[Townley]

That push towards growth is real across both sides of the developer-administrator spectrum (I know many experienced developers struggling through React/Vue, ETL pipeline tools, or more devops than they'd prefer).

Across the board, it's partially fad and hype, but it's also because these workflows really are better. On the k8s side, a containerized architecture gives developers peace of mind in their local environments, makes you more provider-agnostic, and has the potential to scale more easily.

A sysadmin who can provide all of those is valuable, and deciding if that value is worth the learning curve is an individual decision. But to whatever extent the "resume-driven-development" aspect of container orchestration hype is distorting the market, it does seem to be in service of a better (if more complicated) toolset.

[eropple]

> a containerized architecture gives developers peace of mind in their local environments

...unless you use cloud-specific services, which almost everybody should be doing because the management load of self-hosted alternatives is very high. Correctly care-and-feeding a message queue or a log store is so much more work than creating an SQS queue or a Kinesis shard, especially when you are not running a company centered around managing a message queue or a log store. Which you probably aren't. Localstack exists as an AWS stub for local development, but it sure isn't great and the impedance mismatch is pretty high--just trying to write Pulumi code that can target either it or AWS proper is an exercise in frustration.

Don't get me wrong: containers as a better way to ship "statically linked" applications are great. But none of the container-orchestration stuff seems out of the "hype" stage from anything I've seen as a consultant or as a line developer; I've never-not-once found a reason to reach for k8s on any major cloud provider. I guess it's OpenStack 2.0 for on-premises deployments, and in that light there's definitely some value, but your cloud provider is doing a lot of work that you're already effectively paying for by being in that ecosystem--for most users (who can't hire somebody like me) it's worth using it.

[streetcat1]

I think that you might be able to replace SQS specific queues with knative eventing. This should provide some insulation from aws specific services.

[eropple]

1) I don't use "work-in-progress" things in production (unless I own it and wrote it) and I have a hard time recommending others do so.

2) It's not just events in your application you have to worry about, but environmental stuff as well. SNS is the lingua franca of AWS and you've gotta put it somewhere, with reliability guarantees. That increases the amount of orchestration you have to do outside the safe-and-happy confines of k8s itself, and that makes my job way harder than having only-one-road-to-plow.

At my current company we use ECS/Fargate, but it's only really so we don't have to manage servers; each ECS service has one task and is independently managed. And it interacts directly with the baseline cloud provider so there's no weird jank at the edges of our compute vs. our datastores. The containers are a convenience here--I'd use EC2 just as readily. But I see no real value to using k8s instead and haven't at any of my consulting gigs to date, either. The k8s environment is both incomplete and at best kinda-incompatible with the things that actually matter, like your data, and TBH it casts real doubt on the reason to use it.

[streetcat1]

So I have no doubt that SQS is more mature than knative. In my case I am developing an actual product IN k8s (with around 40 new CRDs) , so my goal is to use as much of the platform as possible (including istio and knative) and avoid cloud specific services.

The value with k8s is that you can abstract the underlying hardware by using only k8s objects.

[eropple]

"The underlying hardware" has side effects. You can't exactly ignore them. And your cloud provider has non-substitutable stuff. Just as an example from my day today, by hewing to k8s you lose stuff like Athena and Glue for data analytics and ETL. I'm sure somebody out there would like to charge me 10x what AWS does to do a worse job of it inside of k8s, but no. So instead you get a Frankenstein of Terraform/Pulumi/CloudFormation and (poor and poorly expressive) k8s configuration and you've geometrically increased the complexity of your system, your failure cases, and the challenge of solving a problem when you're under the gun.

So your product might be fine, but everything that exists to feed it--be it monitoring and alerting or business analytics or security or even hands-on operational control surfaces--is going to be worse for it and create marginal drag every step of the way (either in terms of labor or money).

More and more (and your comments are reinforcing this position, TBH) I get the "it's a slick five-minute demo" argument out of k8s, much the same way that Docker brainwormed people long before it was good or useful. I have a cluster at home, and it's fine, but it's for play. I can't afford systemic drag from immature and possibly-wrong tech choices where I've gotta make money, though.

[streetcat1]

Thanks for the feedback. I do not think that k8s is bad bet long term as you paint it to be. Of course it is less mature than AWS. But the point is 5 years from now.

The problem with AWS is the price and the latency. Everything is fine until you get the bill. But by than you are completely locked to that architecture. The same apply to all the public cloud providers, not just AWS.

So as I see it, for new applications which are based on micro services, and want some day to become self managed, K8S is the only long term good bet.

[weberc2]

> On the k8s side, a containerized architecture gives developers peace of mind in their local environments

We're looking at moving away from containerized local development (using Docker for Mac on high-end MacBook Pros) because the performance is abysmal. The Linux VM eats 100% CPU at idle (i.e., with no containers running at all) and our handful of pretty simple containers bring the machines to their knees. It's unclear if we're hitting some pathological case (maybe volumes of 100s of MBs?) but there are many, many other issues filed against Docker for Mac about its high CPU usage. We've tried all of the usual things--blowing away the VM, tinkering with different resource allocations for the VM, etc, but we haven't had much luck (nor have the other users who have filed issues against Docker for Mac, judging by the comments).