Why is Kubernetes getting so popular? | Hacker News Reader

Why is Kubernetes getting so popular?

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Main benefits of Kubernetes:

• Lets companies brag about having # many production services at any given time

• Company saves money by not having to hire Linux sysadmins

• Company saves money by not having to pay for managed cloud products if they don't want to

• Declarative, version controlled, git-blameable deployments

• Treating cloud providers like cattle not pets

It's going to eat the world (already has?).

I was skeptical about Kubernetes but I now understand why it's popular. The alternatives are all based on kludgy shell/Python scripts or proprietary cloud products.

It's easy to get frustrated with it because it's ridiculously complex and introduces a whole glossary of jargon and a whole new mental model. This isn't Linux anymore. This is, for all intents and purposes, a new operating system. But the interface to this OS is a bunch of <strike>punchcards</strike> YAML files that you send off to a black box and hope it works.

You're using a text editor but it's not programming. It's only YAML because it's not cool to use GUIs for system administration anymore (e.g. Windows Server, cPanel). It feels like configuring a build system or filling out taxes--absolute drudgery that hopefully gets automated one day.

The alternative to K8s isn't your personal collection of fragile shell scripts. The real alternative is not doing the whole microservices thing and just deploying a single statically linked, optimized C++ server that can serve 10k requests per second from a toaster--but we're not ready to have that discussion.

I am ready! NetBSD is running on the toaster. I think haproxy can do 10K req/s. tcpserver on the backends. I only write robust shell scripts, short and portable.

As a spectator, not a tech worker who uses these popular solutions, I would say there seems to be a great affinity amongst in the tech industry for anything that is (relatively) complex. Either that, or the only solutions people today can come up with are complex ones. The more features and complexity, the more something is constantly changing, the more a new solution gains "traction". If anyone reading has examples that counter this idea, please feel free to share them.

I think if a hobbyist were to "[deploy] a single statically linked, optimized [C++] server that can serve 10k requests per second from a toaster" it would be like a tree falling in the forest. For one because it is too simple, it lacks the complexity that attracts the tech worker crowd, and second, because it is not being used by well-known tech company and not being worked on by large numbers of people, it would not be newsworthy.

I can see your point for small hobby projects. But enterprise web development in C++ is no fun at all. For example: "Google says that about 70% of all serious security bugs in the Chrome codebase are related to memory management and safety." https://www.zdnet.com/article/chrome-70-of-all-security-bugs...

Developer time for fixing these bugs is in most cases more expensive, than to throw more hardware at your software written in a garbage collected language.

> because it is not being used by well-known tech company and not being worked on by large numbers of people, it would not be newsworthy.

And at this point the hobbyist might wonder, "why isn't my toaster software being used by well-known companies? where are the pull requests to add compatibility for newer toaster models?"

> As a spectator, not a tech worker who uses these popular solutions, I would say there seems to be a great affinity amongst in the tech industry for anything that is (relatively) complex.

I think you have it backwards. General/abstract solutions (like running arbitrary software with a high tolerance for failure) have broad appeal because they address a broad problem. Finding general solutions to broad problems yields complexity, but also great value.

> great affinity [...] for anything that is (relatively) complex.

That, and mixture of a sunken cost fallacy/lack of the ability to step back and review if the chosen solution is really better/simpler rather than a hell of accidental complexity. If you've spend countless months to grok k8s and sell it to your customer/boss, it just has to be good, doesn't it?

Plus, there's a great desire to go for an utopian future cleaning up all that's wrong with current tech. This was the case with Java in the 2000s, and is the case with Rust (and to a lesser degree with WASM) today, and k8s. Starting over is easier and more fun than fixing your shit.

And another factor are the deep pockets of cloud providers who bombard us with k8s stories, plus devs with an investment into k8s and/or Stockholm syndrome. Same story with webdevs longing for nuclear weapons a la React for relatively simple sites to make them attractive on the job market, until the bubble collapses.

But like with all generational phenomenae, the next wave of devs will tear down daddy-o's shit and rediscover simple tools and deploys without gobs of yaml.

I think the popularity of Kubernetes is that it can run all kinds of workloads on a single platform not really its performance. I've been in Ops business for over a decade now, in my case every single customer has a completely different kind of application architecture and sometimes even with similar use cases (i.e like ecom app or chatbots etc). With Kubernetes the differences are largely irrelevant encapsulated nicely within the container. This means in my universe I can run all of our customers on a single architecture and the differences are nicely abstracted.

Same feeling here but I came to understand that it's the enterprise and the design by committee that brings in the complexity.

K8S is developed by a multitude of very large companies. Each with their own agenta/needs. All of them have to be addressed. Thus the complexity. If you think about it they probably manage to keep the complexity to relatively low levels. Maybe because it is pushed to the rest of the ecosystem (see service meshes for example).

Being pushed by the behemoths also explains the popularity. Smaller companies and workers feel that this is a safe investment in terms of money and time familiarizing with the tech stack so they jump on. And the loop goes on.

Main business reason for all that though I think it's the need of Google et all to compete with AWS creating a cloud platform that comes to be a standard and belongs to no-one really. In this sense it is a much better, versatile and open ended openstack attempt.

That's kind of why people use Google Go. No memory issues, statically linked, easy cross-compile, and it can handle 10k requests on a toaster.

And yes, there is less fancy companies like one where I work where we don't use Kubernetes because it's kind of overkill if all of your production workload fits onto 2 beefy bare metal servers.

I can see a point in using Docker to unify development and production environments into one immutable image. But I have yet to see a normal-sized company that gets a benefit from spreading out to hundreds of micro instances on a cloud and then coordinating that mess with Kubernetes. Of course, it'll be great if you're a unicorn, but most people using it are planning for way more scaling than what they'll realistically need and are, thus, overselling themselves on cloud costs.

> I would say there seems to be a great affinity amongst in the tech industry for anything that is (relatively) complex.

hah, i've noticed that too - specifically around k8s/deployments/system architecture too. i've taken to calling it complexity fetishisation.

i think it stems from the belief/hope that, whilst they don't "google sized" data today, they need to allow for it.

i'll take two toasters, please.

Deploy that toaster on k8s and now you have a vc funded startup.

This, and more but it's all in the same vein.

I was pretty skeptical too but then handed over a project which was a pretty typical mixed bag: Ansible, Terraform, Docker, Python and shell scripts, etc... Then I realized relying on Kubernetes for most projects has the huge benefit of bringing homogeneity to the provisioning/orchestration which improves things a lot both for me and the customer or company I work for.

Let's be honest here, in many cases it does not make a difference whether Kubernetes is huge, inefficient, complicated, bloated, etc... or not. It certainly is. But just the added benefit of pointing at a folder and stating : "this is how it is configured and how it runs" is huge.

I was also pretty skeptical of Kustomize but it turned out to be just enough.

So, like many here. I kind of hate it but it serves me well.

As a fellow Kubernetes-hater, this is the best explanation I've read for its virality. Thanks!

I am still not convinced by Kubernetes, but you make a good point.

> Company saves money by not having to hire Linux sysadmins

Citation? In my experience companies hire more sysadmins when adopting k8s. It's trivial to point at the job reqs for it.

> Company saves money by not having to pay for managed cloud products if they don't want to

Save money?! Again citation. What are you replacing in the cloud with k8s? In my experience most companies using k8s (as you already admitted) don't have a ton of ops experience and thus use more cloud resources.

> Treating cloud providers like cattle not pets

Again. Citation? Companies go multi-cloud not because they want to but because they have different teams (sometimes from acquisition) that have pre-existing products that are hard to move. No one is using k8s to get multi-cloud as a strategy.

> It's going to eat the world (already has?).

Not it won't. It's actually on the downtrend now. Do you work for the CNCF? Can you put in a disclaimer if so?

> just deploying a single statically linked, optimized C++ server that can serve 10k requests per second from a toaster

completely un-necessary; most of the HN audience is not creating a c++ webserver from scratch; most of the HN audience can trivially serve way more than 10k reqs/sec from a single vm (node, rust, go, etc. are all easily capable of doing this from 1 vcpu)

You says all what I want to say.

I don't agree with the last paragraph.

Your C++ example is orthogonal to the deployment aspect because it discusses the application. Kubernetes and the fragile shell scripts are about the deployment of said application.

How are you going to deploy your C++ application? Both options are available, and I would wager that in most cases, Kubernetes makes more sense, unless you have strict requirements.

Kubernetes is for orchestrating a distributed system. What I was suggesting is to (1) make a monolith and (2) make it fast, light and high-throughput. The goal of your service is to reliably serve users at scale; this is just another way of doing it, just much more esoteric.

A "C++ monolith" allows me to potentially bypass a lot of this deployment stuff because it could serve lots (millions) of users from a single box.

In a world where your architecture is that simple I don't think kubernetes would be the choice for long.

I think for the average application there's still something to be said for manual cross-layer optimization between infrastructure, application, and how both are deployed.

What I mean is we can't yet draw too clear a line between the application and how it's deployed because there are real tradeoffs between keeping future options open and getting the product out the door. A strength of kubernetes is that if you get good at it it works for a variety of projects, but a lot of effort is needed to get to that point and that effort could have gone into something else.

Disagree with the GUI part. Text based configuration is stable, version-controllable, and intuitive to use. Look at Xcode for a nightmare of GUI configuration.

> stable, version-controllable, and intuitive to use

Neither of those features are inherently impossible to do with GUIs. Alternatively, you can have a GUI editing your text based configuration.

Although, doesn't look as cool so, here we are.

> • Company saves money by not having to pay for managed cloud products if they don't want to

In some cases, the cost of a managed cloud product may be cheaper than the cost of training your engineers to work with K8s. It just depends on what your needs are, and the level of organizational commitment you have to making K8s part of your stack. Engineers like to mess around with new tech (I'm certainly guilty of this), but their time investment is often a hidden cost.

> The alternatives are all based on kludgy shell/Python scripts or proprietary cloud products.

The fact that PaaS products are proprietary is often listed as a detriment. But, how detrimental is it really? There are plenty of companies whose PaaS costs are insignificant compared to their ARR, and they can run the business for years without ever thinking about migrating to a new provider.

The managed approach offered by PaaS can be a sensible alternative to K8s, again it just depends on what your organizational needs are.

"The alternative to K8s isn't your personal collection of fragile shell scripts. The real alternative is not doing the whole microservices thing and just deploying a single statically linked, optimized C++ server that can serve 10k requests per second from a toaster--but we're not ready to have that discussion."

You are writing this and i thought yesterday how to extend my current home k8s setup even further.

I would even manage that little c++ tool through k8s.

K8s brings plenty of other things out of the box: - Rolling update - HA - Storage provisioning (which makes backup simpler) - Infrastructure as code (whatever your shellscript is doing)

I think that the overhead k8s requires right now, will become smaller over the years, it will be simpmler to use it, it will become more and more stable.

It is already a really simple and nice control plane.

I like to use a few docker containers with compose. But if i already use docker compose for 2 projects, why not just using k8s instead?

You still need quite a lot of stuff for that one, statically linked, heavily optimized C++ server. In a way, that's actually what k8s comes from ...

How do you manage deployments for that C++ monolith? How is the logging? Logrotate, log gathering and analysis? Metrics, their analysis and and display? What happens when you have software developed by others that you might also to want to deploy? (If you can run a company with only one program ever deployed, I envy you).

All of that is simplified by kubernetes by simply making all stuff follow single way - "classical" approaches tend to make Perl blush with the amount of "There is more than one way to do it" that goes on.

> • Company saves money by not having to hire Linux sysadmins

.. but hire others to manage k8s? Or existing software engineers have to spend time doing so?

Many of the other points don't seem unique to k8s either.

I do like the alternative you've suggested though.

Are there any decent GUI services for creating the YAML files?

Most of it can be managed by text boxes on the front-end with selections and then it can just generate or edit the required files at the end of a wizard?

Your static app won't scale. Once your kernel is saturated with connections, once your buffers are full, you will get packets dropped. Your app may crash unexpectedly so you need to run it in an infinite loop. And of course your static example is a simple echo app or hello world. That works fine from a toaster. In the real world we use databases where every store takes a significant time to process and persist. You quickly overgrow a single server. Then you need distributed systems and a way to do versioning so you use containers and then you need an orchestrator so you pick K8S because it's most mature and there are many resources around. And then you can even do rolling updates and rollbacks. Finally you use Helm, Terraform and Terragrunt and never look back. It works surprisingly good. I lost several years by learning all this stuff, it was difficult but it was worth it. I have more visibility into everything now thanks to metrics-server, Prometheus Operator, Grafana, Loki and I have two environments so I can update deployments in one environment and test, once tested ok, I can apply to live. No surprises. No need to run 5 year old versions of software and fear updating it...

AFAIK, Yandex Taxi uses "single statically linked, optimized C++ server that can serve".

Can't agree more. To this add the moving-sand landscape of an ecosystem there.

But then again it's actually the first public/popular attempt on a cloud OS. There might be a next one with better ergonomics than yamls.

Well aren't Openshift and Rancher offering those ergonomics?

I've never coded in C++, so I'm curious - what is the feedback loop like? My understanding is that since C++ is a compiled language, you can't "hit refresh" the same way you can in JavaScript/Ruby/etc.

Is that an incorrect understanding? I know C++ is supposed to be great for performance, but in truth I've never needed anything to be that fast. And if I can get the job done just as well with something I already know, I won't bother learning something like C++ which has a reputation for not being approachable.

But maybe I don't have full context?

Technically you can have some sort of command in your C++ program to make it fork itself, that is restart itself disk, maybe after freeing non-shareable resources like listening sockets. One could even imagine that this command includes self-recompilation by invoking make (or whatever your build system is).

An alternative is to have your program expose its pid somewhere, and your make file could send a signal to that pid when a new version is ready. The advantage is that if your program crashes on startup, you don't have to do something different to restart it.

If your application has to include an "auto-update" feature (like browsers), use that instead - its certainly better to eat your own dog food. Maybe just hack it a little bit so that you can force a check programmatically (e.g. by sending it a signal) and so that it connects to a local updates server.

It is true that C++ is an overly complicated language; if you don't need maximal performance, you have a lot of AoT languages that are a bit slower ( something around 0.5 C ) but more "user-friendly". In particular, if you are into servers and want fast edit-compile-run loops, Go might be a good choice.

> I've never needed anything to be that fast

In a world where you are billed by ressources used, wouldn’t it be a good idea to have light and fast services that don’t consume those ressources ?

I’ve been wondering this for a time now.

Go will get you 90% there in performance. I recommend that instead of C++ because it compiles fast for that edit-build-refresh cycle. Go also has the benefit of producing static binaries by default which solves a lot of the problems Docker was for.

C++ is more for the extreme control over memory. An optimized C++ server can max out the NIC even on a single core and even with some text generation/parsing along the way.

If you're a ruby user looking for extra performance, try Crystal[1]. Everything you love + types compiled to native binaries. You can set up sentry[2] to autocompile and run every time you save, so the feedback loop is just as tight.

[1]: https://crystal-lang.org/

[2]: https://github.com/samueleaton/sentry

It doesn't have to be C++ of course. The main point of OP lies in C++ being fast and easy to deploy (at least it can be). Go, Rust, to some extend C# and Java also fall in that category. This feature set becomes interesting, because it has the potential to simplify everything around it. If you don't need high fault tolerance you can go a very long way with just a single server, maybe sprinkled with some CDN caching in front if your users are international.

If you do need higher availability you can go the route StackOverflow was famous for for quite some time of having a single ReadWrite master server, a backup master to take over and a few of ReadOnly slave servers, IIRC. With such setups you can ignore all the extra complexities cloud deployments bring with them. And just because such simple setups make it possible to treat servers like pets, doesn't mean they have to be irreproducible undocumented messes.

The other day (actually years) I did a gamejam in Go, I bound Cmd+R to essentially the following:

    system("go build")
    exec("./main")

Not a literal hot code reload that some advanced stuff get to enjoy, but nice enough to shorten the feedback loop.

Working in strongly statically typed languages is quite different, because the types (and the IDE/compiler) guides you. You don't have to hit refresh that often.

Even just working in TypeScript with TSed and a few basic strongly typed concepts (Rust's Result equivalent in TS, Option or Maybe, and typed http request/response, and Promise and JSON.parse) makes a big difference.

A lot less okay, just echo/print/log this object (or look up documentation eew), look at what does this look like and how to transform it into what I need. Instead you do that in the IDE.

I like that alternative. Especially now that we have Rust and Actix Web.

I would speculate that for companies these two statements will be exclusive:

• Company saves money by not having to hire Linux sysadmins

• Company saves money by not having to pay for managed cloud products if they don't want to

As a developer I want to right code, not manage a Kubernetes installation. If my employer wants the most value from my expertice they will either pay for a hosted environment to minimize my time managing it or hire dedicated staff to maintain an environment.

Absolutely agree.

A lot of people is just really interested in having something complex instead of understanding their actual needs.

And this is why I only give Linux like one decade more to still be relevant on the server.

With hypervisors and managed environments taking over distributed computing, if there is a kernel derived from Linux or something completely different, it is a detailed that only the cloud provider cares about.

That doesn't really make sense in the context of docker.

It's still Linux inside the container. Even if it's some abstract non-Linux service thing running the container, what happens in the container is still the concern of the developer.

or a Free Pascal server (powered by mORMot (https://github.com/synopse/mORMot))? Natively compiled, high performance, and supports almost all OS's and CPU's

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What is your estimate about when we ll be ready to have that discussion?

So now it's kubernetes + kludgy shell/Python scripts.

If it makes things more deterministic, then yeah, why not?

I don't think that kubernetes is getting popular at all.

If you really think that deploying a single binary is an alternative to microservices then you don't understand microservices.

> The real alternative is not doing the whole microservices thing and just deploying a single statically linked, optimized C++ server that can serve 10k requests per second from a toaster--but we're not ready to have that discussion.

The alternative is to have a old and boring cluster of X identical java nodes which host the entire backend in a single process... The deployment is done by a pedestrian bash script from a Jenkins. It used to work fine for too long I guess and folks couldn't resist "inventing" microservices to "disrupt" it.

I’ll take a shot.

k8s is popular because Docker solved a real problem and Compose didn’t move fast enough to solve orchestration problem. It’s a second order effect; the important thing is Docker’s popularity.

Before Docker there were a lot of different solutions for software developers to package up their web applications to run on a server. Docker kind of solved that problem: ops teams could theoretically take anything and run it on a sever if it was packaged up inside of a Docker image.

When you give a mouse a cookie, it asks for a glass of milk.

Fast forward a bit and the people using Docker wanted a way to orchestrate several containers across a bunch of different machines. The big appeal of Docker is that everything could be described in a simple text file. k8s tried to continue that trend with a yml file, but it turns out managing dependencies, software defined networking, and how a cluster should behave at various states isn’t true greatest fit for that format.

Fast forward even more into a world where everybody thinks they need k8s and simply cargo cult it for a simple Wordpress blog and you’ve got the perfect storm for resenting the complexity of k8s.

I do miss the days of ‘cap deploy’ for Rails apps.

> k8s is popular because Docker solved a real problem and Compose didn’t move fast enough to solve orchestration problem. It’s a second order effect; the important thing is Docker’s popularity.

I introduced K8s to our company back in 2016 for this exact reason. All I cared about was managing the applications in our data engineering servers, and Docker solved a real pain point. I chose K8s after looking at Docker Compose and Mesos because it was the best option at the time for what we needed.

K8s has grown more complex since then, and unfortunately, the overhead in managing it has gone up.

K8s can still be used in a limited way to provide simple container hosting, but it's easy to get lost and shoot yourself in the foot.

>Before Docker there were a lot of different solutions for software developers to package up their web applications to run on a server.

There are basically two relevant package managers. And say what you will about systemd, service units are easy to write.

It's weird to me that the tooling for building .deb packages and hosting them in a private Apt repository is so crusty and esoteric. Structurally these things "should" be trivial compared to docker registries, k8s, etc. but they aren't.

.rpm and .deb are geared more towards distributions needs. Distributions want to avoid multiplying the number of components for maintenance and security reasons. Bundling dependencies with apps is forbidden in most distribution policies for these reasons, and the tooling (debhelpers, rpm macros) actively discourage it.

It's great for distributions, but not so great for custom developments where dependencies can either be out of date or bleeding edge or a mix of the twos. For these, a bundling approach is often preferable, and docker provides a simple to understand and universal way to achieve that.

That's for the packaging part.

Then you have the 2 other parts: publishing and deployment.

For publishing, Docker was created from the get go with a registry, which makes things relatively easy to use and well integrated. By contrast, for rpm and deb, even if something analog exists (aptly, pulp, artifactory...) it much more some tools created over time which work on top of one another, giving a less smooth experience.

And then, you have the deployment part, and here, with traditional package managers, it difficult to delegate some installs (typically, the custom app develop in-house) to the developers without opening control over the rest of the system. With Kubernetes, developers gained this autonomy of deployment for the pieces of software under their responsability whilst still maintaining separation of concerns.

Docker and Kubernetes enabled cleaner boundaries, more in line with the realities of how things are operated for most mid to large scale services.

Which two package managers do you mean?

dpkg, rpm, nix, snap, dnf, and I'm sure someone is going to respond with package managers I forgot.

> Docker solved a real problem

> everybody thinks they need k8s and simply cargo cult it for a simple Wordpress blog

docker _also_ has this problem though. there are probably 6 people in the world that need to run one program built with gcc 4.7.1 linked against libc 2.18 and another built with clang 7 and libstdc++ at the same time on the same machine.

and yes, docker "provides benefits" other than package/binary/library isolation, but it's _really_ not doing anything other than wrapping cgroups and namespacing from the kernel - something for which you don't need docker to do (see https://github.com/p8952/bocker).

docker solved the wrong problem, and poorly, imo: the packaging of dependencies required to run an app.

and now we live in a world where there are a trillion instances of musl libc (of varying versions) deployed :)

sorry, this doesn't have much to do with k8s, i just really dislike docker, it seems.

Of course the correct approach is the NixOS one. What docker really did is solve the packaging, distribution, and updating problem.

The dependency thing is just the fallout of the (bad) default provided by distributions.

I am a big fan of using namespaces via docker, in particular for development. If I want to test my backend component I can expose a single port and then hook it up to the database, redis, nginx etc. via docker networks. You don't need to worry about port clashes and it's easy to "factory reset".

In production this model is quite a good way to guarantee your internal components aren't directly exposed too.

> docker _also_ has this problem though. there are probably 6 people in the world that need to run one program built with gcc 4.7.1 linked against libc 2.18 and another built with clang 7 and libstdc++ at the same time on the same machine.

You are supposed to keep only a single process inside one docker container. If you want two processes to be tightly coupled then use multi-container pods.

Hit the nail on the head. How else could you at the push of a button not just get a running application but an entire coordinated system of services like you get with helm. And deploying a kubernetes cluster with kops is easy. I don't know why people hate on k8s so much. For the space I work in it's a godsend

Good points but I think it would be accurate to say that Docker solved a developer problem. But developers are only part of the story. Does Kubernetes solve the business' problem? The user's problem? The problems of sys admins, testers, and security people? In my experience it doesn't (though I wouldn't count my experience as definitive).

At my company we have had better success with micro-services on AWS Lambda. It has vastly less overhead than Kubernetes and it has made the tasks of the developers and non-developers easier. "Lock-in" is unavoidable in software. In our risk calculation, being locked into AWS is preferable than being locked into Kubernetes. YMMV.

> I do miss the days of ‘cap deploy’ for Rails apps.

Oh boy I do not miss them. Actually I'm still living them and I hope we can finally migrate away from Capistrano ASAP. Dynamic provisioning with autoscaling is a royal PITA with cap as it was never meant to be used on moving targets like dynamic instances.

>I do miss the days of ‘cap deploy’ for Rails apps.

Add operators, complicated deployment orchestration and more sophisticated infrastructure... It is hard to know if things are failing from a change I made or just because there are so many things changing all the time.

What happens if you give the mouse a hammer?

For me, and many others: infrastructure as code.

Kubernetes is very complex and took a long time to learn properly. And there have been fires among the way. I plan to write extensively on my blog about it.

But at the end of the day: having my entire application stack as YAML files, fully reproducible [1] is invaluable. Even cron jobs.

Note: I don't use micro services, service meshes, or any fancy stuff. Just a plain ol' Django monolith.

Maybe there's room for a simpler IAC solution out there. Swarm looked promising then fizzled. But right now the leader is k8s[2] and for that alone it's worth it.

[1] Combined with Terraform

[2] There are other proprietary solutions. But k8s is vendor agnostic. I can and have repointed my entire infrastructure with minimal fuss.

I'm not sure "a plain ol' Django monolith" with none of the "fancy stuff" is either what people are referring to when they say "kubernetes", or a great choice for that. I could run hello world on a Cray but that doesn't mean I can say I do supercomputing. Our team does use it for all the fancy stuff, and spends all day everyday for years now yamling, terraforming, salting, etc so theoretically our setup is "entire application stack as YAML files, fully reproducible", but if it fell apart tomorrow, I'd run for the hills. Basically, I think you're selling it from a position which doesn't use it to any degree which gives sufficient experience required to give in-depth assessment of it. You're selling me a Cray based on your helloworld.

So are you saying that, no matter what, if you want to reply your whole infrastructure as code (networks, dmz, hosts, services, apps, backups etc ) that you are going to have to reproduce that somehow (whatever the combo of AWS services are, OR just learn K8S

Effectively, "every infrastructure as code project will reimplement Kubernetes in Bash"

Swarm is still supported and works. I have it running on my home server and love it.

Kubernetes is fine, but setting it up kind of feels like I'm trying to earn a PhD thesis. Swarm is dog-simple to get working and I've really had no issues in the three years that I've been running it.

The configs aren't as elaborate or as modular as Kubernetes, and that's a blessing as well as a curse; it's easy to set up and administer, but you have less control. Still, for small-to-mid-sized systems, I would still recommend Swarm.

There's an offshoot of this that I see from developers, especially at old, stodgy companies.

Once everything is "infrastructure as code", the app team becomes less dependent on other teams in the org.

People like to own their own destiny. Of course, that also removes a lot of potential scapegoats, so you now mostly own all outages, tech debt, etc.

Conversely I think the trend of writing infrastructure as yaml may be the worst part of modern ops. It’s really hard to think of a worse language for this.

> I can and have repointed my entire infrastructure with minimal fuss.

When you get to that blog post please consider going in depth on this. Would love to see actual battletested information vs. the usual handwavy "it works everywhere".

Have you tried or considered Nomad (from the makers of Terraform)?

With "Swarm", do you mean Docker Swarm? Why has it "fizzled"?

The way I learned it in Bret Fisher's Udemy course, Swarm is very much relevant, and will be supported indefinitely. It seems to be a much simpler version of Kubernetes. It has both composition in YAML files (i.e. all your containers together) and the distribution over nodes. What else do you need before you hit corporation-scale requirements?

Yup, even monoliths can benefit from certain k8s tooling (HPAs, batch jobs, etc).

Do you have a recommended tutorial for engineer with backend background to setup a simple k8 infra in ec2?

I've just started to look into it, but it seems like the project has been focusing on improving the onboarding experience since it has a reputation for being a huge pain to set up. Do you think it has gotten easier lately?

Out of curiosity why do you feel swarm fizzled out?

I’ve deployed swarm in a home lab and found it really simple to work with, and enjoyable to use. I haven’t tried k8, but I often see view points like yours stating that k8 is vastly superior.

Of course it doesn't have the advantage of #2, but I've found ECS to be far easier to grok and implement.

According to the article you are wrong about "infrastructure as code". Kubernetes is infrastructure as data, specifically YAML files. Puppet and Chef are infrastructure as code.

Edit: not sure why the down votes, I was just trying to point out what seems like a big distinction that the article is trying to make.

Do you have a good tutorial for doing Django or a standard 3 tier web app on Kubernetes? We are using kubernetes at my workspace, but it seems way too complicated to consider for something like that. Maybe if I can bridge the gap between architectures it will help.

Out of curiosity, are you using terraform to deploy k8s, your app stack on k8s, or both?

imo, all swarm needed was a decent way to handle secrets and it would have been the k8s of its day

The simple answer is that Kubernetes isn't really any of the things it's been described as. What it /is/, though, is an operating system for the Cloud. It's a set of universal abstraction layers that can sit on top of and work with any IaaS provider and allows you to build and deploy applications using infrastructure-as-code concepts through a standardized and approachable API.

Most companies who were late on the Cloud hype cycle (which is quite a lot of F100s) got to see second-hand how using all the nice SaaS/PaaS offerings from major cloud providers puts you over a barrel and don't have any interest in being the next victim, and it's coming at the same time that these very same companies are looking to eliminate expensive commercially licensed proprietary software and revamp their ancient monolithic applications into modern microservices. The culimination of these factors is a major facet of the growth of Kubernetes in the Enterprise.

It's not just hype, it has a very specific purpose which it serves in these organizations with easily demonstrated ROI, and it works. There /are/ a lot of organizations jumping on the bandwagon and cargo-culting because they don't know any better, but there are definitely use cases where Kubernetes shines.

I think this is a good answer. I'll add that as soon as you need to do something slightly more complex, without something like k8s you aren't going to be happy with your life. With k8s, it's almost a 1 liner. For example, adding a load balancer or a network volume or nginx or an SSL cert or auto scaling or...or...or...

Come on. What? Setting up a load balancer or nginx is considered complex now?

You can use something like dokku for most of what you cited for much less overhead, if you are not planning to use the "highly available" feature for sure

Any competent engineer without experience is more likely to figure out how setup and/or troubleshoot nginx than kubernetes.

Just running docker-compose on load balanced machines is pretty close to having all k8s features (that would give you an endpoint, scaling, running pods[containers],heartbeats and nodes[vms]). If you run Kubernetes on GCP you will see it's just a wrapper of GCP vms, load balancers, instance groups and disks. EG: GCP k8's autoscaling for the nodes isn't any better than just simple GCP load balancers and instance groups (it literally is the same thing). k8's best feature (only?): specify yaml files to declare the setup. That is great! But, you make edits to this 4 times a year - that is a ton of complexity for those 4 git commits.

It’s pretty close to get it up and running. It’s not close to operating. You have to roll your own load balancer, health checks, method of updating and managing the underlying nodes, you don’t have operators or guarantees about the control plane, etc...

Spin up a K8S in any major cloud provider and you get all this with a consistent API, which is where the value lies.

With Kubernetes, you can run multiple apps in the same cluster and let Kubernetes manage the capacity on GCP for you. Nice this you have shared headroom for all your apps versus an app per VM in your setup (I think?).

What is wrong with actually using Google’s hosted Kubernetes that would make you want to run compose yourself in their VMs and setup auto scaling, physical machine upgrades, etc.

You can replicate k8s featureset with plenty of other architectures.

But thats not the point.

k8s is the first infrastructure control plane in existence which is widley supported and standardized.

Can you get a managed docker swarm on aws, gcp, azure, do etc.? no.

How many kubernetes offerings do you know? I know at least 6.

Revolution doesn't need to be flashy and noisy.

Off the top of my head, deployments and sidecars are both missing, which are incredibly useful.

We edit yaml files everytime we update a service version, which happens multiple times per week? Is there a better way to deal with this?

GKE uses other GCP products, but ”k8's autoscaling for the nodes isn't any better than just simple GCP load balancers and instance groups (it literally is the same thing)” isn't entirely accurate - GKE and K8S have logic that manages node pools that you won't be able to use with just instance groups.

OS for the cloud is exactly what it is. I see AWS, Azure and GCP as OEMs for cloud, just like Samsung, Oppo, Motorla, etc are OEMs for smartphones. Android was the open source abstraction across these devices. K8s is the open source abstraction across clouds.

The meaning of "app" on top of these two operating system abstractions is entirely different and the comparison probably doesn't extend beyond this. From a computing stack standpoint though, it makes sense.

AWS and other cloud provider provides far more reliable and simpler features/toolkings than k8s. For teams that's serious about building services on the cloud, having k8s to take over certain area of orchestration make sense, but the "operating system" K8s provides is just a tiny peace of the overall infrastructure.

Yes, people ought to do a side by side comparison of a new user learning to K8S v AWS v GCP before claiming Kubernetes adds more complexity than it returns in benefits.

Remember the first time you saw the AWS console? And the last time?

Hmm really? My experience is that, with k8s I end up learning all the complexities of k8s in addition to AWS.

Besides, personally I find AWS console much easier to understand. I don't get why people hate it.

I've spent in total a tenth as much time learning k8s and related systems, as I have spent on AWS.

Most situations I have a direct comparison, k8s takes less ops. Often thanks to helm.

The AWS console is designed for lockin and I could use configuration management for AWS too but the time required to go through their way of doing x is just not worth it. Unless I want to become a AWS solutions architect consultant

> Remember the first time you saw the AWS console? And the last time?

There was a time in between for me - that was Rightscale.

For me, the real thing that k8s bring is not hardware-infra - but reliable ops automation.

Rightscale was the first place where I encountered scripted ops steps and my current view on k8s is that it is a massively superior operational automation framework.

The SRE teams which used Rightscale at my last job used to have "buttons to press for things", which roughly translated to "If the primary node fails, first promote the secondary, then get a new EC2 box, format it, install software, setup certificates, assign an elastic IP, configure it to be exactly like the previous secondary, then tie together replication and notify the consistent hashing."

The value was in the automation of the steps in about 4 domains - monitoring, node allocation, package installation and configuration realignment.

The Nagios, Puppet and Zookeeper combos for this was a complete pain & the complexity of k8s is that it is a "second system" from that problem space. The complexity was always there, but now the complexity is in the reactive ops code, which is the final resting place for it (unless you make your arch simpler).

Ansible. You can keep your YAML and deploy actual virtual servers on your cloud provider. Kubernetes is an introvert and this doesn't correspond to anything but it's padded cell walls. In Ansible it's an extrovert, an exoskeleton. Kubernetes insides out makes it right again. Make sense?

Why do a comparison? K8S runs on AWS and GCP. They have managed services for setting up one. If you know K8S as a developer, then you simply consume the cloud K8S cluster.

What if instead they revamped their ancient microservices into modern monolithic applications?

I'm sorry, but I can't stand this kind of bullshit. You cannot possibly take two random things, put 'modern' in front of one word and 'ancient' in front of another, to justify changing things.

The problem of Kubernetes is probably that people started drinking the microservices koolaid and now need complex solution to deploy their software that became more complex when they adopted a microservices architecture.

IaaS is not "the cloud". it was in 2008 when all we had was EC2 and RDS.

Today Kubernetes is the antithesis of the cloud - Instead of consuming resources on demand you're launching VMs that need to run 24/7 and have specific roles and names like "master-1". Might as well rent bare-metal servers. It will cost you less.

You are completely wrong. It is trivial to have your k8s control plane and your workload cluster in something like an ASG, and basically know nothing about the nodes in either group. I'm not even using GKS or EKS, just ASGs on AWS. My servers and applications are cattle, not pets.

I knew literally nothing about k8s in September and now I have multiple clusters humming along, treating the worker cluster nodes as a generic pool of compute, autoscaling the cluster as well as the pods inside it. Upgrading is a breeze, I have great observability, I can deploy experiments and new applications with a single CI step or click, in fact I have nodes that are killed and get replaced for cost savings by SpotInst in the middle of the business day and I don't even need to know about it. My load balancers and even DNS are all provisioned for me and I can use the same Helm charts to create an identical staging and production environment.

Kubernetes IS the spirit of the Cloud and 12 factor apps. It's not that scary, and with tools like Rancher and k3s you can make it even simpler.

Doesn't kubernetes also have autoscaling capabilities?

https://kubernetes.io/blog/2016/07/autoscaling-in-kubernetes...

> Might as well rent bare-metal servers. It will cost you less.

Long term, but up front costs are what make cloud services appealing.

FWIW, it's possible to minimize your idle VM costs to an extent. For example, you could use one or more autoscale groups for your cluster and keep them scaled to one vm each. Then use tools like cluster auto scaler to resize on demand as your workload grows. You are correct that idle vm costs can't be completely avoided. At least not as far as I am aware.

Does cloud really mean "resources on demand"?

If that is your definition of "cloud" then most stuff running on AWS and other "cloud" providers isn't. I agree that Kubernetes and even containers aren't the end all. I think they are a stepping stone to true on demand where you have the abstraction of just sandboxed processes compiled to WASM or something run wherever.

But as of where we are now, it is a good abstraction to get there. It provides a lot of stuff like service discovery, auto-scaling and redundancy. Yes you do need to have instances to run K8s, but that is as of date the only abstraction that we have on all cloud providers, local virtualization, and bare metal. So yes it isn't true on demand "cloud" but in order to work like that you need to fit into your service provider's framework and accept limitations on container size, runtime, deal with warm up times occasionally.

> Might as well rent bare-metal servers

In light of this statement, what do you make of the fact that billions of dollars are spent on EC2? And of the people who spend that money?

I read the entire article and couldn’t figure out what Kubernetes is. Your description helped a little.

Oh darn, I still don’t understand. Maybe I should learn what Docker is first?

"Approachable"

The buzzword mumbo-jumbo on the first paragraph alone (which isn't really even your fault or anything, just the bogus pomp inherent to k8s as a whole) is already a scarecrow to anyone that "wasn't born with the knowledge", really.

It is pretty hard to get used to it. Brushing it away won't make it approachable.

It's not because of the networking stack.

I've yet to meet anyone who can easily explain how the CNI, services, ingresses and pod network spaces all work together.

Everything is so interlinked and complicated that you need to understand vast swathes of kubernetes before you can attach any sort of complexity to the networking side.

I contrast that to it's scheduling and resourcing components which are relatively easy to explain and obvious.

Even storage is starting to move to overcomplication with CSI.

I half jokingly think K8s adoption is driven by consultants and cloud providers hoping to ensure a lock-in with the mechanics of actually deploying workloads on K8s.

Services create a private internal DNS name that points to one or more pods (which are generally managed by a Deployment unless you're doing something advanced) and may be accessed from within your cluster. Services with Type=NodePort do the same and also allocate one or more ports on each of the hosts which proxies connections to the service inside the cluster. Services with Type=LoadBalancer do the same as Type=NodePort services and also configure a cloud load balancer with a fixed IP address to point to the exposed ports on the hosts.

A single Service with Type=LoadBalancer and one Deployment may be all you need on Kubernetes if you just want all connections from the load balancer immediately forwarded directly to the service.

But if you have multiple different services/deployments that you want as accessible under different URLs on a single IP/domain, then you'll want to use Ingresses. Ingresses let you do things like map specific URL paths to different services. Then you have an IngressController which runs a webserver in your cluster and it automatically uses your Ingresses to figure out where connections for different paths should be forwarded to. An IngressController also lets you configure the webserver to do certain pre-processing on incoming connections, like applying HTTPS, before proxying to your service. (The IngressController itself will usually use a Type=LoadBalancer service so that a load balancer connects to it, and then all of the Ingresses will point to regular Services.)

Assuming that like us, you spend the last 10 - 12 years deploying IPv6 and currently running servers on IPv6 only networks, the Kubernetes/Docker network stack is just plain broken. It can be done, but you need to start thinking about stuff like BGP.

Kubernetes should have been IPv6 only, with optional IPv4 ingress controllers.

It really feels like Kubernetes was developed by some enterprise Java developers. Nothing seems well defined, everything is done in the name of abstraction, but the rules of the abstraction are never clearly stated, only the purpose is.

I really hope someone takes the mantle of Leslie Lamport (creator of the language TLA - "the quixotic attempt to overcome engineers' antipathy towards mathematics") and replaces Kubernetes with some software with a first principles approach.

You mean you dont like 3+ layers of Nat VIA iptables ?

+1000. Came here to rant, I'll just say "this"

For the nginx ingress case:

An ingress object creates an nginx/nginx.conf. That nginx server has an IP address which has a round robin IPVS rule. When it gets the request it proxy's to a service ip which then round robins to the 10.0.0.0/8 container IP.

Ingress -> service -> pod

It is all very confusing but once you look behind the curtain it's straight forward if you know Linux networking and web servers. The cloud providers remove the requirement of needing Linux knowledge.

I don't think this is accurate which plays into the parents point, I guess.

Looking at the docs, ingress-nginx configures an upstream using endpoints, which are essentially Pod IPs, with skips kubernetes service based round-robin networking altogether.

Assuming you use an ingress that does configure services instead, and assuming you're using a service proxy that uses ipvs (i.e. kube-proxy in default settings) then your explanation would have been correct.

For the most part, kubernetes networking is as hard as networking with loads of automation. Often, depth in both those skills are pretty exclusive, but if you're using the popular and/or supported CNI not doing things like changing in-flight, your average dev just needs to learn basic k8s debugging such as kubectl get endpoints to check whether his service selectors are setup correctly, and curl them to check whether the pods are actually listening on those ports.

> It is all very confusing

Is there an easier + simpler alternative?

When you are coming from old sysadmin world and you mastered unix systems architecture and software - what k8s does is very straightforward because its the same you already know.

K8S is extremely complicated for huge swarm of webdevs and java developers that really reqlly dont understand how the stuff they use/code really works.

K8S was supposed to decrease the need for real sysadmins but in my view it actually increased the demand because of all the obscure issues one can face in production if they dont really understand what they are doing with K8S and how it works under the hoods.

Which I find hilarious.

I think you're right for small clusters, you end up needing more sysadmins. But to manage 1000 node Kubernetes cluster, I suspect it can be done with less administration

"I've yet to meet anyone who can easily explain how the CNI, services, ingresses and pod network spaces all work together."

Badly! That'll be $500, thanks for your business.

On a serious note, the whole stack is keeping ok-ish coherence considering the number of very different parties putting a ton of work into it.

In a few years' time it'll be the source of many war stories nobody cares about.

Answer has to include implementation details. No credit if your answer does not reference iptables.

It helps going from the bottom up, IMO. It's a multi-agent blackboard system with elements of control theory, which is a mouthful, but it essentially builds from smaller blocks up.

Also, after OpenStack, the bar for "consulting-driven software" is far from reached :)

Devops/arch here, I think Kubernetes solves deployment in a standardized way and we get fresh clean state with every app deploy. Plus it restarts applications/pods that crashes.

That said I think Kubernetes may be at its Productivity journey on the tech Hype cycle. Networking in Kubernetes is complicated. This complication and abstraction has a point if you are a company at Google scale. Most shops are not Google scale and do not need that level of scalability. The network abstraction has its price in complexity when doing diagnostics.

You could solve networking differently than in Kubernetes with IPv6. There is not a need for complicated IPv4 nat schemes. You could use native ipv6 addresses that are reachable directly from the internet. Since you have so many ipv6 addresses you do not need Routers/Nats.

Anyhow in a few years time some might be using something simpler like an open source like Heroku. If you could bin pack the services / intercommunication on the same nodes there would be speed gains from not having todo network hops going straight to local memory. Or something like a standardized server less open source function runner.

https://en.wikipedia.org/wiki/KISS_principle https://en.wikipedia.org/wiki/Hype_cycle

This is a good point, I was wondering why IPv6 is being avoided so hard.

There are many arguments that IPv6 didn't solve too many IPv4 pain points, but if it solved something is definitively this.

Good point on the app restart. I think K8S is in some ways the equivalent of Erlang BEAM for the masses for the cloud.

Kubernetes is getting more popular because:

1) It solves many different universal, infrastructure-level problems. 2) More people are using containers. K8s helps you to manage containers. 3) It's vendor agnostic. It's easy to relocate a k8s application to a different cluster 5) People see that it's growing in popularity. 6) It's Open source. 7) It helps famous companies run large-scale systems. 8) People think that it looks good on a resume and they want to work at a well known company. 9) Once you've mastered K8s, it's easy to use on problems big and small. (Note, I'm not talking about installing and administrating the cluster. I'm talking about being a cluster user.) 10) It's controversial which means that people keep talking about it. This gives K8s mind share.

I'm not saying K8s doesn't have issues or downsides.

1) It's a pain to install and manage on your own. 2) It's a lot to learn--especially if you don't think you're gonna use most of it's features. 3) While the documentation has improved a lot, it's still weak and directionless in places.

I think K8s is growing more popular because it's pros strongly outweigh it's cons.

(Note I tried to be unbiased on the subject, but I am a K8s fan--so much so that I wrote a video course on the subject: https://www.true-kubernetes.com/. So, take my opinions with a grain of salt.)

My question is: Why is only k8s so popular when there are better alternatives for a large swath of users? I believe the answer is "Manufactured Hype". k8s is from a purely architectural standpoint the way to go, even for smaller setups, but the concrete project is still complex enough that it requires dozens of different setup tools and will keep hordes of consultants as well as many hosted solutions from Google/AWS/etc in business for some time to come, so there's a vested interest in continuing to push it. Everyone wins, users get a solid tool (even if it's not the best for the job) and cloud providers retain their unique selling point over people setting up their own servers.

I still believe 90% of users would be better served by Nomad. And if someone says "developers want to use the most widely used tech", then I'm here to call bullshit, because the concepts between workload schedulers and orchestrators like k8s and nomad are easy enough to carry over from one side to the other. Learning either even if you end up using the other one is not a waste of time. Heck, I started out using CoreOS with fleetctl and even that taught me many valuable lessons.

What are these alternatives with more users?

Where is the momentum?

Hosted GKE costs the same per month as an hour of DevOps time, what's wrong with paid management for k8s?

I didn't say more users, I said appropriate for more users. The alternative I mentioned is Nomad and I wish more people would give it a try and decide for themselves. The momentum behind it is Hashicorp, makers of Vault, Consul, Terraform, Vagrant, all battle-proven tools. The fact that there's one big player behind it really shows in how polished the tool, UI and documentation is.

The issue that I have with managed k8s is that these products will decrease the pressure to improve k8s documentation, tooling and setup itself. And then there's folks (like me) who want or need to run something like k8s on bare metal hardware outside of a cloud where the cloud-managed solution isn't available.

I got a bit disillusioned with k8s and looked at Nomad as an alternative.

As a relatively noob sysadmin, I liked it a lot. Easy to deploy and easy to maintain. We've got a lot of mixed rented hardware + cloud VPS, and having one layer to unify them all seemed great.

Unfortunately I had a hard convincing the org to give it a serious shot. At the crux of it, it wasn't clear what 'production ready' Nomad should look like. It seemed like Nomad is useless without Consul, and you really should use Vault to do the PKI for all of it.

It's a bit frustrating how so many of the HashiCorp products are 'in for penny, in for a pound' type deals. I know there's _technically_ ways for you use Nomad without Consul, but it didn't seem like the happy path, and the community support was non-existent.

Please tell me why I'm wrong lol, I really wanted to love Nomad. We are running a mix of everything and its a nightmare

Nomad + Consul is the happy path. Adding Vault into the mix is nice, but not required.

Consul by itself is the game-changer. Even in k8s it's a game-changer. It solves so many questions in an elegant way.

"How do I find and reach the things running in (orchestrator) with (unknown ip/random port) from (legacy)?" being the most important. You run 5 servers, and a relatively lightweight client on everything (which isn't even outright required, but it sure is useful!), and you get a _lot_ with that.

Consul provides multiple interfaces and ingress points to find everything. It also is super easy to operate, and has a pretty big community.

If you absolutely cannot have Consul, Nomad is still a really good batch job engine, and makes a very great "distributed cron," which is more extensible, scalable, and easy to use than something like Jenkins for the same task.

My team is pretty small (was 4 people, now 6) and we manage one of the worlds largest nomad and consul clusters (there are some truly staggeringly large users of Vault so I won't make that claim). Even when shit really hits the fan, everything is designed in a way that stuff mostly works; and there's enough operator friendly entry points that we can always figure out the problem.

Nomad Team Lead here.

Edit: just noticed an actual Nomad user replied as well, and I like their answer better. Consider mine an addendum. :)

Batch workloads rarely require Consul, but for deploying your standard network services on Nomad: Consul is basically required. You could likely use any number of service mesh systems instead (either as sidecars, Docker network plugins, or soon CNI), but you'll be doing a lot of research and development on your own I'm afraid.

The Nomad team is by no means opposed to becoming more flexible in the future (and indeed better CNI support is landing soon as a first step), but we wanted to focus on getting one platform right and a pleasure to use before trying to genericize and modularize it.

I'm sympathetic toward the idea of a system made of interchangeable parts, but I also kinda feel like it's a bit unrealistic, maybe? Even with well-defined interfaces, there will always be interop problems due to bugs or just people interpreting the interface specs differently. Every new piece to the puzzle adds another line (or several) to a testing matrix, and most projects just don't have the time and resources to do that kind of testing. It's unfortunate, but IMO understandable that there's often a well-tested happy path that everyone should use, even when theoretically things are modular and replaceable.

Nomad isn't really feature mature or user friendly enough, you still eventually need 100 bolt-ons.

I think a Distributed OS is the only sane solution. Build the features we need into the kernel and stop futzing around with 15 abstractions to just run an isolated process on multiple hosts.

As the Nomad Team Lead I sympathize with your first statement, but I hope our continued efforts will dissuade you from the second.

Linux (and the BSDs) are remarkably stable, festureful, and resilient operating systems. I would hate to give up such a strong foundation. Nomad can crash without affecting your running services. Nomad can be upgraded or reconfigured without affecting your running services. Nomad can be observed, developed, and debugged as a unit often without having to consider the abstractions that sit above or below it. The right number of abstractions is a beautiful thing. Just no more and no less. :)

I'm resisting kubernetes and might go with nomad (currently I'm "just using systemd" and I get HA from the BEAM VM)... But I do also get the argument that the difference between kubernetes and nomad is that increasingly kubernetes is supported by the cloud vendors, and nomad supports the cloud vendors.

I second this.

> I still believe 90% of users would be better served by Nomad.

Well sure, but if the story just ended with "everyone use the least exciting tool", then there'd be few articles for tech journals to write.

But Kubernetes promises so much, and deep down everyone subtly thinks "what if I have to scale my project?" Why settle for good enough when you could settle for "awesome"? It's just human nature to choose the most exciting thing. And given that I do agree that there's some manufactured hype around Kubernetes, it isn't surprising to me why few are talking about Nomad.

I'd say it's down to two things. First is the sheer amount of work they're putting into standardization. They just ripped out some pretty deep internal dependencies to create a new storage interface. They have an actual standards body overseen by the Linux Foundation. So I agree with the blog post there.

The second reason is also about standards, but using them more assertively. Docker had way more attention and activity until 2016 when Kubernetes published the Container Runtime Interface. By limiting the Docker features they would use, they leveled the playing field between Docker and other runtimes, making Docker much less exciting. Now, new isolation features are implemented down at the runc level and new management features tend to target Kubernetes because it works just as well with any CRI-compliant runtime. Developing for Docker feels like being locked in.

> By limiting the Docker features they would use, they leveled the playing field between Docker and other runtimes, making Docker much less exciting.

Isn't the most popular k8s case to deploy Docker images still though?

It's confusing, but Docker images (and image registries) are also an open standard that Docker implements [1].

A lot of the Kubernetes "cool kids" just run containerd instead of Docker. Docker itself also runs containerd, so when you're using Kubernetes with Docker, Kubernetes has to basically instruct Docker to set up the containers the same way it would if it were just talking to containerd directly. From a technical perspective, you're adding moving parts for no benefit.

If you use containerd in your cluster, you can then use Docker to build and push your images (from your own or a build machine), but pull and run them on your Kubernetes clusters without Docker.

[1] https://en.wikipedia.org/wiki/Open_Container_Initiative

Yes. The big difference, however, is that k8s removed docker from consideration when actually running the system. Yes, you have docker underneath, and are probably going to use docker to build the containers.

But deploy to k8s? There's no docker outside of few bits involving "how to get to the image", and the actual docker features that are used are also minimized. The result is that many warts of docker are completely bypassed and you don't have to deal with impact of legacy decisions, or try to wrangle system designed for easy use by developer at local machine into complex server deployment. And, IMHO, interfaces used by k8s for the advanced features are much, much better than interfaces used or exported by docker.

Yes. But I think k8s took a lot of attention away from Docker in terms of headspace and developer interest. RedHat for example is pushing CRI-O, which is a minimalist CRI-compliant runtime which lets admins focus even more on k8s and less on the whole runtime level.

It makes a bit more sense if you see Kubernetes as the new Linux: a common foundation that the industry agrees on, and that you can build other abstractions on top of. In particular Kubernetes is the Linux Kernel, while we are in the early days of discovering what the "Linux distro" equivalent is, which will make it much more friendly / usable to a wider audience

This is exactly how we see it at my company.

Likewise, Linux is also a confusing mess of different parts and nonsensical abstractions when you first approach it. It does take some time to understand how to use it, and in particular how to do effective troubleshooting when things aren't working the way you expect.

But I 100% agree--I think it's the new Linux. In 5-10 years, it'll be the "go to", if not sooner.

Second this!

In my humble opinion because there is so much money and marketing behind it. If you go attend the OSS summit all the cloud players are sending evangelizers and having the whole conference to be about Kbuernetes.

Then a lot of people drink the koolaid and apply it everywhere / feel they're behind if they aren't in Kubernetes.

We are not in Kubernetes and have multiple datacenters with thousands of VMs/containers. We are doing just fine with the boring consul/systemd/ansible set up we have. We also have somethings running in Containers but not much.

Funnily enough at the OSS summit I had a couple of chats with people in the big companies (AWS, Netflix, etc.) and they themselves have the majority of their workflows in boring VMs. Just like us.

There is quite a bit of latency added whenever you use a containers.

IMO containers are greatest for stateless apps that don't require much resources, but having a dedicated machine for them is a waste.

Kubernetes is an almost necessary tech when you operate your own cloud and that’s where it came from: Google.

The smart people at Google knew that by quickly packaging their own internal tech and releasing it on open source they’d help people move from the incumbent AWS.

Helping customers switch IaaS hurts the both, lock in is better, but it hurts AWS way more. Proof? They made it free to run the necessary compute behind K8s control plane, until recently that was.

Are there benefits on running your biz’ web app using constructs made for a “cloud”? Sure there is, that’s why people are moving to K8s. There is real business benefits, given a certain amount of necessary moving parts. LinkedIn had such a headache with this they created Kafka.

I suspect most organisations’ Architects and IT peeps push for K8s as a moat for their skills and to beef up their resumé. They know full well that the value is not there for the biz’ but there’s something in it for them.

I remember when Docker and K8 emerged and YAGNI kept everything in perspective. Unless you had a fleet of hundreds of servers to manage and spin-up at a moment's notice you just used Chef, Puppet or Ansible. Now nothing's too small for this ridiculously over-engineered technology. Got a WordPress blog? You're doing it wrong if you don't put it in a Docker container and launch it with K8. Same with a lot of Rails projects for which Capistrano was more than aadequate. Just gotta scratch that itch until you've no more skin left.

To draw anecdotally from my own experiences, its for two reasons:

1. It's simple to get started with, but complex enough to tweak to your needs in respect to simplicity of deployment, scaling and resource definition.

2. It's appealingly cloud-agnostic just at the time where multiple cloud providers are all becoming viable and competitive.

I think it's more #2 and #1; as always, timing is everything.

Yeah, I think people are overthinking it. The real reason is that if you do a superficial investigation you will quickly come back with the impression that k8s is near universally supported across cloud vendors and gives an appearance of providing a portable solution where otherwise the only alternative would be vendor lock-in. It makes it a no-brainer for anybody starting out with a new cloud deployment.

I host about a dozen rails apps of different vintage and started switching from Dokku to Digital Ocean Kubernetes. I had a basic app deployed with load balancer and hosted DB in about 6 hours. Services like the nginx ingress are very powerful and it all feels really solid. I never understood Dokku internals either so them being vastly simpler is no help for me. I figured for better or worse kubernetes is here to stay and on DO it is easier than doing anything on AWS really. I have used AWS for about 5 years and have inherited things like terraformed ECS clusters and Beanstalk apps. I know way more about AWS but I feel you need to know so much that unless you only do ops you cannot really keep up.

I found deploying databases with Dokku to be really intuitive. CockroachDB is great, but still a lot more steps than dokku postgres:create <db>. The whole certificates thing is quite confusing. Otherwise, k3s on-prem is great

I like to say (lovingly) that Kubernetes takes complex things and simplifies them in complex ways.

Kubernetes makes impossible things merely hard, but at the expense of also making normal and easy things hard.

The system becomes so complex that most people screw up simple things like redundancy, perimeter security and zero downtime updates.

I've seen all of the above from very bright and capable people.

It just hides the complexity in some yml files instead of in a deploy script or a sysadmin's head.

You say that like it's a bad thing. A declarative model is infinitely better for representing complex systems than scripts and mind space. The challenge is actually being able to get to that point.

What does the Kubernetes configuration format offer over configuration management systems like Ansible, Salt, Puppet, Chef, etc?

Having extensively used Chef and K8s, the difference is that they try to deal with chaos in unmanaged way (Puppet is the closest to "managed"), but when dealing with wild chaos you lack many ways of enforcing the order. Plus they don't really do multi-server computation of resources.

What k8s brings to the table is a level of standardization. It's the difference between bringing some level of robotics to manual loading and unloading of classic cargo ships, vs. the fully automated containerized ports.

With k8s, you get structure where you can wrap individual program's idiosyncracies into a container that exposes standard interface. This standard interface allows you to then easily drop it into server, with various topologies, resources, networking etc. handled through common interfaces.

I said that for a long time before, but recently I got to understand just how much work k8s can "take away" when I foolishly said "eh, it's only one server, I will run this the classic way. Then I spent 5 days on something that could be handled within an hour on k8s, because k8s virtualized away HTTP reverse proxies, persistent storage, and load balancing in general.

Now I'm thinking of deploying k8s at home, not to learn, but because I know it's easier for me to deploy nextcloud, or an ebook catalog, or whatever, using k8s than by setting up more classical configuration management system and deal with inevitable drift over time.

What a container lets you do is move a bunch of imperative logic and decisions to build time, so that there are very few decisions made at deploy time. I'm not trying to have a bunch of decisions made that are worded as statements. I've watched a long succession of 'declarative' tools that make a bunch of decisions under the hood alienate a lot of people who can't or won't think that way, and nobody really should have to, even if they can. There are so many things I'd rather being doing with my day than dealing with these sorts of systems because otherwise it won't get done, and I'm heavily invested in the outcome.

I think the build, deploy, start and run-time split is an important aspect that gets overlooked quite a bit, and is critical to evaluating tools at this point. That is why we aren't still doing everything with Chef or Puppet. Whether we continue doing it with Kubernetes or Pulumi or something else matters a bit less.

Repeatability is not the goal, as others in this thread have implied. The goal is trusting that the button will work when you push it. That if it doesn't work, you can fix it, or find someone who can. Doing that without repeatability is pretty damned hard, certainly, but there are ways to chase repeatability without ever arriving at the actual goal.

> Now I'm thinking of deploying k8s at home, not to learn, but because I know it's easier for me to deploy nextcloud, or an ebook catalog

can't you do that just with containers?

>Now I'm thinking of deploying k8s at home

Are we talking about k8 base on your own server rack at your house?

Containers are the big difference.

Kubernetes is one way to deploy containers. Configuration systems like Ansible/Salt/Puppet/Chef/etc are another way to deploy containers.

Kubernetes also makes it possible to dynamically scale your workload. But so does Auto Scaling Groups (AWS terminology) and GCP/Azure equivalents.

The reality is that 99% of users don't actually need Kubernetes. It introduces a huge amount of complexity, overhead, and instability for no benefit in most cases. The tech industry is highly trend driven. There is a lot of cargo culting. People want to build their resumes. They like novelty. Many people incorrectly believe that Kubernetes is the way to deploy containers.

And they (and their employers) suffer for it. Most users would be far better off using boring statically deployed containers from a configuration management system. Auto-scaled when required. This can also be entirely infrastructure-as-code compliant.

Containers are the real magic. But somehow people confused Kubernetes as a replacement for Docker containers, when it was actually a replacement for Docker's orchestration framework: Docker Swarm.

In fact, Kubernetes is a very dangerous chainsaw that most people are using to whittle in their laps.

I'm not intimately familiar with those, but I did a lot of similar things with scripts.

As far as I can tell: those are imperative. At least in some areas.

Kubernetes is declarative. You mention the end state and it just "figures it out". Mind you, with issues sometimes.

All abstractions leak. Note that k8s's adamance about declarative configuration can make you bend over backwards. Example: running a migration script post deploys. Or waiting for other services to start before starting your own. Etc.

I think in many ways, those compete with Terraform which is "declarative"-ish. There's very much a state file.

For certain things like layer 4 and layer 7 routing or firewall policies, health checking and failover, network-attached volumes, etc you have to choose software and configure it on top of getting that configuration in that tooling. So you are doing kernel or iptables or nginx or monit/supervisord configurations and so on.

But basic versions of these things are provided by Kubernetes natively and can be declared in a way that is divorced from configuring the underlying software. So you just learn how to configure these broader concepts as services or ingresses or network policies, etc, and don't worry about the underlying implementations. It's pretty nice actually.

Ansible configuration is imperative (you need to run notebooks in order) but Kubernetes YAML is declarative. That alone is a huge difference!

I've been using Kubernetes exclusively for the past two years after coming from a fairly large Saltstack shop. I think traditional configuration management is flawed. Configuration drift _will_ happen because something, somewhere, will do something you or the formula/module/playbook didn't account for. A Dockerfile builds the world from (almost) scratch and forces the runtime environment to be stateless. A CM tool constantly tries to shape the world to its image.

Kubernetes isn't a silver bullet of course, there will be applications where running it in containers adds unnecessary complexity, and those are best run in a VM managed by a CM tool. I'd argue using k8s is safe default for deploying new applications going forward.

It's not just the configuration format. There is a whole 'Kubernetes runtime' (what they call the 'control loops' aka 'controllers') that runs 24/7 watching the configuration live and making appropriate changes.

Unlike Ansible (and I suspect the others) where it's really only more of a 'run once' type of thing... And sometimes if you try running it a second time it won't even succeed.

They are not comparable. You might use ansible, salt, puppet or chef to deploy kubelet, apiserver, etc. You could, barring those with self-love, even deploy Ansible tower on Kubernetes to manage your kubernetes infrastructure.

According to the article the advantage of Kubernetes is that you're not writing code like you are with Puppet and Chef. You're writing YAML files.

What about Terraform?

as a sys-admin, I like k8s because it solves sys-admin problems in a standardized way. Things like, safe rolling deploys, consolidated logging, liveness and readiness probes, etc. And yes, also because it's repeatable. It takes all the boring tasks of my job and let's me focus on more meaningful work, like dashboards and monitoring.

Yep, same here. Once you learn it, it is a standardized consistent API and becomes a huge force multiplier

k8s is a lever to scale sysadmins power, not scale services to huge numbers. :)

Lets use Bazel, and Bazel's rules_k8s to build\containerize\test\deploy only the microservices of my monorepo that changed.

Lets use Istio's "istioctl manifest apply" to deploy a service mesh to my cluster that allows me to pull auth logic / service discovery / load balancing / tracing out of my code and let Istio handle this.

Lets configure my app's infrastructure (Kafka (Strimzi), Yugabyte/Cockroach, etc) as yaml files. Being able to describe my kafka config (foo topic has 3 partitions, etc) in yaml is priceless.

Lets move my entire application and its infrastructure to another cloud provider by running a single bazel command.

k8s is the common denominator that makes all this possible.

> k8s is the common denominator that makes all this possible.

can't... terraform make all of that possible?

Terraform explicitly doesn't want to deal with deployment of stuff that is inside VMs etc. and tries to tell you to use managed services or cloud-config yamls as the solution.

You can write your own providers, you can use the provisioned support, but TF doesn't like that and it shows.

K8s is great - if you are solving infrastructure at a certain scale. That scale being a Bank, Insurance Company or mature digital company. If you're not in that class then it's largely overkill/overcomplex IMO when you can simply use Terraform plus managed Docker host like ECS and attach cloud-native managed services.

Again the cross cloud portability is a non starter, unless you're really at scale.

Hard disagree.

What k8s really scales is the developer/operator power. Yes, it is complex, but pretty much all of it is necessary complexity. At small enough scale with enough time, you can dig a hole with your fingers - but a proper tool will do wonders to how much digging you can do. And a lot of that complexity is present even when you do everything the "old" way, it's just invisible toil.

And a lot of the calculus changes when 'managed services' stop being cost effective or aren't an option at all, or you just want to be able to migrate elsewhere (that can be at low scale too, because of being price conscious).

> you can simply use Terraform plus managed Docker host like ECS and attach cloud-native managed services

That's not actually simple at all, and you would need to build a lot of the other stuff that Kubernetes gives you for free.

Kubernetes gives you an industry standard platform with first-class cloud vendor support. If you roll your own solution with ECS, what you are really doing is making a crappy in-house Kubernetes.

k8s as a bunch of other benefits beside just scaling and you can run a single node cluster with the same uptime characteristics as your proposed setup and get all these benefits.

And, we only have to learn one complex system and avoid learning each cloud, one of which decided product names which have little relation to what they do was a good idear

Because Google made it. Same thing with Tensorflow. And, fun fact, both are massively overhyped and a real PITA to learn and use. But Google uses it, so hey.

This just isn’t true. I’ve never used Tensorflow but Kubernetes is great.

We moved to it from docker swarm because docker swarm still has a lot of glitches with its overlay network. Rolling upgrades would leave stale network entries and its impossible to reproduce. Sometimes it happens sometimes it doesn’t.

With a managed solution, Kubeadm, or RKE it’s not hard to deploy anymore. All our infrastructure is in code, is immutable, and if you’re careful can be deployed into any kubernetes cluster.

Just like Docker has been great for easily deploying open source products, kubernetes is great for doing the same thing when you need to deploy horizontally. It’s easy for OSS to provide a docker image, a docker compose file for single node deploy, and Kubernetes yaml for a horizontal deploy.

I'll add my use case: we use hosted kubernetes to deploy all of our branches of all of our projects as fully functional application _stacks_, extremely similarly to how they will eventually run in production. Want to try something and show it to someone in the product owner level? Ok there will be a kube nginx-ingress backed environment up in build-time + a few minutes.

The environments advertise themselves via that same modified ingress's default backend. We stick a tiny bit of deploy yaml in our projects, the deployments kube tagging gives us all the details we need to provide diffs, last build time, links to git repos, web sites etc for the particular environment. The yaml demonstrates conclusively how an app could or should be run, regardless of os or software choice, so when we hand it to ops folks there is a basis for them to run from.

There's nothing too novel about Kubernetes, similar patterns could be seen in Erlang many years ago, though in different abstraction levels.

However, because enterprise ops prior to Kubernetes are both costly and brittle, Kubernetes just works for enterprises.

We had a huge PowerShell codebase and it was a nightmare to maintain. in the meantime, it's no way as robust as Kubernetes.

It's just as simple as that: sure, Kubernetes seems to be complex, but most enterprise stuff are even worse. At the same time, despite they are costly, the quality is usually pretty crappy because those scripts are written under delivery pressure.

You can tell by the volume of comments how interested in the topic the community is.

I've noticed that there are a lot of replies such as "it is overhyped" and "I can just run a VM".

Kubernetes is not for you as your use case may not match what it does and solves. Kubernetes provides a standard way of running your applications. It is complex but logical. Yaml sucks but it is simple and logical. I prefer to use terraform for kubernetes but it is the same thing, simple and logical. You cannot say the same with puppet, chef, ansible etc. All of those configuration tools are a big mess of different setups and scripts. I can go to any company and understand how their system works quite quickly. It makes searching for answers easy too because it is standard.

When you are running several services and there is an outage, it is a godsend. You can instantly view the status of things, how they are configured and when they changed. That is POWERFUL.

It takes a while to understand how all of the resources fit together but that is the same case with any type of deployment system and/or operating system.

p.s. I am not running that huge of a system, maybe about 5k containers total between dev, staging and prod. Maybe 500k requests a day. Running a couple kubernetes clusters is significantly nicer than running things in ECS.

TIL about kudo, The Kubernetes Universal Declarative Operator. We've been doing the exact same things in a custom go CLI for 2 years.

The kubernetes ecosystem is really amazing and full of invaluable resources. It's vast, complex, but well-thought. Getting to know all ins and outs of the project is time consuming. So much things to learn and so little time to practice...

I work on KUDO team. Would love to hear what you think about it. All devs hang out in #kudo channel on Kubernetes community slack, please don’t hesitate to join and say hi.

Ars longa, vita brevis ...

There's a silent majority of people that don't use k8s (or containers) - hell there is a significant portion of servers that don't even use linux. I find the majority of engineers my age (mid 30s) think it is nothing more than straight marketing - between said marketing fueled vc dollars and "every company is a software company" there's a very good reason why k8s has taken off but I'd ask the following:

Why should it have?

Many people I talk with will complain about security, performance and complexity of k8s (and containers in general). Non-practicing engineers (read: directors/vps-eng) will complain about the associated cost with administering their k8s clusters both in terms of cloud cost and devops personnel cost.

Someone earlier mentioned it was the new wordpress - I don't think that's an unfair comparison, although I would challenge the complexity/cost of it.

You don't necessarily HAVE to use K8s to get advantage of it. Use something like Knative and you're good to go. Google has Cloud run and Azure would soon come up with some similar abstraction on top of kubernetes.

Honestly, at least with GKE, hosting applications on managed k8s is not that complicated, to the point that I don't think it is a poor choice even for small teams who might not need all the bells and whistles of k8s. That is, so long as that small team is already on board with CI and containers.

Kubernetes got popular because it was the first system that came along that provided a CRUD API for resources of all kinds, including custom resources (CRDs), and was immediately compatible with public artifact hubs like DockerHub and Google Container Registry. The second one is the real kicker here, and I think is why Kubernetes "won" and Mesos et al did not. With Mesos et al you had to set up your own artifact storage. As powerful as Mesos was, there was no MesosHub.

Longer term, I think the contribution of Kubernetes will be getting us used to a resource/API-driven approach to infrastructure that abstracts away cloud providers, hardware, etc. But it will probably be superseded in the coming years by something that honors similar API "contracts." Probably written in Rust troll

I'm using Kubernetes extensively in my day to day work and once you get it up and running and learn the different abstraction, it becomes a single API to manage your containers, storage and network ingress needs. Making it easy to take a container and getting it up and running in the cloud with an IP address and a DNS configured in a couple API calls (or defined as YAMLs).

That being said, I will also be the first one to recognize that PLENTY of workloads are not made to run on Kubernetes. Sometimes it is way more efficient to spawn an EC2/GCE instance and run a single docker container on it. It really depends on your use-case.

If I had to run a relatively simple app in prod I would never use Kubernetes to start with. Kubernetes starts to pay itself off once you have a critical mass of services on it.

One could argue if you have a tiny set of services you are better off using a managed offering like AWS Lambda or Cloud Run

Kubernetes, I think, exists in the 'hedgehog' at the middle of the diagram of various drives and fears.

There is some tech so simple that you just learn it and start using it, others that you know you can pick up when the time is right.

And software you would be happy to invest time in... as long as someone is paying you to do it, software you fear might keep you from getting a job if you don't invest in it.

There is software so simple it might be right (it isn't) and software so complicated that it must be important if people are using it/working on it.

So it's not that Kubernetes is good, it's just that it makes people neurotic enough to jump on the bandwagon. Been a few of those in my career. A few have stuck, most have not.

Kubernetes is insurance for companies against getting locked in proprietary technologies.

It also promotes immutable infrastructure and hence increases the portability. While some of the things like load balancers and ingress are controlled by cloud provider almost everything else can be seamlessly migrated to another cloud provider or on prem.

It makes dev, test, staging, prod environments consistent and also solves a lot of pain points of managing infrastructre at scale with autoscaling, auto healing and more. Istio adds a lot more kubernetes and makes the supporting microservices even easier.

Its going to be an important piece in Hybrid world as it brings a lot of standardization and consistency in two disparate environments.

I mean, k8s draws experience from 12+ years of thousands of high caliber engineers. It's like deliver modern cars to Chinese market in 1970s time. Of course it will be popular...

I can only speak for myself as a relatively late adopter, right around early 2020 this year.

I only consider that late because I've been reading the hype around k8s for many years already.

Became a late adopter of containers just before k8s actually. Now I've migrated most of my setups both privately and professionally to containers. And setup my first k8s clusters both at work and in my homelab.

So my perspective is that containers are first and foremost an amazing way of deploying software because all that complexity I did in ansible to deploy the software has been moved to the container image.

The project itself now, be it Mastodon, Jitsi, Synapse to name a few, package most of their product for me in automatic build pipelines. All I need to do is run and configure it.

And therefore, moving on to k8s, it would stand to reason that some of those services are able to be clustered. Where better to do such clustering than k8s?

That's just an ops perspective. We also have devs where I work and with k8s they're able to deploy anything from routes down to their services using manifests in CD pipelines. What's not to like?

Only reason one might get disenchanted with k8s is if you expect it to be a one-stop solution for your aging .net application. Not saying you can't deploy that in k8s, I'm just using it as an example of something that might not be microservice ready.

Kubernetes is getting popular because it is a no-brainer api to existing things like firewall, virtual ip, process placement, etc.

It's basically running a big computer without even trying.

It's a developer tool made originally by google. Of course it's popular. Which isn't to say it's bad, it's just not much of a question as to why it's popular.

-------

Kubernetes - kubernetes.io

Kubernetes is an open-source container-orchestration system for automating application deployment, scaling, and management. It was originally designed by Google, and is now maintained by the Cloud Native Computing Foundation.

Original author(s): Google

If the question was, Why is kube getting so popular with developers, it might get a different response. I wonder how many software developers come to kubernetes through the templated/helm chart/canned approach made by there DevOps team, not that this isn't a fine approach, but I find it a different conversation to say, Serverless, where anyone can just jump in.

After spending 18 months working on bringing kubernetes(EKS) to production, with dozens of services on it, the time was right to hand over migrating old services to the software engineers who maintain them. Due to product demands, but also some lack of advocacy, this didn't happen, with the DevOps folks ultimately doing the migration and retaining all the kubernetes knowledge.

An unpopular opinion might be that Kubernetes is popular because it gives DevOps teams new tech to play with, with long lead times for delivery given its complexity. Kubernetes usually is a gateway to tracing, service meshes and CRDs, which while you don't need at all to run Kubernetes, they will probably end up in your cluster.

Every person I know who wants to use k8s has never had to maintain it.

"Developers love it!" Yeah, I'd love someone to drive my car for me, too. Doesn't mean it's a great idea to use technology so complex you have to hire a driver (really several drivers) to use it.

If you already have 3 people working for you that (for example) understand etcd's protocols or how to troubleshoot ingress issues or how to prevent (and later fix) crash loops, maybe they can volunteer to babysit your cluster for you, do all the custom integration into the custom APIs, keep it secure, etc. But eventually they may get tired of it and you'll have to hire SMEs.

If you're self-hosting a "small" k8s cluster and didn't budget at least $500k for it, you're making a mistake. There are far simpler solutions to just running a microservice that don't require lots of training and constant maintenance.

Complexity isn't always bad, but unnecessary complexity always is.

Before K8S, to run a service you need:

- Setup VM: and their dependencies, tool chain. If you use thing like package that has native component such as image processing you event need to setup some compiler on the VM - Deployment process - Load balancer - Systemd unit to auto restart it. Set memory limit etc.

All of that is done in K8S. As long as you ship a Dockerfile, you're done.

I feel like you're simplifying things unnecessarily, all of the things you mentioned you still configure, except the configuration is now in YAML.

but how do you setup k8s?

How big does your company get before you need to step away from a tiny handful of very large EC2s?

If you have 16CPU EC2 for your business logic, one for your DB, and you're smartly hosting your static content elsewhere or via Cloudflare ... I mean you need to have a 'big company' before going too far beyond that.

What gives? What are all these startups doing?

This is not a story about K8's, this is entirely something else, it's about psychology, complexity, our love of it, or rather our 'belief' that complexity = productivity that solving 'the hard infra problem' must inherently, be somehow be 'good for the company' because it 'feels difficult' and therefore must be doing something powerful or at least gaining some kind of competitive advantage?

(Aside from the 'Docker is Useful and K8's follows' point which actually makes sense a little bit ...)

I've tried to make the argument that Kubernetes introduces a level of complexity that should make everyone think twice before diving into that eco-system. I've tried to make this argument using both detailed, factual arguments, and also by using humor and parody. I am confused why Kubernetes has so much momentum, especially when you consider that most of the things we want (isolation, security, dependency management, flexible network topologies) can be gained much more simply with Terraform and Packer. With a mix of humor and detailed factual analysis, my most recent attempt to make this argument is here:

http://www.smashcompany.com/technology/my-final-post-regardi...

- Its free

- Most code running on k8s hasn't hit full production load yet.

- Where it has worked well, its been managed by devs that know what they are doing.

- It something worth putting on a backed dev resume

- Apparent cost saving ('we just need 1 vm instead of 5', 'we can auto scale to infinity','we don't have yo pay for aws, we get it all on our own vms').

Wait a few months and we will see a slurry of posts that read 'why we moved away from kubernetes', 'top 5 reasons to not use kubernetes', 'How using kubernetes fucked us, in the ass', 'You dont need kubernetes', 'Why I will never work on a project that uses kubernetes', 'Hidden costs of kubernetes' and so on.

C'mmon, you know how this works. Just take the time and read the docs. They are well written (They just don't mention where k8s does not work well)

Exhibit 1 : Why Kubernetes is not part of our stack [1]

[1]: https://news.ycombinator.com/item?id=23460066

Because developers are lazy.

I dont want do memory management-> gc

I dont want to do packaging -> Docker

I dont want to do autoscaling -> Kubernetes

Kubernetes is great, but also very complex and almost an entire new paradigma to learn and understand. I feel like there's a huge void between no Kubernetes and Kubernetes that isn't being filled yet. Dealing with and/or managing Kubernetes is a task on its own, I have the feeling that container orchestration doesn't have to be that complex.

Something like an easy to use (and operate!) multi-tenant docker-compose on steroids with user management/RBAC and a built-in Docker image repository that gets out of your way would be amazing for small teams / startups that don't want to deal with the complexity of Kubernetes.

- There are big names behind it. - It will replace VM orchestration platforms. - Fear of missing out.

Jokes aside, when you've lots of teams, all working on small pieces of a large product and shipping on their own, iterating fast... you need a platform and ecosystem on top to meet their requirements. As you reach planet-scale, you need to NOT let your cost grow exponentially. Hence it is popular.

What if you're not planet-scale? Well, it will still help (attract talent, design for scale, better ecosystem etc.). Hence it is popular.

If you're building a business however, focus on business and time-to-market, definitely not the infra, i.e. kubernetes.

I think kubernetes is to Infra what RoR was to Web. Not necessarily in terms of architectural style of MVC, but more towards standardization of similar enough problems that can be put into a mutually agreed convention.

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

in my opinion it kinda sets a common lingo between development people and operations people.

operations details are hidden from developers and development details (the details of the workload) are hidden from the operations engineers.

I've been completely perplexed by how I might repeatably and reliably setup a single DigitalOcean (or similar) server.

I can't just blow away the instance, make a new one with their API, and run a bash script to set it up because I need to persist some sqlite databases between deploys.

Nix looks promising, but also seems to be a lot to learn. I think I'd rather focus on my app than learn a whole new language and ecosystem and way of thinking about dependencies.

I don't think my needs are insane here, I'm surprised there seems to be no infrastructure as code project for tiny infrastructures.

I’m a huge K8s advocate but if all you’re looking for his a repeatable way to spin up DO droplets then use a user-data script.

User data is a bash script that can be automatically run when the machine first spins up.

You could pass that script via digital oceans cli or even a tool like terraform.

Easy: the perception of infinite overhead. The cloud itself (e.g. EC2) gives you capacity-on-demand, but the glue to make all the nodes work together is missing. And its a really hard problem, in general, because its distributed systems. K8s fills that demand, or seeks to. The alternative is to roll-your-own, which is possible but expensive, error-prone, and difficult to hire for. (My last company discovered this to their detriment after sinking a LOT of time into building out a really complex Salt+Vagrant+AWS solution, and then decided to migrate to k8s).

Beats me. It doesn't correspond to either virtual server nor hypervisors. It certainly doesn't correspond to real hardware. Cloud OS my butt... "Hey, let's take a zillion commodity cloud provider instances running on hypervisors, then install Ubuntu, then run Kubernetes on them, then run docker containers on them and fiddle about all day with yaml trying to make internal networking do insecure things to imitate real world infrastructure"

Just use Ansible if you miss YAML, and you can actually deploy to real hardware.

It has most of the features needed.

Everyone was trying to make a system simple and adopted, but if you want it to be adopted, it's going to need a lot of features. Also Google worked some real magic in getting Kubernetes being supported by all the cloud providers.

It's a framework that will enable you to do what you want, while being the standard.

You could write your script to do that in a simpler way, but most people already know the standard and it's easier for everybody to understand Kubernetes rather than your clever solution.

I've seen people extolling the many benefits of Kubernetes. For those who are all in, how does something like CDK compare?

I served millions of users with single low end server. Kubernetes is just a sign that people can't code anymore.

As a follow up question. I’ve been running on Azure Service Fabric for a little over three years now and been quite happy with it so far.

But it doesn’t seem like it generates quite the same buzz as kunernetes. Not even within the azure/win/.net part of the world.

So have anyone here worked with both and could share some experience?

I learned to like kubes, but... why on earth is it YAML :(

yaml is such a horrible format that I would even prefer JSON...

In a side note if you were to invest your time in writing operators, would you use kubebuilder or operator-sdk?

Both use controller-runtime underneath so there is not much difference between the two. I personally have used both and prefer kubebuilder

Kubebuilder. Operator-sdk is migrating to kubebuilder anyway - https://github.com/kubernetes-sigs/kubebuilder/projects/7

I think kubernetes is great conceptually if you're running on the cloud, but it's a very complicated domain, and has a lot ecosystem churn. Things break a lot if you're not careful. Upgrading dependencies is a constant pain. Certainly a time such

This article adds nothing to common knowledge everyone with a bachelors degree in computer science is completely aware of. Can anyone tell me what I missed? Or where is the reason why this post is trending among people whose background I cannot grasp?

Do you guys think k8s is doing a job which previously the jvm did in enterprise? i.e. if everything is on the jvm, building distributed systems doesn't require a network of containers.

Can k8s success be explained partly due to the need for a more polyglot stack?

How do you roll over a fleet of JVM applications with zero downtime and maintain rollback revision history?

Is it as easy as two simple commands?

I think the JVM is more akin to Docker in that regard. K8s sits above that.

I thought it was pretty insane yesterday when I read a YC-backed recruiting company was using Kubernetes. Absolutely insane. It's become the new, hottest, techiest thing that every company has to have even when they don't need it.

It's perfectly sane if their team already knows how to use K8s, especially if they use a hosted solution like GKE or Digitalocean K8s. (I'll admit that I'd never want to manage my own k8s cluster.)

Once you know K8s, it's not very difficult to use. Plus, it provides solutions to a lot of different infrastructure-level problems.

Why is it insane? Was there something about this company's stack that could have avoided Kubernetes in favor of something else?

the main thing I like about them: configuration. it's trivial to split integration configuration from applicative configuration from deployment configuration, it's trivial to version configurations,

it's not unique in what it does, but even with puppet and the likes you always had this or that exception because networking, provider images varying selinux defaults etc.

kuberent on it's own already covered most ground, but configmap and endpoints really tie it together in a super convenient package

it's not without pitfalls, like ms aks steal 2gb from each node so you have to be aware of that and plan accordingly, but still.

> it's not without pitfalls, like ms aks steal 2gb from each node so you have to be aware of that and plan accordingly, but still.

This is what I hate alot about things like k8, docker, etc is the memory profile… pretty much makes it a non starter if you want to run it on anything low cost.

As a manager i've heard in all my meetings about 'kubernetes', had a look at it and have always been questioning the cost to manage this.

What is the cheapest way to setup a production kubernetes on a cloud provider?

Digital ocean has a managed kubernetes service that does not cost anything except the resources you use. The master node and management is free, you only pay the node pools and stuff like block storages (their version of EBS) or load balancers.

At this point, most big cloud providers cost almost the same but in terms of maturity, google’s offering is still ahead. I have not tried out digital ocean’s hosted solution, but the might be the cheapest.

One thing I've discovered when hiring people is if I'm not using things like kubernetes, I don't get (as many) candidates apply. I also don't get as good quality candidates, either.

My opinion is that Kubernetes is the common integration point. Tons of stuff works with Kubernetes without having to know about each other, making deployments much much easier.

Because Google is an advertising company, their search engine controls what people believe in and they also have some good engineers but they are probably not well known. There is very little they couldn't advertise into popularity. Whenever you see overcomplicated software or infrastructure its always a way to waste executive function, create frustration and create unnecessary mental overhead. If the technology you're using isn't making it easier for you to run your infrastructure from memory, reduce the use of executive function and decrease frustration then you should ignore it. Don't fall for the fashion trends.

Please don't criticize, condemn, or complain if you don't have anything constructive to add.

This is the wrong question. The question should be why are containers so popular? If you're going to use containers, kubernetes makes it easier to do so.

Not a microservices guru, but why are big companies (most famously Uber, who was sort of spearheading it famously) starting to abandon this architecture?

Somehow k8s capabilities look like a description of WebSphere feature list, just done with cooler technology for younger generations.

Some developers just refuse to admit they're are trends in development.

Kubernetes is popular because it's the new 'cool'.

I love to read when some tech we are using @ Nursoft.co about 1+ year is "getting" popular, it's feels good.

Kubernetes is popular because developers want names on their CVS. A couple of shell scripts will get you anywhere.

Am I the only one who noticed that 'Innovation' was by far the shortest section of that article?

Call me biased [1] but K8s will take over the world! Yes you get containers and micro-services and all that good stuff, but now with Anthos [2] its also the best way to achieve multi-cloud and hybrid architectures. What's not to like!

1. I work for GCP 2. https://cloud.google.com/anthos/gke

Is there any benefit of Anthos over deploying straight to GKE if you're already bought into GCP? We've had this debate several times recently and can't come up with a good answer.

Google created it but did they get any benefit from it? Did it help in getting any business for GCP?

Two different questions.

To the first- yes, enormously so. If you know your history, it is the Linux to the Microsoft that is AWS- except backed by a business. (Google is maybe RedHat in that story, but the analogy is more inaccurate than accurate).

To the second, not really. GCP is mostly turning into an ML play.

Because the demos are awesome and there is a lot of money to be made in getting it beyond demos

I get the feeling K8 is the modern PHP. Software that's easy to pick up and use without complete understanding and get something usable. Even if its not efficient and results in lots of technical debt.

And like PHP, it will be criticised with the power of hind sight but will continue to be used and power vast swaths of the internet.

But languages are easy, there is the whole field of PL theory to draw from. If you're randomly throwing things together like Lerdorf was, there's a missed opportunity.

But what is the universally regarded theory that k8s contradicts? I don't think there is one.

I don't think this is right. The reason I say that is because for the most part, teams new to k8s aren't building and managing their own clusters, they are using a managed solution. In that case, an application deployment only need be a few dozen lines of yaml. Most teams aren't really going to be building deep into k8s, and it shouldn't be hard to deploy your containers to some other managed solution.

I completely understand the use case for Kubernetes when you're dealing with languages that require a lot of environment config, like Python.

I've never really thought it was that useful for (for example) nodejs, where you can just npm install your whole environment and deps, and off you go.

I have mostly used Kubernetes for Node.js apps and find it very useful for the following reasons:

- Automatic scaling of pods and cluster VMs to meet demand.

- Flexible automated process monitoring via liveness/readiness probes.

- Simple log streaming across horizontally scaled pods running the same app/serving the same function using stern.

- Easy and low cost metrics aggregation with Prometheus and Grafana.

- Injecting secrets into services.

I'd imagine there are other things can offer the same, but I find it convenient to have them all in the same place.

Because it’s basically turning things off and on. At scale.

So anybody doing k8s onprem? How is it going/working?

if you're on microservices, it's no brainer. You'll need an army of DevOps with semi-custom scripts to maintain the same. It's really automating a lot of stuff. Helm + Kubernetes let our company's ability to launch microservices with no DevOps involved. You just provide the name of the project, push to git and GitLab CI will pick it up and do the stuff by the template. Even junior developers in our team are doing that from day one. Isn't that a future we dream about? If you have too much load it will autoscale pod, if node is overloaded it will autoscale node pool, if you have a memory leak it will restart the app so you can sleep at night. I can provide a million examples that make our 100+ microservices management so much simpler. No Linux kungfu, 0 bash scrips, no SSH, and interaction with OS, not a single devops role for 15+ developers team.

Our management of cluster is just a simple "add more CPU or memory to this nodepool", sometimes change a nodepool name for deployment for certain service. All done simple cloud management UI. For those who call microservices fancy stuff. No, we are a startup with fast delivery, deploy cycle. We have tons of subproject , integrations, and our main languages are nodejs, golang and python. Some of these are not good at multi-thread so no way to run it as a monolith. The other one is used only when it's needed for high performance. So All together Microservices + Kubernetes + Helm + good CI + proper pubsub gives our backend extremely simple fast cycle of development, delivery, and what's important flexibility in terms of language/framework/version.

What is also good is the installation of services. With helm I can install high availability redis setup for free in 5 minutes. The same level of setup will cost you several thousand dollars for devops work and further maintenance and update. With k8s it's simple helm install stable/redis-ha

So yeah, I can totally understand some simple projects don't need k8s. I can understand you can build something is Scala and Java slowly but with high quality as a monolith. You don't need k8s for 3 services. I can understand some old DevOps don't want to learn new things and they complain about a tool that reduces the need of these guys. Otherwise, you really need k8s.

I will happily use k8s for that big monolith.

Because soon from one program on a dev server, there is a need to run databases, log gathering, multiply the previous to do parallel testing in clean environment, etc. etc.

Just running supporting tools for a small project where there was insistence on self-hosting open source tools instead of throwing money at slack and the like? K3s would have saved me weeks of work :|

It gets more popular mostly because it's popular.

This seems appropriate... https://microservices.io/

Obligatory- the best introduction to Kubernetes, from conceptual perspective, is Google's incredible Borg paper:

https://static.googleusercontent.com/media/research.google.c...

Religion

In this post it might only be an example, but I don't see anything, that necessitates the use of YAML. All of that could be put in a JSON file, which is far less complex.

YAML should not even be needed for Kubernetes. Configuration should be representable in a purely declarative way, instead of making the YAML mess, with all kinds of references and stuff. Perhaps the configuration specification needs to be re-worked. Many projects using YAML feel to me like a configuration trash can, where you just add more and more stuff, which you haven't thought about.

I once tried moving an already containerized system to Kubernetes for testing, how that would work. It was a nightmare. It was a few years ago, maybe 3 years ago. Documentation was plenty but really sucked. I could not find _any_ documentation of what can be put into that YAML configuration file, what the structure really is. I read tens of pages of documentation, none of it helped me to find, what I needed. Then even to set everything up, to get the Kubernetes running at all also took way too much time and 3 people to figure out and was badly documented. It took multiple hours on at least 2 days. Necessary steps, I still remember, not being listed on one single page in any kind of overview, but somewhere a required step was hidden on another documentation page, that was not even mentioned in the list of steps to take.

Finally having set things up, I had a web interface in front of me, where I was supposed to be able to configure pods or something. Only, that I could not configure everything I had in my already containerized system, via that web interface. It seems that this web interface was only meant for the most basic use cases, where one does not need to provide containers with much configuration. My only remaining option was to upload a YAML file, which was undocumented, as far as I could see back then. That's were I stopped. A horrible experience and I wish not to have it again.

There were also naming issues. There was something called "Helm". To me that sounds like an Emacs package. But OK I guess we have these naming issues everywhere in software development. Still bugs me though, as it feels like Google pushes down its naming of things into many people's minds and sooner or later, most people will associate Google things with names, which have previously meant different things.

There were 1 or 2 layers of abstraction in Kubernetes, which I found completely useless for my use-case and wished they were not there, but of course I had to deal with them, as the system is not flexible to allow me to only have layers I need. I just wanted to run my containers on multiple machines, balancing the load and automatically restarting on crashes, you know, all the nice things Erlang offers already for ages.

I feel like Kubernetes is the Erlang ecosystem for the poor or uneducated, who've never heard of other ways, with features poorly copied.

If I really needed to bring a system to multiple servers and scale and load balance, I'd rather look into something like Nomad. Seems much simpler and also offers load balancing over multiple machines and can run docker containers and normal applications as well, plus I was able to set it up in less than an hour or so, having to servers in the system.

You absolutely can use just JSON with Kubernetes and not YAML. The K8s backend services store configuration in JSON and the API protocols use JSON. There's even a K8s configuration management tool called Ksonnet that uses an extended, JSON-like language with full program-ability, instead of the template mess of Helm charts.

I honestly couldn't tell you.

What I can tell you, is that the unbelievable bloat in the complexity of our systems is going to bite us in the ass. I'll never forget when I joined a hip fintech company, and the director of eng told us in orientation that we should think of their cloud of services as a thousand points of light, out in space. I knew my days were numbered at exactly that moment. This company had 200k unique users, and they were spending a million dollars a month on CRUD. Granted, banking is its own beast, but I had just come from a company of 10 people serving 3 million daily users 10k requests a second for images drawn on the fly by GPUs. Our hosting costs never exceeded 20k per month, and the vast majority of that was cloudflare.

Deploying meant compiling a static binary and copying it to the 4-6 hardware servers we ran in a couple racks, one rack on each side of the continent. We were drunk by 11am most of the time.

Today, it's apparently much more impressive if you need to have a team of earnest, bright-eyed Stanford grads constantly tweaking and fiddling with 100 knobs in order to keep systems running. Enter kubernetes.

> is that the unbelievable bloat in the complexity of our systems is going to bite us in the ass.

My favorite example of this right now is Vitess. Sure, it's a beautiful piece of technology. But, for a usecase my company is looking at, we'll be replacing one (exceptionally large) DB with in excess of 80 mysql pods, managed by another opaque-through-complexity system running on the top of kubernetes (which already bites us regularly even though it's "managed").

The complexity and failure scenarios makes my head ache, even though I should never have to interact with it myself.

Oh, and my current favorite PITA - having to change the API version of deployment objects from 'v1beta1' to 'v1' in over 160 microservice charts as part of a kubernetes version upgrade. Helm 2 doesn't recognize the deployments as being identical, so we're also have to do a helm3 upgrade as well, just to avoid taking down our entire ecosystem to do the API version upgrade. Wheeee!

I work at a fintech that runs a rails monolith on k8s and you would probably puke at how cheap our hosting cost is given our AUM. Engineering is a funny thing.

I'm curious how long ago you were at that company serving 3m customers a day. I have not been in the industry very long, so I don't really know what things were like >5 years ago, and don't want to sound as if I'm pretending to be an expert.

That said, a couple thoughts that came to mind:

1. having only 4 servers in 2 locations serving 3m customers a day seems crazy to me, atleast in the context of current practices regarding highly available systems.

2. not sure your cost comparisons are fair, in the first case you're talking about cloud costs (so including hardware, 3rd party services/api fees, etc), but in the second you're just talking hosting fees.

If your first company had a relatively static, hardware-heavy (gpus doing most of the work) workload, easily handled by a few servers -- then it would be crazy to pay for a cloud provider. And it wouldn't make much sense to bother with k8s or containers either (imo).

On the other hand, if the more recent company has a dynamic/spikey, software-heavy workload, with a ton of different services, orders of magnitude more infrastructure, and (being fintech) much more demanding SLAs... then it might make a lot of sense to use a cloud provider and take advantage of k8s. Especially if you're a start up that doesn't have the time/expertise to deal with datacenter design.

I agree that there's a lot of unnecessary fixation on the latest and greatest these days, but there are definitely situations where kubernetes can be very valuable.

Network effects. Kubernetes is getting into the "no one fired for choosing" category. Whatever it's flaws you can be sure it'll be a round in 10 years (or more sure than other tech). With cloud providers creating flux in their offerings, who knows if the locked-in simpler alternative will be desisted in 10 years, but at least with k8s you can move if they stop supporting it.

Does there exist a solution that does what kubernetes does but without the complexity?

If such a tool does not exist do any of you feel that the creation of such a tool is within the realm of possibility?

I would imagine all these knobs could have default configurations that 99% of all users would be okay with and that the knob should only be exposed in a small amount of cases.

It sounds like your first company did one thing well, and the second one was trying to do a lot of different things. So while volume was lower, complexity was higher.

Don't get me wrong. I'd still probably build that as a monolith in Java instead of a thousand NodeJS services, but I can see how you end up with Kubernetes.

Kubernetes makes it easier to run your application if it’s already way too complex for it’s own good.

I remember back in the day we were deploying a production video streaming server at a customer site, and a team from IBM deployed their analytics suite alongside us. We had over 8Gbps coming out of a single 1U server. The IBM installed a separate server for every Java process that their application needed, which was something like 8. It was ridiculous.

Wouldn't be prudent...

Your argument is about complexity but it doesn’t really speak to kubernetes itself. You can have some dead simple architecture on top of k8s. Hosting your own k8s though, that’s pretty complex, but get that working (or have your cloud provider just host a cluster for you) and things can be pretty darned simple.

dang, why'd you leave the old company? ;-)

> I'll never forget when I joined a hip fintech company, and the director of eng told us in orientation that we should think of their cloud of services as a thousand points of light

Let's be real, if you are old enough to get that reference without Googling, you probably would not have lasted that long at a hip fintech company anyways :-P

tl;dr - Kubernetes is a good tool, but it has been marketed and evangelized to where it is today, it's meteoric rise is not organic.

I am a huge Kubernetes fan, and think that it is a good and necessary tool with little accidental complexity (most concepts are there because you will likely need them and/or that they are a valid concern), but my position is that the growth of Kubernetes has not been organic -- it's been heavily promoted and marketed and pushed to where it is today.

Let's compare a project like Ansible first release in 2012[0], and the first AnsibleFest is in 2016[0]. Ansible is a very useful abstraction/force multiplier for doing ops. If a dedicated conference is a measure of community/enthusiasm reaching a fever pitch, it took 4 years for Ansible to reach critical mass. Kubernetes had it's first Kubecon in 2015[1] ONE year after it's initial release in 2014[2]. Did it reach critical mass 4x quicker than ansible? Maybe, but I think the simpler explanation is that the people who want Kubernetes to succeed know that creating buzz and the appearance of widespread adoption and community is more important than it actually being there, as it becomes a self-fulfilling prophecy. Once you have enough onlookers, people motivated to work on open source (i.e. give away labor, time and energy for free) will come improve your project with you, serve as an initial user base, your biggest promoters, all the while strengthening your ecosystem.

Another interesting side to this is how thoroughly Kubernetes seems to be crushing it's competition -- DC/OS (Mesos), Nomad and other competition are not fighting a functionality war, they're fighting a marketing war. DC/OS and Nomad are not obviously worse in function, but certainly don't compare when you consider ecosystem size (perceived, if not actual) and brand. It's a winner-take-most scenario and tech companies are particularly good at seizing this kind of opportunity. Of course, if you compare the resources of the entities backing these projects, it's clear who was going to win the marketing war.

In a world of free tiers as a good way to get people locked in, developer evangelists who build essentially propaganda projects (no matter how cool they are), and shrinking attention spans, Kubernetes is a good tool which has marketed itself to greatness. In it's wake there are efforts like the CNCF which I struggle to characterize because it's hard to differentiate their efforts to standardize from an effort to bureaucratize. I'm almost certainly blinded by my own cynicism but most of this just doesn't feel organic. Big, useful open source software gets world-renowned after years/decades of being convenient/useful/correct/etc but Kubernetes (and other projects given the CNCF gold star) seem to be trying to skip this process or at least bootstrap a reputation out of the gate.

DevOps traditionally moved much slower -- I can remember what seemed like an age of "salt vs ansible vs chef", with all three technologies having had lots of times to prove themselves useful. Even the switch to containers instead of VM/user based process isolation took more time than Kubernetes has taken to dominate the zeitgeist.

[0]: https://en.wikipedia.org/wiki/Ansible_(software)

[1]: http://www.voxuspr.com/2019/03/what-is-kubecon-its-past-pres...

[2]: https://en.wikipedia.org/wiki/Kubernetes

The arguments used to consistently market software

1. It's portable

2. It's fast

3. It's declarative

4. It's fun / productive / easy

5. It's safe / automatic

6. It's an integrated framework

The opposites are also used to detract competitors.

The idea of k8 is that it will be portable to all hosting providers and linux distributions as opposed to developing shell scripts for Red Hat, especially multiple versions. I don't think it's easy or fun or fast.

Because everyone chases the newest, shiniest thing in tech, and it's not cool nor fun to make boring old stuff in C then copy one binary and maybe a config to the server.

Even if one does have a single binary and config file that one can just copy to a server and run, there's more to non-trivial deployments than that. For example, how do you do a zero-downtime deployment where you copy over a new binary, start it up, switch new requests over to the new version, but let the old one keep running until either it finishes handling all requests that it already received or a timeout is reached? One reason why Kubernetes is popular is that it provides a standard, cross-vendor solution to this and other problems.

Then you need to add management of storage for it, management of logs, integration of monitoring, healthchecks, maybe some multiple environment case because UAT is good thing to have, etc. etc.

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