to hunt is much lower.

There's a super-weird tradeoff here. There's all kinds of modern, high-level techniques that improve programmer productivity and reliability of bigger systems.. They convert people who can't be productive C programmers into doing OK work.

But they're also slow and a bit opaque in how they work. And it's really easy to run out of performance and have to do exotic things to get them to scale, in which case you have to build bigger systems still and cede a lot of those advantages.

Whereas, if you write to the metal, you can get a lot of performance out of a single large computer.

Reminder that even absolute expert C programmers can get better performance from completely naive Rust than optimised C: [1].

[1]: http://dtrace.org/blogs/bmc/2018/09/28/the-relative-performa...

I kinda knew this comment would show up. It's completely irrelevant / orthogonal to what I'm saying. But I knew someone would have to beat their favorite horse :D

Yes, Rust may have somewhat better programmer productivity than C, but it's not really at a massively higher level of abstraction.

Not requiring pointer arithmetic in a day-to-day basis and having a proper module system absolutely puts it at a higher level of abstraction.

That truth serum sure has a long list of memory vulnerabilities causing tremendous amount of damage.

Come on, C is not an exceptional language from any point of view. It just pretends that everything is a fast PDP-11, and thanks to the insane amount of work and mental gymnastics done by the compiler, it will output good code. It has shitty abstractability that hinders performance if anything (just look at the small string optimizations done by C++) and hurts maintainability and productivity. At least it should have a proper macro system, but preprocessor macros are just a disgusting hack.

It is if not outright a “bad language”, it should definitely be left behind outside of maintaining the litany of programs written in it, and one should start new programs in either managed languages (if absolute control over the hardware is not required), or at least in C++ or Rust.

UNIX and C are still being taught at Stanford.

https://web.stanford.edu/class/archive/cs/cs107/cs107.1222

Not being an exceptional language doesn’t make it non-popular. There is plenty of programs written in it and certain domains are simply 100% C (particularly operating systems)

Interpreters for popular languages such as Perl, Python, Ruby, etc. are all written in C. The original Go compiler was written in C. Even the people developing Rust used Flex and Bison when trying to formalise a grammar.

The question is whether C is useful. For example, in building things from the ground up. Or vetting programmers.

Another way to vet programmers is to observe how many negatives they try to cram into their sentences. For example, "Not being... doesn't... non-popular."

If they are unable to make clear, concise, positive statements the same deficiency is likely to carry over to writing programs.

> My classic C programmer curmudgeon take is that the root of the problem, as with everything else in this industry, is bad software built on top of bad software built on top of bad software... and on it goes.

No, not really. Nowadays things are way way better than how they were a decade ago. Nowadays you can get pipelines that build and test on multiple target platforms with a dozen or so lines of code, and things run so well that they became reliable infrastructure integrated with your prod system.

Back then you had none of this, and had to pay the salary for a "build engineer" who worked like a wizard stirring a cauldron just to get a single production build out of the door.

I’ve been cultivating this opinion that it’s the other way around. In any other domain, few people use crap tools to make something amazing, and I think it comes down to what you surround yourself with informs what you make.

We need better tools if we want better things.

The bad things are still around in your infra even if you manage to never see them because you only see the "dozens lines of code" at the front.

Someone who really buys that "dozens lines of code" will definitely has no idea what kind of complexity it was about.

Oh sure. Can you try to set up ANY CI pipelines to make it more or less working, don't worry about "pipelines that build and test on multiple target platforms" and get back to share with us your experiences?

What exactly do you want to hear? Not op, but I’ve been doing it for some time.

How much code did you write to get it barely working all by yourself? Or you were just working on top of someone else's work? I did it a couple of times, it was never something like "dozens lines of code".

Back in the late 90's I worked on a system that shipped on 4 different chip architectures, 4 different (unix-based) operating systems, dealt with different endianness and was more reliable and easier to understand. And it was more responsive to users with 1990's hardware than stuff is today. :shrug:

The big question is: Do you need that kind of functionality? I agree that very large and complex infrastructures have their place - the problem is just that they import a ton of complexity and usually cost a lot.

People are always suprised when they see a minimal webserver instance on a ten year old debian [0] handling tens of thousands of requests, without issue. It might go down once a decade because the disk failed, but it cost 1200$ to run over that decade. I don't think that's the perfect way, but modern infrastructures love to include a lot of complexity when it's not needed. The problem is that including something is very easy and the cost is only payed once it breaks. Also, hardware is really cheap (you might not think so, but if you compare it to western IT salaries, it is).

[0] I know outdated instances with no update strategy are not really a benchmark, but I encourage you to go out and ask people what their container base image upgrade strategy is - the situation really did not change that much.

Kind of depends on what you’re building, right? Avoiding building new features in order to limit complexity is probably a good idea in select cases but not in others. Using more complex, purpose-built technology over standard boilerplate is often very cost-efficient, but only if you run at a scale where the additional complexity is worth the savings…

> The big question is: Do you need that kind of functionality? I agree that very large and complex infrastructures have their place - the problem is just that they import a ton of complexity and usually cost a lot.

I think that's the key. Most of us aren't Google/Facebook/whatever. Yet lots of people want to mimic those. A simple stack with a relation database on a single machine still goes a long way. In fact, it goes a lot longer way today than it did 20 years ago. It's ok to scale when you need to, but I think premature scaling is the wrong way to go, especially since most things never get to FB/Google/etc size.

I understand trying to keep complexity low. But I don’t understand how a relational database would be less complex than a simple key value store.

Every time this argument pops up, I end up wondering if it’s really about architectural complexity, or if it’s about sticking with the old and known.

A lot of relational databases offer a better (or more useful) consistency model than k-v stores, assuming your data isn’t just a bunch of keys and values. Having to worry about consistency can significantly your worsen complexity of your application code.

MongoDB is complex, that’s true. But DynamoDB or GCP Bigtable are pretty simple.

Simple indeed, they don't even offer anything that matches SQL flexibility.

Exactly my point. If the argument is to avoid unnecessary complexity, then how come a SQL database is the better choice?

Because not having proper query language turns simple wishes into complex solutions.

But it does have way to query, if you of course only know SQL and didn't bother to learn the MongoDB way to query then for you, the uninformed outsider, it might seem complex. But so does ArangoDB or Neo4j or GraphQL.

Like, if you were never exposed to rxjs and are now trying to build things with it doing

  $stream.pipe(
    switchmap(),
    filter(),
    etc(),
  )

It does seem more complex than

  stream.map().filter().etc()

but it's only so because you haven't put in the effort to learn that way.

Sure, whatever.

Now write DBA scale ISO SQL 2016 / Transact SQL / PL/SQL in that interesting Mongo flavoured language, including database engine debugger integration, and JIT compilation.

1. MongoDB is not complex, the driver structure sucks.

Example Go's mgo driver by Gustavo Niemeyer was simple and effective, but abandoned. The official drivers is unnecessarily complicated. And Go's need to have "context" everywhere adds to this, but MongoDB is not complex. Idk I'm not some super genius and picking up MongoDB was really easy. Querying (aka aggregation pipelines), you have to think of that as "pipes in bash". It's in the words aggregation pipelines. find | groupby | sort | filter | select. Something like that. It's not SQL it's different, but not complex, sorry.

In what context? A hosted database might be "simpler" to operatoe, but BigTable is quite complicated and does a lot of complex, low-level, work to be very fast.

First, I'd say the key value store is actually older than the relational database, by at least a couple of decades. Of course, not the current ones, but we're also not using the relational database from the 80s so ...

Now to try and answer your question, I think a relational database is a lot more complex than a simple key value store, but if it's a good implementation, it will hide this complexity from the user, and using the database will be rather simple. It can be as simple as a key value store since you can just use a relational database like one. Note that this hiding of complexity is by design, it is one of the main goals of the relational model, it's not accidental.

Throw ACID requirements on top of a simple kv store and it is not a simple kv store any more

you stick with an old and known since its getting the job done, customer is happy and you can get a good night sleep too

> tens of thousands of requests,

a raspberry pi can pretty much serve 100k req. / second. An average dev laptop should be able to handle 1M req. / second without much issues

> a raspberry pi can pretty much serve 100k req. / second

I appreciate the sentiment, but my intuition says that number is too high. What would that look like? I can't picture nginx or haproxy serving up a static 'hello world' response at that volume on a Pi3.

And if you do anything with a slow-ish 3rd party API you're probably going to hit the TCP socket limit before you can respond to 100k/s.

Legitimately curious about whether my intuition is wrong. I don't have an unused Pi handy to test it myself.

Edit: It's possible you're citing https://levelup.gitconnected.com/serving-100k-requests-secon... ? Pretty interesting article in any case, especially this claim:

> This test pitted a native C++ server against a scripted Node.js one, so of course the outcome was given. Well, not really. If I run the same test using µWebSockets.js for Node.js, the numbers are a stable 75k req/sec (for cleartext). That’s still 8.5x that of Node.js with Fastify and just shy of 75% of µWebSockets itself.

Edit 2: Doing a bit more research and finding some other benchmarks online, it seems like 100k with µWebSockets is plausible. I recant my skepticism.

> a raspberry pi can pretty much serve 100k req. / second. An average dev laptop should be able to handle 1M req. / second without much issues

Depends on what you do. It's quite easy to hit these numbers with a low number of static pages, but apps that can easily work with static pages usually don't have DevOps people. That's why I went with thousands, to have a reasonable number for an app that actually does some complex processing.

That doesnt seem right. https://www.diva-portal.org/smash/get/diva2:1439759/FULLTEXT... According to this paper, looks like 1000s of requests is more realistic, both for pi and laptop.

Still enough for 99% of websites.

> Still enough for 99% of websites.

I'm not sure you have much experience working on websites. Multiple deployments are required for performance reasons, which is the main driving force for paying hefty bills for CDNs, and their recent investment in edge computing.

You deploy to multiple deployments in multiple regions in a good part to drive down those 300ms requests to sub 50ms. Otherwise your user gets fed up and drops you in favor of a competitor.

But if you work on a service who has only a dozen users in the same region and can wait in turns to see who can make a request, go right ahead with your production raspberry pi setup.

https://en.m.wikipedia.org/wiki/Name_calling

I ultimately agree with you, but in between a raspberry pi and “hefty bills CDNs” is something like a half rack at a Colo, a f5, and a couple PowerEdges.

Those 99% of websites don’t have the performance problem you’re talking about. You’re talking about the 1%.

I bought artisanal knitted socks for Christmas. If their website is faster than their knitting that’s good enough. That website is part of the 99%.

> You deploy to multiple deployments in multiple regions in a good part to drive down those 300ms requests to sub 50ms

one raspberry pi per continent :p

e.g. I'm in a small rural village in southern france right now and I get 2GB down / 1GB up more or less with a 9ms speedtest ping (which is slow, it's often 2ms) - anyone from europe would get < 50ms ping notwithstanding the latency between them and their isp

by the time my website has, say, > 500k req/second I can definitely invest in, idk, some used 2015 i7 laptop to give myself a x10. For reference, 1M requests per second is Instagram in 2015, one of the most used websites in the world - by the time you're at that scale you've been bought by Facebook anyways.

Heyo, I worked at a CDN for a few years on edge cache stuff. Almost every web site would be well served with a single Pi and a CDN. For almost every web site, the CDN is free.

My user gets fed up because the page takes a second to load?

Not every page loads 50 different resources. Not every page serves people globally. Not every page has competitors.

And then you serve megabytes of js libs that will cause multi-second load times and log every single mouse movement, autostart a video with sound and pop up 10 different bullshit, so.. you would be at the exact same spot from a shitty dev laptop.

(Half kidding)

> I'm not sure you have much experience working on websites.

I might say the same about you. Be respectful.

> a raspberry pi can pretty much serve 100k req. / second. An average dev laptop should be able to handle 1M req. / second without much issues

How big are these requests? If you're returning more than 1kB including all the headers, you're not beating 100kreq/s on a standard consumer-level 1Gbit link.

The argument is about the power of a single machine. If your enterprise is somehow limited by 1Gb links, no amount of scaling is going to address that.

I think the parent's argument is that a Raspberry Pi is limited to 1Gb link, so how can do 100k reqs/sec

That, plus if I open dev tools and look at requests for even this site, the only things that small are three of the images (the orange Y in the corner, the vote arrow, and a 1x1 somewhere).

It wouldn't be possible to get that request rate outside of a microbenchmark, just because of the network speed the pi supports.

you can buy faster network cards for a RPi but this is missing the point: 100k req/sec is not a huge volume and a decent server should be able to handle it without issues.

it's not, people have been able to put >1G network cards on a Pi:

- 2.5G: https://www.jeffgeerling.com/blog/2020/testing-25-gbps-ether...

- 10G (in practice 3.6G max which is more than what most can expect from their ISP): https://www.hackster.io/news/10-gbps-ethernet-on-a-raspberry...

The thing is that sometimes you do.

At my current company we're at cusp when we need to address scalability to able to grow as a business, and the business is growing. It took several years to get to this point, but here we are.

I prefer simplicity as much as the next guy, but at some moment it becomes simpler overall to use cloud services controlled by k8s than to maintain large amounts Ansible scripts and Jenkins jobs.

With that, by the way, comes an inevitable untangling of various parts in the software, and simplification of it. To be fast you need the processing path to be simple.

> The big question is: Do you need that kind of functionality?

What functionality? Automated unit tests to ensure you're not shipping code that is so broken that it even breaks basic invariants? Automated integration tests that ensure you're not shipping code that fails to call other components/services? UI tests to ensure that your latest commit didn't made your prod service unusable for the end user? Performance tests that help you determine if your latest change doesn't suddenly exhaust your computational resources in peak demand?

The people paying my salary sure seem to think that we do need it.

I was working on large scale deployments with multiple datacenters, multiple databases, message passing networks and running multiple customer-facing products.

Load balancers and HA setups were already in use. LVS existed. VMs were popular. "CI/CD" existed, without that name.

> 2005 your average box ...

Speak for yourself.

And I had all this in place by 1999. Including the multiple databases, the caches, the load balancing, edge processing nodes all over the world, etc.

Sure we built a bunch of it ourselves, and we had 4 sysadmins, but please don't tell me that this wasn't already going on over 20 years ago.

The future is already here, it’s just unevenly distributed.

By 2004 we were doing perforce and CI. No Continuous Deployment because we were building on-prem software, but by 2008 I was doing svn and Continuous Delivery (similar problem, not hosting).

We would have been if it had been appropriate.

To be fair though, I think a lot of my coworkers suspect i’m talking out of my ass because they’ve been doing this stuff for 5-8 years and think everyone else has too. As tempting as it sometimes is to launch into a lecture., it wouldn’t really help. Everybody knows what they know, and they’re going to know it until they watch it catch on fire and then they will either want to hear about alternatives or they’ll share ideas for fixing it, not realizing they’re repeating something you told them two years ago. Hey that’s a great idea, wish I’d thought of it.

Classic over-engineered DevOps, adding complexity for complexity sake. When you have a hammer...

Everything you described was 2005.

In 2005 there were, for instance, fancy J2EE application servers instead of fancy container roulette tools.

The fun part is that the 2005 architecture is still plenty sufficient for 99% of deployments but everybody architects for 100x the scale they actually need.

This is a good point, but I'd say that's just the ops version of premature optimization.

No, it's the ops version of premature abstraction - when devs build a whole extensible framework around a simple use case just because "requirements might change later" (which 90% of the time they never do, so on average the work is wasted much more often than not).

I mean yes. . . premature abstraction driven by premature optimization. Or more simply, solving a problem you don't have now, and might not ever have.

Everyone talks FAANG scale on day 1. It's common and absurd.

Usually because most business say they need highly available, scalable infra from day 1.

I typically see it happen in the other direction myself. Business folks describe the problem/product and engineering team says “oh yea we can do that, we’ll need K8s” when they do not, in fact, need K8s

This times one million. Back in 2005 there would have been so much shit you wouldn't even dream of doing and a lot of things you did do, you sure as shit wouldn't do now. . . we used to write our cache systems. Migrations were all custom scripts. Fucking nightly builds were a thing because we didn't kick of builds on commit.

Unit tests weren't even common practice back then. Yeah, most places had tests but there was no common language to describe them.

And as much as git can be a big complex pain. . . merging was a BIG thing back then too. I seldom deal with long lived branches and the nightmarish merges they often needed.

Also, to all the young folks who "want to work with physical servers" again. Have fun with the next set of device driver patches you need to roll out.

I heart my containerized IaC buzzword laden cloud existence. #FuckThatNoiseOps

It's as much a cultural problem as a 2005 vs now problem because I have experience working at a joint that uses AWS yet chooses to roll their own Kubernetes, uses GitHub yet flails around with long lived branches and 20 minutes CI stages, uses containers but still has 20 minutes build times, uses ArgoCD yet has tiresome "release events" that generally can't be rolled back and take at least an hour to "fix-fowards" after a bad release. Sometimes you can lead a horse to water and even push it into the trough, but it would rather eat dust than let go of its last-decade ideas about operations.

> Your automation may be an order of magnitude more complex than 2005, but it enables two orders of magnitude more functionality.

And can create more than 2 orders of magnitude in terms of economic value (i.e. profit) as a result.

If that was true, why has the economy since 2000 never hit the speed of growth that it had in the 1990s? It seems the big economic gains of the Internet came early, and what we've seen since is the Law Of Diminishing Returns: increasing inputs for decreasing outputs. Bigger investments for less economic growth.

> hit the speed of growth that it had in the 1990s? It seems the big economic gains of the Internet came early

It did, just not in the way you're describing it. This is how it's manifested itself:

> Apple, Amazon, Alphabet, Microsoft and Facebook all account for just under 20 percent of the market value for the entire S&P 500. With a collective value of nearly $5 trillion, these top tech companies easily dwarf other entire industries in the index, with companies like Berkshire Hathaway and JPMorgan Chase falling well short. Currently, the total valuation of the S&P 500 is almost $27 trillion.

[0] - https://www.statista.com/chart/20794/tech-companies-highly-v...

That is not economic growth. A valuation of some companies on the stock market has noting to do with economic growth. "Create more than 2 orders of magnitude in terms of economic value" never actually happened.

> 2 orders of magnitude in terms of economic value (i.e. profit)

Then you clearly misread my initial point. economic value != overall economy growth

2005 Your app takes some user data, stores it in a database, and presents a filtered view of it to the user on request.

2022 Your app takes some user data, stores it in a database, and presents a filtered view of it to the user on request.

Well if that’s all you’re doing in 2022, there’s nothing wrong with deploying your code and grepping logs over ssh. Bash scripts and offloading some of the complexity of management to AWS (e.g. use autoscaling) goes pretty far

Autoscaling? Do you mean facing so much cloud management complexity that it invites automation, in order to spend more money for a herd of excitingly ephemeral server instances than for a reasonably overprovisioned boring actual computer?

In 2002 I built a website that got about 3m page views a week, with about 50k concurrent users, and a whole bunch of fun things like payments, outbound email, etc. It ran on a single server.

Since then I've working on things that use several servers, things that use no servers with edge functions instead (which have servers, but still), and that use autoscaling across lots of servers.

No doubt some businesses need autoscaling but most don't. It definitely shouldn't be something you reach for before you actually anticipate a need for it.

I partially agree with what you're saying but let's not pretend we weren't handling payments in 2005, some of us where anyway. I think what changed is the scale of things: we had a lot less people online back then.

I think the increased complexity in our architectures is correlated with the DevOps role coming to the picture, but I'm not sure there's a cause link there. My recollection from having lived through the initial years of DevOps (I began working professionally in 2000) is that an important goal was to reduce the terrible friction between dev and ops (the latter including sysadmins, DBAs, etc). Whatever the extra complexity we have now, I would not want to go back to the days when I carried a pager and responded to find out the problem was caused by an application I had no insight into, and there was no corresponding on call person on the side of the dev team. Another important goal was to manage infrastructure a bit closer to how we develop software, including the big step of having the configuration (or the code that generates it) in SCM. Another thing I don't miss is logging into a server to troubleshoot something and finding /etc/my.cnf, /etc/my.cnf.<some date>, /etc/my.cnf.test, etc. It's much easier to just run tig on either the file or the ansible/chef/whatever that generates it IMHO.

2005 was fullon enterprise websphere/weblogic era, so no, if anything it was much more complex (from architectural side) than today's python/nodejs or even spring boot solutions. Automation (bash/ant) plus ci like cruise control already there.

> you handle payments,

Yeah, because obviously nobody handled any payment in 2005 … The same can be said for everything in your list.

And more importantly, it's unlikely that your business is more complex than what it used to be in 2005. And if you're spending more resource to deliver the same business value, you're wasting them. (That's why PHP is still ubiquitous btw, it sucks by most standards, but it's good enough to do business and that's what matters).

>> Your automation may be an order of magnitude more complex than 2005, but it enables two orders of magnitude more functionality.

This!

The primary problems with DevOps are...

1. It is still in its infancy therefore it's changing quickly.

2. Bad (or no) documentation is much more painful than before. A single family house without blueprints can, usually, be adequately serviced; whereas, a 27 story office building cannot.

Also not pictured:

* 2005: ship it if it builds.

* 2022: run unit testing, deployment to beta, run integration testing, run UI testing, deployment to preprod, run internationalization testing, run regional/marketplace-specific testing, run consistency checks, run performance tests, deployment to prod.

I think the variable here isn't year, but where you work(ed).

Maybe, but the pipeline required to do all that in 2005 would be considerably more complex and brittle than the 2022 version using tools and infra designed for the job.

Missing the point:

That code in 2005 was better in every way.

Context: just learning loopback API framework. What a steaming pile of overengineered garbage.

All you did is describe the increase in complexity of the infrastructure. Which does not rebut the point, because that is the point. The infrastructure people are using now is much more complicated than what was common 15 years ago.

If you want to rebut this you need to demonstrate the kind of capabilities we have now thanks to this complexity that we could not have before.

> you handle payments

No you don't. Most people handle payments by integrating with a 3rd party service, most likely stripe or paypal.

Good point re payments.

Your system today doesn’t even handle left pad, outsourcing even that to a non deterministic tree of geo-distributed modules.

you handle payments, integrate with other services, queue tasks for later, and so on

This just means “use APIs”, adds {base_url, secret_key} pairs to a config file. Where are orders of magnitude devops-wise?

Integrating with other services makes your software more brittle as there are more points of failure from hardware and networking on your end, to API gateways, networking, and hardware on their end. Periodically those things tend to go sideways which means whatever it was your system was trying to do doesn't happen, or worse it only partially happens. Usually some poor engineer is then tasked with figuring out if this is an on-going problem or a one-off problem? Did it affect a single customer, or is it affecting all customers? Is it affecting a single instance, or is the problem happening across all instances? Is it a problem on our end, or is the 3rd party API misbehaving (again) today?

Generally you need solid APM and logging to support the operations of this.

Then there's queueing tasks for later and making sure you never lose messages between systems. All sorts of fun happens when you hit a capacity limit in your queueing system due to unintended/unnoticed design flaw and all of a sudden system performance starts to tank as things aren't getting processed due to too much stuff in the queue that isn't draining at a sufficient rate. You need to figure out is the queue actually draining or is it still increasing in size? Are all the worker nodes still running or did one (or several) of them hang and didn't die but simply isn't processing any jobs out of the queue but still consuming a spot in your auto-scaling group blocking a new healthy instance from coming online? Is it a problem in your software or is it actually a blip in operations from your cloud-provider?

It's way, way, way more complex than simply "chuck some API keys in a file and she'll be right!". That's hobby project level stuff, not realistic ops of a production system.

I’m literally working at automated finance and we are offloading these cases to client support, and late/next day status requests for b2b peers. The only devops-level technicality there is an in-process keep-alive system which prevents overwhelming the support repeatedly. What you’re describing tries to deal with these issues at the level where it is hard, and it is, but that’s exactly the road to complexity and infra costs (and infra issues as well). As a result, it trades simple client issues for hard technical ones, and you still need support. It’s cool to have an ideal incident-free system, but only when you can cover its costs - and more importantly its evolution barriers - by exactly that quality. Iow, don’t replace humans with machines either until machines learn to wipe their own ass, or until it’s just too much ass to manage efficiently anyway.

I’d fight at your side few years ago, but since starting to work in this field and asking around I realized nobody cares about that ideal way, cause it’s so expensive and hard to maintain, and the cost of change is prohibitive. It even left few scars on my mental health, exactly because I was too anxious to go this way after rotating in environments where devops is praised as something inevitable to survive. If you squint at us at the right angle you still can see devops, but I think we are just expressing two opposite sets of ideas, each applicable in its own type of a business env. You may still call that a hobby-level, and I’d even agree (cause it essentially is) if that hobby didn’t bring as much as to sustain and profit the company at the levels many companies would wish they were at. If it works and brings revenue who cares how it’s categorized.

Wanted to add, todays pipelines include a whole new level of security that was pretty much ignored in 2005.

Security adds complexity

> todays pipelines include a whole new level of security that was pretty much ignored in 2005.

The very opposite.

> Security adds complexity

If anything, complexity is the enemy of security

The question is, do you need all that or was/is PhP and Mysql enough for the job.

Extremely complicated architectures are a liability, not a feature to be proud of; increasing complication (i.e. costs) doesn't mean increasing functionality (i.e. value).

For example, why do you "queue tasks for later"? Do you have exceptionally punishing latency and throughput requirements that can only be met at a reasonable cost by not answering synchronously, or it's because your database doesn't do transactions?

Similarly, what do you do with "queues, caches, and so on"? Meet further extreme performance and availability requirements, or attempt to mask with additional complications the poor performance of inefficient complicated components?

In 2005, but also in 2000, web applications had already progressed past "just serving a web page", mostly without complicated architectures and therefore without the accompanying tools.

I think tool improvements made cargo-culting actually advanced state of the art software architectures and processes easy and affordable, creating a long term feedback loop between unnecessary demand for complexity (amateurs dreaming of "scaling up") and unnecessary development and marketing of advanced (but not necessarily good) complexity-management tools, often by the same amateurs.

Also not pictured--

2005: two system administrators wrote all automation using a handful of Bash, Perl and Python scripts AND LEAVE THE COMPANY a couple of years laters

20xx: new hired system administrators continue to rewrite scrips. no shared knowledge because scortched-earth policy in effect

2022: HN: DevOps is a failure -- you just need two system administrators...

> you handle payments, integrate with other services, queue tasks for later

I distinctly remember buying things on Amazon in 2005. Actually come to think of it, I did everything you list in 2005, at multiple companies.

I find this take apologetic. "But we're running on the cloud, we need this complexity", is a wrong take. Yes, the underlying services may need this, but the infrastructure managing these services don't need to be this complex.

Every complex tool can be configured to work in a simpler manner, and all configuration repositories directing these tools can be organized much better. It's akin to a codebase after all. Many code quality processes and best practices to apply to these, but sysadmins don't like to think like developers, and things get hairy (I'm a sysadmin who does development, I see both sides of the fence).

The sad part is, these allegedly more robust platforms do not provide the transparency neither to developers, nor to sysadmins, nor to users. In the name of faster development, logging/debugging gets awry, management becomes more complex and users can't find the features they have used to have.

Why? We decoupled systems and decided to add this most used feature at a later date, because it's not something making money. Now my account page even doesn't show my e-mail address, I can't change my subscription renewal date, or see my past purchases, why? They're at distant tables or these features are managed by other picoservices which are not worthy to extend or add more communication channels.

Result? Allegedly mature web applications with weird latencies and awkwardly barren pages, with no user preferences or details.

Adding layers and layers of complexity to patch/hide shortcomings of your architecture doesn't warrant a more complex toolset to manage it.

So someone overengineered something in 2022, and therefore, nothing's better?

How about my anecdata:

2010: your infrastructure is automated using a handful of Bash, Perl and Python scripts written by two system administrators. They are custom, brittle in the face of scaling needs, and get rewritten continuously as your market share and resulting traffic grows. Outages happen far too often, you think, but you would, because you're someone who gets paged for this shit, because you know a core system well... ...that got broken by a Perl script you didn't wrote.

2019: your infrastructure runs on EKS, applications are continuously deployed as soon as they're ready using Jenkins and Flux. You wrote some YAML, but it's far better than that Perl stuff you used to have to do. The IDE support is like night vs day. You have two sysops, or devops, or whatever, who watch over the infra. You've had to attend to a system outage once in the past two years, because an AWS datacentre overheated, and the sysops just wanted to be sure.

You write some YAML, the sysops write some CDK. Your system is far more dynamically scalable, auditable, and reliable.

My anecdote can totally beat up your anecdote.(In other words, this is a silly line of argument)

My 2020 looks like this:

no docker no k8s

1 server

  git repo
  /var/www/domain_name
  git clone git_url /var/www/domain_name/backend/
  cd /var/www/domain_name/backend/
  go build

Updates

  git pull
  go build
  systemctl restart domain_name.backend.service

I pay 46€/month and I'm looking forward to halve those costs. Server load is mostly <0.5 I call this the incubation server. If a project takes off I rent a more expensive, but dedicated, server. It's very unlikely that I ever need more than 1 single server per project.

I will never write microservices, I can scale fine with a monolith. Lately I even moved away from JS frontends to render everything with Go on the server. Yeah it requires more resources but I'll gladly offer those resources for lower response times and a consistent experience.

Sadly companies that are hiring don't see it that way. That's ok. I'll just stay unemployed and try building my own stuff until something succeeds again.

I had a 7 year long project that brought in 5-7k€/m. The server costed 60€/m. I can do that again. I know it's not your kind of scale or income level, but it allowed me to have a good life living it my way.

No one ever said a VPS with a shell script is terrible. You think of scale the wrong way. Scaling is not only about increasing from 10 requests / second to 1000 requests / second. Scaling is about organizational scale too, i.e. how do you ensure going from 2 to 20 developers increases productivity by at least 20x and not 1.5x?

Tools like Docker, Kubernetes and whatever absolutely help in that regard.

I think it's somewhat disingenuous to compare DevOps requirements of 5-7k/m projects with systems run and operated by companies in the mid market.

That said, something I often wonder about is if you could minus out 100% of the cruft systems run by realistic sized companies, exactly how cheaply could you run them and with what DX? Half of the problem is things built by 100 people with competing and shifting priorities will never result in a clean, tidy, sensible system and it's mighty difficult to minus out the effects that the organization scale has on the end result.

I'm currently working through building a hobby project on that as far as I know will only ever have one user, but I'm enjoying the total freedom to take my sweet time building it exactly as nice as I wish the systems I wrangle in my day job would be and I'm 100% looking to run it for free or as close to free but with as much performance as I can get because why the hell not? It's a totally different ballgame.

I didn't understand half the things you wrote. What's a company in the mid market? (nm I looked it up) What cruft? Not a native English speaker, you way of expressing yourself is hard to understand for me. DX?

Are there really things built by 100 people, if so, why do you need 100 people? Why can't you do with 1 lead 1-2 database guys 1-2 code monkeys? Why can't this be done in a monorepo and a monolith? Why does it have to run -in-the-cloud- on other people's computers?

I had a project that was ranked in the top 1000, according to Alexa, on a single server. But it didn't bring in enough revenue and took up most of my time so I shut it down. I re-launched it 15 years later but it's dead. No one knows or remembers the domain anymore save for bots who keep hitting those "fkk-sex-nude-porn" etc spam links.

Back then you could make a site popular with 1€/day on Adwords, nowadays ... lol, this won't even lead to your ads being displayed, anywhere.

Go can handle 500 million visitors per month on 10 year old hardware (= 1 server). Which "mid market" company has 500 million visitors per month?

Writing websites/apps isn't complicated. For me anyway. You figure out the data models, write the use cases and you're half way. The other half is writing the display layer to make use of that data.

You make it all sound like the requirements or the product is different. It's not. It's all the same. You can have observability without k8s. You can scale without k8s. You don't need a managed database. Man this stuff is simple. It's people how are trying to sell you cloud and microservices and whatnot that make it all sound so hard. A good software developer if spending his knowledge and lifetime to build something for you that is built to last, because you can't apparently do it yourself or don't want to. It will last even when he isn't part of your company anymore. He could've built the same for himself and monetize it, instead of bowed down to you (not your personally) and opted for steady income.

I understand how, let's be honest, when we talk DevOps we mean k8s, so I understand how sweet a siren's song k8s sings. But it's ultimately a waste of resources. It's a solution asking for a problem. Until you reach proportions that require k8s you'll be completely satisfied with a 3 server setup, that is Go and pick a database. I promise, I guarantee.

That 5-7k/m project had 30 people concurrent at most. It had 30TB/m outgoing traffic at most. How much does 30TB egress cost in GCP,AWS etc? It used to be about 3k, I believe it's 1/3 of it now.

Why would the principles that are valid for a "small" project not apply to a "mid market company"? More features? So what? The principle remains the same. Boring, same old. Data models, wrappers, display layer. It's the same for all, your beloved FAANG, mid market, small business, single owner.

Whatever.

This is a build deployment perspective.

I for one do not miss hosts never being patched because all those slight modifications to systems files that were tweaked several builds ago and now everyone is too scare to touch.

I won't miss the 12 month projects to upgrade some dated software to a slightly less dated version of that same software.

From my perspective in Security, DevOps has made life much better.

At my first company, our builds happened whenever the release engineer (he was friends with the milk man and chimney sweep) felt like "doing a build".

As another example, CI/CD adds a lot more work and maintenance but it results in better overall hygiene.

The ability to spin up a box, have it run insecure code, and then spin it down; and the ability to do that all day long, is worth it for the security benefits that all this complexity entails.

> The ability to spin up a box, have it run insecure code, and then spin it down; and the ability to do that all day long

What's the best way to do that? I have some insecure code that needs to run about 6x a day, and so far my best thought has been an isolated box outside my network that does the internet based fetches, translates the data and then submits them over the web to another service that verifies/checks the output.

I run 50+ smallish applications on AWS using Bitbucket Pipelines, Fargate, Aurora MySQL, S3, Cloudfront and a few other services. Most of the setup is scripted using very simple Cloudformation scripts. I estimate that I spend maybe 10% of my time on this and the rest of my time on ordinary dev/architecture tasks.

Before Docker and AWS this would have taken me so much more time.

The only drawback is that we have a hard time finding other developers in the company that want and have the time to learn the setup. It's not very complicated, but require some familiarity with the AWS ecosystem. It can seem daunting to someone who has to learn it from scratch.

> The only drawback is that we have a hard time finding other developers in the company that want and have the time to learn the setup

This is my experience as well in enterprise cloud. I don't get it. Have these people seen what cloud jobs pay for less work?

1997: a team of 5 sys admins, 3 of them functional alcoholics, writing only in Bash scripts, manage over 2000 internet facing SPARC machines.

A lot of DevOps is actually CVOps - stuff that people get familiar with so they can put it in their resume.

What was wrong with the other 2?

Dysfunctional alcoholics.

Those bash scripts probably still in place and working, meanwhile modern ways of managing the servers have been recreated a dozen times over the last 25 years as every time a new person comes in there's always a better way of doing things.

The difference is now you're a failure if you stay at the same job for more than 2 or 3 years.

CVOps - hahahaha. I've always heard and used the term "Resume Driven Development" but I guess CVOps is a nice term too.

It's usually always a solution with an overly complex chain of tools that only do a small part of deployment/security tasks because it's a food chain, where each vendor can eat a part of the company's budget consistently, based on a problem that really isn't consistently solved...

Apps are still no more secure because there are several points where they can be compromised, rather than just a few involved in a less automated, but more easily replicate-able process. Also, I don't need "flavor of the month" skills to get things done. There is always a revolving door of fly-by-night-hype tools and brands that regularly rise and fall in the IT world... I avoid them (new hyped products) like the plague. I'm fine with being the stubborn middle aged IT guy now. :P

It's all a food chain based on making money. What matters to me most is whether money is being made from the product that is deployed, and if it's simple, reliable, and secure enough to be worth development. I don't do my job to make a bunch of companies money by using their DevOps tools.

Screw impressing other engineers with solution complexity every time. Functional reliability always wins at the end of the day. Leveraging a massive list of Ops tools only creates a huge backlog of update work, designing efficiency and simplicity in most of my solutions is what ultimately pleases most of my clients.

I think you mean:

> your infrastructure is automated using 10 extremely complex devops tools

... held together by ...

> a handful of Bash, Perl and Python scripts written by two system administrators. They are custom, sometimes brittle and get rewritten every 5 years.

We learned nothing in the last decades. If at all, complexity for the same things multiplied.

In 2005 your infrastructure provisioning wasn’t automated. The complexity has increased, but so has what we get. Being able to provision new hardware stacks like software is amazing, in 2005 I had to get quotes from hosting providers.

Whereas now nobody cares about the cost because it's all hidden away in a massive bill at the end of the month?

True but to be fair modern infra does a hell of a lot more

2005: no cloud, had to order 1Us, wait, rack up. Needed a DBA for the database, a network sysadmin for the networking, all to serve a simple website with not the same level of HA. We are doing way more now, which needs some more complexity and yes, in many cases we are overengineering it.

2005 Linode sold me VMs, no need for a DBA or network admin for a simple main/reserve website

17 years later and getting more than 364 days uptime out of AWS is apparently "not worth the cost"

2005: you had 4 people that understand what everything did

2022: you have a team of monkeys clicking buttons

Joking aside, it seems like the developers these days don't have the understanding that they did a while back. Not being involved with the nitty-gritty causes them to just write code willy-nilly.

Today's shit has 10x or 100x more throughput, it makes sense that upgrading data response and availability requires more people.

But, todays devops has become a proprietary mix of aws protocols, constantly changing standards and languages.

I still use bash scripting wherever I can, it is much more simple and has been ultimately unchanged for decades, which is nice for compatibility

Author claim is more about how to make people work together on deployment. Rather than a rant on devops tools.

You can do simple things with modern devops tools. You can go off rails with simple scripts. It's not the tooling, it's about engineering maturity and the requirements of what you're building.

IaC wasn't even prevelant or a production ready thing back in 2005. I'm unsure what magical bash scripting would do any of that, maybe it the data centres too!

IaC wasn't a thing because you honestly didn't need code to solve the vast majority of deployment problems. It was a configuration issue.

Not 2005, but a year later in 2006 I was using cfengine to deploy code and configuration to servers from an svn repository. The same svn repository had dhcpd configs that described pretty much every device on the network. The dhcp configs also pointed to a tftp service from which new nodes pxe booted to an installer which pulled down the node specific kickstart, and provisioned the machine.

We didn't call it infrastructure as code, but it sure fucking smells the same.

Perl/Bash/Python? Maybe for non-mission-critical things. By 2005 everyone who needs stability/scalability were using J2EE.

2005: your infrastructure powers a webshop with $1m annual revenue

2022: your infrastructure powers a $5b startup

All you’ve demonstrated is that some folks are bad at SRE.

>to the people claiming that today's infra does more things... No, I'm comparing stuff with the same levels of availability, same deployment times, same security updates.

ok but in my experience it seems like more things are being done in places I see with devops nowadays versus back then. I mean I know you say that it's the same, but it's hard to believe your statement in a comment versus my lying eyes. It seems more likely to me that your two examples are both actually fictitious and thus it is easy for you to say that they are exactly the same in what gets output - or have you been at the same place for 17 years, seen the changes, yet have had no input on the company to stop the madness? Because if the latter that would also seem... weird.

Were microservices a thing back in 2005? Honest question, I always assumed that SOA was more of a newer philosophy in web software. The scale of what we build has changed a lot over the years, as well as the need to handle the variance of scale through techniques like auto-scaling. All of that adds an incredible amount of complexity in systems that surely didn't exist 18 years ago.

I don't think SOA was in common discussion in 2005, I think more about 2007 would sound right, Rest was pretty much the winner by 2009. But perhaps my memories here are warped by my personal career and not having to have the arguments after 2009.

No I don't think microservices was anywhere at that time, although one could argue that they are a repackaging of the ideas of Small Pieces, Loosely Joined https://en.wikipedia.org/wiki/Small_Pieces_Loosely_Joined or an architectural expression of loose coupling https://en.wikipedia.org/wiki/Loose_coupling for corporate data.

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