Pratique du Shadowing: How to ACTUALLY Get a DevOps Job in 2026 - Apprendre l'anglais à l'oral avec la vidéo

What would it take for a complete beginner, someone with no IT job,

no production experience, and no idea where to start to become somebody that a company trusts with production deployments and infrastructure?

Is that actually realistic in 2026?

I think it is.

I think you can absolutely get there, but you need to understand what the path looks like and what you're building towards.

You need to understand Linux.

You need to understand the software development life cycle.

You need to understand scripting and you need to understand web hosting very well.

You can learn AWS, Terraform, Docker, Kubernetes in isolation, and that's fine.

It's useful, but putting those tools together and getting that real experience is what's going to take you to the next level.

It'll make you ready for the job.

And I'm going to be honest, going straight from beginner to a DevOps job is something that's not super realistic, unless you find some junior DevOps position where they're willing to train you in,

which is exceedingly rare nowadays.

But I don't want this to get you discouraged.

This does not mean that DevOps is out of reach.

It means you're going to build your way there.

By the end of this video, you'll know which first job to pursue, what to learn, what to build, and then when you should actually start applying for DevOps jobs.

So where should you start?

In my opinion, you should still start in help desk, tier one support, IT, maybe at an MSP.

You're going to have to understand how production systems work.

Then you move towards system administrator or cloud support.

Maybe you get a cloud engineer job and then eventually you become a DevOps person.

How long does this take?

Well, there's honestly no real minimum and it depends where you're at technically and with your experience.

I think increasing responsibility and exposure matters more than how long you stay in any given position.

You're probably going to be administering systems first, and then you're going to get that Linux and cloud experience.

But what if you're already a software developer?

This is an entirely alternate path.

From this side, you have to pick up the infrastructure stuff.

From the operations side, you have to learn Git, GitHub workflows and source control, pull requests, testing and staging environments, build artifacts and CICD.

And from the software side, of course, you have to learn the infrastructure stuff.

So either way, you're just learning the other half, essentially.

Now, what level of Linux do you actually need for this?

Well, Well, if an application that's running on a Linux server starts breaking, you should be able to troubleshoot using logs without going directly to a tutorial.

That means being comfortable with Linux users, processes, services, files and permissions,

packages, logs, SSH, networking, and then environment variables as well.

If you want something to move towards, I think RHCSA, the Red Hat Certified System Administrator, is a decent certificate to look towards.

I myself will probably get this at some point.

If you can't tell, I'm pretty bullish on certifications in general.

I think they really force you to get the experience needed to do these types of jobs.

So now you've started administering systems.

You've worked your way past help desk.

Now it's time for you to start understanding the software that's running on them.

You need to understand the entire software development lifecycle.

A developer starts with an issue.

They make a branch.

They commit their changes.

They open a pull request.

That code needs reviewing before it's built and deployed.

Then you need good monitoring and a way to roll back if something goes wrong.

And then you've got secrets all over the place.

API keys, tokens, database passwords, usernames, DB URL, all of this stuff.

Your app is going to need them.

So is your CI pipeline.

So are your Kubernetes clusters.

How you manage these secrets is very, very important.

I'd use a secrets manager, like in physical.

Full disclosure, that's the company that I work for.

But you could use any secrets manager.

The point is centralizing your secrets allows you to fine -grained scoped access to them.

You can rotate them from one central place.

You can sync them to all of these different places, whether that's GitHub, whether that's, you know, your CI pipeline, whether that's your Kubernetes clusters or Vercel or whatever other service you're using.

Now, this also makes CI and it makes local development so much easier as well.

The point I'm getting at is learning about secrets management has, to me at least, by proxy, taught me so much about how production infrastructure runs.

Now, on the note of production infrastructure, one thing that I personally wish I started learning earlier was Kubernetes.

I would learn Kubernetes as early as you possibly can.

I was a Windows system administrator.

I didn't do tons of Linux.

We had some Linux boxes that we were, you know, kind of managing but it's mostly just updates

and like easy scripts and stuff but i moved to the startup

and physical in the infrastructure security space

and this is like you know dev sec ops adjacent

and kubernetes was huge it was a big learning curve for

me i had to spend weeks learning kubernetes i was like

walking on the treadmill watching videos about kubernetes i was dreaming about kubernetes i was learning about kubernetes secrets

and how these apps ingest you know secrets

and where the source of truth should be

and how external secrets operator works

and how authentication from your kubernetes cluster to you know your secrets manager works And then that's just secrets management.

Of course, there's like the entire architecture of how Kubernetes works, right?

What a pod is, what a node is, how the control plan works, what the, you gotta learn the command line commands, the kubectl commands, I like calling them kubectl commands.

This is all important stuff.

And it's stuff that I wish I started learning earlier.

Because once you start to understand ingress and deployments and services

and this cluster architecture and really like how all of this high level pieces kind of fit together, I think something clicks in your mind about distributed infrastructure and distributed systems.

And when you start thinking like this, it makes you more of a systems thinker.

And this is 100 % necessary if you wanna be a DevOps professional.

Now there is a cert in the space, as I'm sure you could guess.

I do wanna get it at some point.

It's called the CKA, the Certified Kubernetes Administrator.

There's actually a few of them.

This is just kind of like the first one, the main one.

And I really think that this would be worthwhile for you to get, because in order to get the cert, you have to be able to administer, troubleshoot and debug Kubernetes things really fast and

so it just kind of forces you to be an expert

once again in this domain now alongside this you need real

kubernetes projects as well now how would i use ai in

this entire process well i would definitely be using ai i

would use it to help me script i would use it to help understand what the scripts are doing understand

that you don't have to know the exact syntax of the language

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that you're scripting in in order for you to be a

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devops professional nowadays like i'm gonna be honest with you nobody software engineers included or i should say very very, very few are handwriting code letter by letter anymore.

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It's mostly reviewing the output that an AI created.

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Now, this might not be as fun as handwriting code, but I can tell you debugging is a lot more fun

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because you don't have to spend days at a time looking through stack traces and trying to track something down manually.

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So you've got to understand how an API works.

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You've got to understand error handling.

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You've got to understand environment variables.

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You've got to be using AI extensively if you want to be successful in tech nowadays.

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But most importantly, it's the context.

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You need to understand which systems can I and should I automate, whether it's with AI, whether it's with a script, whether it's with N8N or something of that sort.

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In DevOps, you're managing millions, billions of dollars of infrastructure.

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So it's important that you know what you're doing when you're dealing at these different levels.

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You know, if you're doing something locally on your device and just testing something out, you can automate it with AI.

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If it works as you go up this kind of responsibility ladder, we have to have the context about where you can safely run certain things and what the fallback plan is.

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This is huge.

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And this isn't just unique to DevOps.

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This works in IT.

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This works in software development.

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This works for platform engineers.

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This is for everybody, right?

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You have to have context around what you're doing.

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Don't be reckless, essentially, is what I'm saying.

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Now, what project would I build that kind of brings all of this together?

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I would build a small containerized application with a database, put it in GitHub, use pull requests

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and the entire software development kind of process in order to actually merge things into main, set up some CI tests and GitHub Actions, build it, deploy it on Kubernetes,

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you know, set up DNS and HTTPS and host it on real production servers.

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Once it works, break some stuff, mess up DNS, mess up a credential, mess up some setting with the database

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and understand deeply why you've messed this thing up

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and how you've messed it up and how you could fix it in production.

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Now, putting together this project requires a lot of curiosity and conscientiousness.

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Again, you're going to be working with AI to actually set something up for you, but it's quite a lot of work to make up the entire environment and try and mimic a real world scenario and,

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you know, use GitOps and use again, this pull request workflow and understand all of this hosting stuff.

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And then also introduce purposeful problems.

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Like this is a lot of work.

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I'm not going to lie to you.

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And does this count as production experience?

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Of course not.

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You don't have to lie and say that you've managed production Kubernetes clusters before you actually have, but it is experience.

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It's useful experience.

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And through the process of doing all of this work that is going to be painful, you're going to learn a lot of useful stuff

141

and this my friends will help you in an interview

142

and help you talk confidently about things

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and as i'm doing this i would be writing blogs i

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would be you know making articles i would make a website

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somebody asked this in the youtube comments the other day

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that was like hey how public should i be with my

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learning nowadays being public is as easier as it's ever been

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because you can use ai to help you be public of

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course don't just push out slop nobody's going to like that

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but build things and be curious as much as you possibly can

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and learn in public it's going to help you so you're a complete beginner where do you start i would learn networking, Linux, and Git at a very basic level, and I would start building one application.

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I would still get my beginner level certificates and try and go to, you know, tier one help desk, system administrator, something of that sort, MSP, things like this.

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I would use AI to teach me as much as possible.

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I have a video on Matt Pocock's slash teach.

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It's an AI skill

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that you can use to help AI teach you over a long period of time with some goal in mind.

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It's super, super good.

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Definitely go check it out.

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Matt Pocock is the goat of AI skills.

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Now, when should you start applying for DevOps jobs?

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Again, I would generally say you should start learning things earlier than you think you should.

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So as you're getting your system administrator position, you should be learning Kubernetes.

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You should be learning all of this software side of things.

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You should be learning how infrastructure actually works.

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Of course, you're going to do that in your job as well.

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Once you have a year, year and a half of troubleshooting experience under your belt with just real technical systems, it doesn't have to be distributed systems and all of this insane stuff,

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I would start applying understanding that this application process is going to be a longer application process.

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It's not going to happen overnight.

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But as you have this technical job and you're learning these technical DevOps applicable things, start applying for a job.

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And then also understand what the job is.

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You are going to be a jack of all trades.

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You're going to be managing infrastructure.

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You're going to be up at 3 a .m doing on -call rotation stuff.

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You're going to be the guy or girl who everyone expects to know everything, even though you don't.

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And in today's day and age, working in big tech, things change every two weeks.

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Like legitimately, the thing that you thought was super important two weeks ago might not be super important anymore.

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And there's another thing that you have to learn that's super important.

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This for some people is mentally draining.

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This for me invigorates me because I'm always learning new things and it's super duper fun.

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And I feel like I get to be at the bleeding edge of technology.

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And so this is really cool.

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So yeah, guys, this has been how to actually get a DevOps job from zero in 2026, 2027 seven, I imagine this is still going to carry over.

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I wish you luck.

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If you have any questions, you know, leave them in the comments.

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I read every single one.

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Thank you so much for watching and we'll talk to you in the next one.

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Goodbye.

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Vocabulaire et conseils d’expression pour cette leçon

Cette leçon d’expression orale de niveau C1 s’appuie sur la vidéo « How to ACTUALLY Get a DevOps Job in 2026 ». Les mots qui reviennent le plus souvent : kubernetes, learning, devops, secrets, infrastructure. Cette vidéo contient 187 phrases et 2380 mots à répéter en shadowing. La partie parlée dure 10:15. Le locuteur parle vite, environ 232 mots par minute : attendez-vous à des liaisons et à des sons réduits. 82 % des mots font partie des 3 000 mots les plus courants en anglais ; le reste mérite d’être vu avant de commencer.

Vocabulaire clé de cette vidéo

Les 15 mots les plus avancés de la vidéo, avec leur prononciation et leur sens :

Mot	Prononciation	Sens
administrator nom	/ədˈmɪn.ɪ.stɹeɪ.tɚ/	administrateur, administratrice
cluster nom	/ˈklʌstɚ/	groupe
beginner nom	/bəˈɡɪnɚ/	débutant, débutante
administer verbe	/ədˈmɪn.ɪ.stə/	administrer, gérer
distribute verbe	/dɪˈstɹɪbjuːt/	distribuer
automate verbe	/ˈɔ.təˌmeɪt/	automatiser
debug verbe	/diːˈbʌɡ/	débugger, déboguer
workflow nom	/ˈwɝkfloʊ/	workflow
handwriting nom	/ˈhændɹaɪtɪŋ/	écriture
litter nom	/ˈlɪt.ɚ/	litière
deployment nom	/dɪˈplɔɪmənt/	déploiement
pipeline nom	/ˈpaɪpˌlaɪn/	pipeline
artifact nom	/ˈɑɹtɪfækt/	artefact, artéfact
authentication nom	/ɔːˌθɛntɪˈkeɪʃn̩/	certification
centralize verbe	/ˈsɛntɹəlaɪz/	centraliser

Les verbes à particule que vous entendrez

Mot	Prononciation	Sens
mess up verbe		gâcher
set up verbe	/ˌsɛt ˈʌp/	mettre en place, installer
go up verbe		monter, s'élever
make up verbe	/ˌmeɪk ˈʌp/	constituer, composer
pick up verbe		soulever
put together verbe		assembler

Des phrases à répéter

Des phrases courtes et complètes de la vidéo, à réutiliser dans la conversation de tous les jours :

It'll make you ready for the job.
It means you're going to build your way there.
But what if you're already a software developer?
You've worked your way past help desk.
I'd use a secrets manager, like in physical.

Prononciation à surveiller

Le locuteur utilise 63 contractions et formes réduites, comme you're, you've, I'm. Prononcez-les sous leur forme courte, telles que vous les entendez.

Les sons « th »: authentication /ɔːˌθɛntɪˈkeɪʃn̩/, thinker /ˈθɪŋ.kɚ/, worthwhile /ˌwɜː(ɹ)θˈwaɪl/
Les sons « sh » et « zh »: troubleshoot /ˈtɹʌbl̩ˌʃuːt/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, bullish /ˈbʊlɪʃ/, credential /kɹɪˈdɛnʃəl/, certification /ˌsɜː.tɪ.fɪˈkeɪ.ʃən/
Mots longs — placez bien l’accent: administrator /ədˈmɪn.ɪ.stɹeɪ.tɚ/, administer /ədˈmɪn.ɪ.stə/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, confidently /ˈkɑnfɪdəntli/, exceedingly /ɪkˈsidɪŋli/

Les sons difficiles pour les francophones :

/tʃ/ et /dʒ/ — à ne pas adoucir en « ch » et « j »: ingest /ɪnˈd͡ʒɛst/, discourage /dɪsˈkɝɪd͡ʒ/, merge /mɝd͡ʒ/
/r/ anglais — langue recourbée, sans frotter la gorge: administrator /ədˈmɪn.ɪ.stɹeɪ.tɚ/, distribute /dɪˈstɹɪbjuːt/, troubleshoot /ˈtɹʌbl̩ˌʃuːt/, handwriting /ˈhændɹaɪtɪŋ/, artifact /ˈɑɹtɪfækt/

Comment s’entraîner avec cette vidéo

Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
Commencez à la vitesse 0,75×, répétez phrase par phrase, puis revenez à la vitesse normale quand cela devient facile.
Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme administrator, cluster, beginner.

Qu'est-ce que la technique du Shadowing ?

Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.

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