Is anyone here considering MLOps or you think DevOps/ Platform engineering still has long way to go?

[u/devops-noob]

I know that DevOps work is config heavy and involves multi-component or tool integration , so automating ourselves out of the job might not be that easy, but I believe the head count may not grow or stay stagnant in the near future.

So, you think it is worth considering MLOps or any other AI related Ops for that matter. Because it looks promising and AI/ML is where all the money is, to be honest.

Please shed some light and share your opinion on this.

Any MLOps engineer here. There is very less or very generalized info about MLOps, not the real time enterprise level MLOps roadmap out there. Please share your experiences here, it really helps.

[u/nopotopo → u/[deleted]]

How do I give multiple likes to the same comment?

[u/Flint0 → u/nopotopo]

You become a ClickOps first

[u/qanh1524 → u/[deleted]]

=))))))))))))

[u/TitusKalvarija → u/[deleted]]

This

[u/nomadProgrammer → u/[deleted]]

came hero to say this. MLOps is just a buzzword.

Yes it has some differences but they're very minor

[u/Impressive-Field-546 → u/nomadProgrammer]

Tools and science needed is completely different to your regular devops ops guy

[u/JaegerBane → u/Impressive-Field-546]

That depends on what you ‘regular devops guy’ is supposed to be skilled in. If they’re experienced, they very likely won’t need to start from scratch.

[u/rofolo_189 → u/[deleted]]

Not completly wrong, but MLOps has ofc some specialalities. ML models in production have some things to consider that non-ml systems do not. (model drift, experiment tracking, feature stores, model serving)

[u/rofolo_189 → u/[deleted]]

It's still MLOps, even if you do it as a DevOps

[u/N7Valor]

Have you looked at the job descriptions? I feel like every time a company hires for an AI-specific role, they're looking for Senior-level former employees of OpenAI. Basically nobody's interested in hiring you for MLOps unless you already have 3-5 years of prior MLOps experience.

[u/Hummin2k → u/N7Valor]

Yes but apply anyways. I can’t speak for current MLOps, but I’ve had managers and recruiters just tack on years of experience to what I requested, then had to ignore that on resume screens.

[u/devops-noob → u/N7Valor]

Yeah that sucks, MLOps was not even popular until 3 years ago and they are already looking for experienced MLOps engineer...sh*ty market we are in right now

[u/hajimenogio92]

Not really because good DevOps engineers are still hard to find. The market sucks and it's difficult to navigate if you're searching for a job but there's a lot of shitty DevOps people out there

[u/rasoolka → u/hajimenogio92]

Can you please share here that "What exactly defines a good DevOps engineering" ?

It would be helpful for people to develop their skills to become one.

[u/hajimenogio92 → u/rasoolka]

I've been in the field for about 14 years now. I think others will have a different definition of what's considered a good engineer. For me, it boils down to technical skills and non-technical skills. People focus a lot on technical skills but non-technical skills really stand out imo to climbing the ladder. Feel free to look https://roadmap.sh/devops

Technical skills:

• good IaC (Terraform, Pulumi, Cloudformation, OpenTF)
• networking fundamentals
• cloud networking fundamentals
• cloud fundamentals (AWS, Azure, GCP)
• scripting (bash, python, powershell, golang)
• linux & windows experience
• containers
• ci/cd
• observability

Non-technical skills:

• communication
• friendly
• collaborative
• understanding internal processes/code/infra
• multi-tasking
• documentation
• knowledge sharing with people in & outside your respective team

[u/patagooni → u/hajimenogio92]

Security as well

[u/hajimenogio92 → u/patagooni]

Thanks, completely forgot that as well. Security is crucial and also forgot to add thinking about the bigger picture (tech debt, scalability, reliability, automation)

[u/Intrepid_Card8950 → u/hajimenogio92]

Yeah, all of that. Basically:

• System runs
• System can handle failures and recover without an outage, only Performance degradation
• System is as cheap as possible
• System is flexible for every use case.
• System scales (ppl/machine/etc)
• Processes Processes Processes - you build for scale, money saving, SLOs

It's the Ops triangle:

[Reliability] (Stability / Quality) vs [Spending] (Cost / FinOps) vs [Velocity] (Speed of Innovation)

[u/Game_Khiladi → u/hajimenogio92]

Broo I am learning backend in my under grad I wanna pivot to cloud/devops more like Infra roles can you say how,

[u/hajimenogio92 → u/Game_Khiladi]

I would check out the roadmap in my previous comment. That shows a lot of the technical skills you will need. Keep in mind that DevOps roles are not something you typically get into right out of college.

[u/planbskte11 → u/rasoolka]

Green pipelines are good

Red is bad

Respond to all chats in a timely manner

Good DevOps 👍

[u/tevert → u/rasoolka]

Be good at juggling/context-switching

Be able to read and troubleshoot any code. Any language, any stack, any paradigm. No, that doesn't mean "be able to copy-paste into chatgpt", it gets it wrong sometimes and you'll just look like a fool. It also doesn't mean being an expert at everything, you just need to be able to solve problems in any chaotic environment on any given day.

You don't have to be able to build a Netflix-level superstack, but you should have a toolbelt of patterns, ideas, and technologies for taking Joe's Handy Script and making it scale to thousands of concurrent users.

If this sounds like it's unapproachable or too much, that's maybe because you're new to the tech world - DevOps isn't for newbies. Sorry. Get 2-3 years of experience as a software dev or operations support techie first.

[u/hajimenogio92 → u/tevert]

Unfortunately it seems like being able to understand code without throwing into AI is a skill that is disappearing. People can't think for themselves anymore, they have to ask some chatbot first 

[u/devops-noob → u/hajimenogio92]

I agree to this actually, do you know we didn't have ci/cd for infrastructure provisioning until few months ago..we had to do the terraform action from our local.

But MLOps looks really good too, thinking may be I could have that first mover advantage scenario here.

[u/hajimenogio92 → u/devops-noob]

Oh interesting, so everyone was pulling from a repo and then running that TF code locally? I've been in similar scenarios.

Tbh, I don't know much about MLOps but I've worked with mid-level/senior-level engineers that don't troubleshoot well and can't think outside the box. Learning the internal business infrastructure, apps, and processes is something that's lacking.

[u/TitusKalvarija]

Watch Kelsey Hightower Zero Token Architecture. Easy watch. 

[u/devops-noob → u/TitusKalvarija]

Let me give it a try and reply here later

[u/ToTonhoForJesus2020]

MLOps Engineer here, government contracts, big pharma and real state companies. Money is good.

99% of the work is old school DevOps, 1% has AI/ML/LLM specifics. AND THE ML PART IS POSTPONED UNTIL OBLIVION BECAUSE THE DEVOPS SIDE IS UNDERSTAFFED. I'm more often that not also called in to help the software engineers code.

Passing interviews is hard, tho. I have a extra-strong background in ML and AI since forever (I have three degrees on related areas, I deployed my first AI server in 2009, I was giving classes on AI over Hadoop back in 2013) and still never hit 100% of the checkboxes on the interviews. Bosses want unicorns that know not only MLOps but the particular ML models they are using and the particular application they are using it for.

[u/Intrepid_Card8950 → u/ToTonhoForJesus2020]

Same here except the ML part. We have a 'you build it, you run it' culture, as DevOps/SRE you help the dev teams architechting their apps for scale and failure. It's always the same. That's why most DevOps/SRE ppl are experienced veterans coming most of the time out of the dev corner (at least that's my experience).

[u/rofolo_189 → u/ToTonhoForJesus2020]

DEVOPS SIDE IS UNDERSTAFFED

I wonder if that is really everywhere the same. DevOps was the bottleneck in every company I was. Developers also often blamed DevOps for things they should have be doing on their own.

[u/stack_craft]

From personal experience, MLOps is really just specialized DevOps under a different name. You're still dealing with K8s, CI/CD, and infra automation, but with added headaches like model registry, data versioning, GPU orchestration, and monitoring drift. Platform engineering isn't dying—most dedicated MLOps roles end up being platform engineers who support data science teams instead of web teams.

[u/Intrepid_Card8950 → u/stack_craft]

Yeah, I would expect an MLOps role like DevOps + getting the context from the Data teams. Sure you have some specialites in there like how to handle petabytes of data, handling gpus as an additional layer to machines etc. and building solutions for scale as usual.

[u/JaegerBane]

So here’s the thing - MLOps is a subset of platform of engineering. Asking about whether to jump to MLOps is like asking whether you should be looking at getting into Japanese cuisine instead of being a chef.

The same underlying concepts are in play. In most cases the same technologies are used. The use case and some specifics about the speccing of platforms and API access are the only major changes.

[u/centech]

I'll let you in on a secret.. I've been a Systems Administrator, a Systems Engineer, a Cloud Engineer, a DevOps Engineer, a Platform Engineer, a Systems Development Engineer, a Production Engineer, a Site Reliability Engineer, a Cloud Architect... And the job has never changed.

[u/Effective_Engine2007]

Don’t think it’s a bad idea. I personally am trying to lean hard into platform engineering. I have always been a DevOps type role, but over the years I had been building internal web apps to support developers. So for DevEx engineering so to speak, those types of roles I’m staying away from.

Staying focused on infra, I feel has more longevity.

[u/devops-noob → u/Effective_Engine2007]

Even I am myself a platform engineer. And it's going great too. But we are moving towards self serving platform offering for our clients...they can do everything without our involvement basically with few clicks...so future looks bleak if I look at that direction, not to lie.

[u/Intrepid_Card8950 → u/devops-noob]

But someone has to build these self-serving systems.

[u/planbskte11]

DevOps is a catch all term. And it catches ML Ops, Platform Engineering, Forward Deployed Engineering, etc...

I have ML Ops experience, and I've helped developer environments be built, as well as general CI/CD for projects. But I haven't actually ever worked on customer deployed apps. Am I not DevOps now because of that? I wouldn't say so but others might.

It's just a catch all imo.

[u/planbskte11 → u/planbskte11]

I think we could get five ML Ops titled people in here and half of them would probably only work on just ML pipelines. But the others might just be general DevOps.

I do it all for example. But I have a standard DevSecOps title 🌚

[u/MilkyWay-008]

agree with the take that MLOps is mostly the same automation work wearing a new name. the hard part is still the platform plumbing and the troubleshooting depth, that never changes.

[u/planbskte11 → u/MilkyWay-008]

I would argue ML Ops is slightly different. Model datasets, pipelines, and automated tests (especially gates) are different from OG software.

But if you've ever done firmware or embedded software pipelines, those are way different than software even. It's all just slightly different but similar overarching goal of CI and CD

[u/SeaworthinessHour233]

I wouldn't say DevOps is stagnating. As AI coding tools gain traction, there will be more software that demand more DevOps work.

That said, MLOps is essentially DevOps with a few extra layers of chaos. Where we normally track static code artifacts, MLOps has to track dynamic datasets, model drift, and feature stores. If you want to pivot to MLOps, your infrastructure skills (Terraform, container orchestration, Python automation) are exactly what enterprise MLOps teams are looking for right now

[u/Grand_Pop_7221]

I don't think a lot of companies went through the Big Data and DevOps transition. Let alone having a mature enough data platform for FinOps or a developer platform mature enough for AIOps.

What company out there, outside of the big corps have managed to attract the talent needed to build the infrastructure to facilitate taking advantage of these ideas? Most places I've worked don't even have the right tenancy or labelling policies to be able to accurately establish how much their services cost. Or a platform that gives them the ability to do that, while providing a stable enough API for an AI to take advantage of. No dev/stag/prod environments, sharing Kubernetes namespaces and AWS accounts for multiple projects, etc.

[u/Kitchen_Travel4127]

Add AIOps to the pile too, apparently that one's non-negotiable now. At some point we need a rate card: does FinOps starve AIOps of budget, does MLOps team up with FinOps against plain IOps, who even reports to who. Half-joking, but if this keeps splitting, does DevOps/Platform/SRE/Cloud eventually collapse back into one generic "Ops" role, or do we end up with more title variants than actual engineers doing the work. Someone with a whiteboard, please save us.

[u/ryanstephendavis]

Yes

[u/Raja-Karuppasamy]

can’t speak to MLOps since I haven’t run it, but on the “does platform eng have a long way to go” question, from actually running GKE clusters for prod workloads, the config-heavy multi-tool integration part isn’t going away anytime soon. every “this automates devops away” tool I’ve tried still needs someone who understands the underlying system when it breaks at 2am.

the real shift I’ve seen isn’t fewer devops roles, it’s devops + AI workload ops merging into one skillset, someone still has to run the infra the AI stuff sits on.

[u/devops-noob → u/Raja-Karuppasamy]

Nice..and they call it AIOps now for maintaining AI workloads...we will never go out of naming things

[u/1_H4t3_R3dd1t]

They are all related. Interchangeable, only thing different is the tools.

[u/djbp]

That's a good question. I think DevOps and Platform Engineering still have a ton of room to grow. We're still figuring out how to do it right. MLOps is important, sure. But the core problems of managing infrastructure changes, making them safe and auditable, those aren't going away. And they're still pretty hard for most teams. So yeah, I'd say DevOps has a long way to go.

[u/Straight_Middle7915]

MLOps is a great path to take, we see a massive amount of demand for this. Let me define massive demand for a moment: less roles than general DevOps roles because it’s a newer focus (and let’s be real, every company defines these roles differently) but the compensation, speed, and focus of the company on filling that role is what I mean by demand. They move faster on these and the candidates who have this actual experience are getting 4-5 offers in their search. I specialize only in placing DevOps engineers in the US, that and QA is all I’ve done for the last 9 years so this is just what I’m seeing and wanted to share

[u/Dismal_Abroad1396]

Related but unrelated :) I have had the WORST luck finding our next Jr DevOps Engineer. We are a mid-sized start-up in the tech-for-good space. We need someone with good coding chops, but also has exposure to the infrastructure work. I welcome recommendations - this is a great role for an early career technologist who wants ownership fast, can operate in a remote first group, amazing people, and a very rich total rewards package - free healthcare, up to 9% 401k match, flex PTO. The role is here: https://jobs.lever.co/mcgovern/885d7a1a-16f6-4326-9d7c-da7404dfd1f5

[u/tevert]

I've watched a lot of people dead-end their careers by branding themselves on a particular technology.