Why DevOps Demand Is Exploding (5 Critical Factors)

If you're watching this video, you are probably thinking about learning DevOps skills or maybe you are already in tech and considering upskilling in this direction. Now, I'm going to tell you something very important. Right now, at this exact moment, we are in a rare window of opportunity for DevOps skills. And this window won't stay open forever. So in this video I will explain why DevOps skills are about to explode in 2026 and beyond which five factors drive that demand and most importantly what you need to learn and what mistakes to avoid to take advantage of this opportunity before it's too late. So let's get into it. Here is what most people don't realize. DevOps right now is exactly where software engineering was 10 years ago. So, let me explain what I mean. 10 years ago, if you had basic coding skills, like you could write some Python, you understood loops and functions, you could get a software engineering job. Not just any job, but a job with proper pay, benefits, perks. Companies were desperate for software engineers. They would hire people with relatively basic skills and then train them at work. Why? Because demand was incredibly high and the supply was too low in comparison. But then what happened? Supply cut up. More people learned to code. Boot camps appeared everywhere. Universities expanded their computer science programs. And suddenly having basic coding skills was not enough anymore. Now to get a software engineering job, you need to stand out. You need to know data structures, algorithms. You need to pass technical interviews. You need a portfolio of project that proves that you can actually program more complex applications. So the bar got higher because supply met demand. And this is a natural cycle. It always happens. And right now we are in the exact same stage with DevOps where supply is way lower than the demand. So let me show you the data. DevOps reports from this article show that 37% of IT leaders name DevOps and Dev Sec Ops as the biggest technical skills gap in their teams and 31% of the DevOps leaders say a lack of skilled resources is their biggest challenge. Also interesting, DevOps positions stay open three times longer than any other IT roles. Three times. That's not a small difference. That means companies are actively searching for DevOps engineers and they can't find enough qualified people with these skills. So demand is extremely high and supply is low. And this is exactly the best time to get into any profession. But here's what you need to understand. This optimal window will not last forever. Because just like I mentioned, the same way it didn't last forever for software engineering, the supply will eventually catch up. Whether it takes 2 years or 10 years, eventually it will level out. More people will learn DevOps. The bar will get higher. The opportunities that exist today will be harder to access tomorrow. So still there but they will be harder to access tomorrow. This means if you've been thinking about learning DevOps and you've been waiting for the right time, this is it. This is the right time. This is the window of opportunity that you should take advantage of right now. Now, I've put together this DevOps career guide that breaks down salary ranges by country related career path and a lot of more details. Everything that you need to understand what this opportunity actually looks like in your job market. So if you want to understand that in detail then grab that resource from below the video from description because it may help you understand and put things really in perspective that can motivate you to take your next step. But right now we're not talking about a steady growth of DevOps demand. We are actually talking about explosion in demand for DevOps skills. But why specifically will 2026 see this explosion in DevOps skill set demand? What is so significant about what's changing in the next year? So let's talk about five factors that are coming together right now that is contributing to that explosion that we're going to see. First of all, cloud

adoption is accelerating. More companies are moving now from onremise to cloud at a faster speed. So more legacy systems are being modernized and every company going through this transition needs DevOps expertise and the companies will be bidding against each other to get the most qualified DevOps engineers on their teams. Second, Kubernetes and container orchestration are becoming standard. A few years ago, containers were considered cutting edge modern technology that modern teams were using, but right now they are expected. So companies need people who can manage containerized applications at scale. So those specific skills are becoming extremely highly demanded right now. Third factor is that cyber security is exploding and security is moving left. We are seeing these massive data breaches almost weekly and with the explosion of AI, cyber security is becoming more and more relevant and important for companies and companies are under intense pressure from regulations from customers from their boards to secure their infrastructure and applications. So the old model of build it first and secure it later is dead. They need to integrate security from the very start. But also security needs to be built into every step of the development and deployment process. That's what we mean by shifting left which is integrating security earlier in the pipeline but also in every single step not as an afterthought at the end after everything is already configured and done. So dev sec ops specifically is becoming mandatory not optional anymore and this is creating huge demand for DevOps engineers who understand security. Fourth infrastructure as code is becoming the norm. Manual infrastructure configuration that we've been doing for years or decades is disappearing. Companies need engineers who can write infrastructure as code, version it, test it, deploy it automatically and manage this entire configuration and setup. So this specific skill of DevOps engineering is becoming highly demanded at a very high speed. And fifth and this one is huge actually. AI is fundamentally changing the tech landscape and it's really important to understand how exactly it's changing it and what impact it has because AI is affecting DevOps specifically in two critical ways and you need to understand what that effect is. So let me explain what I mean because this is where things get really interesting. So on one hand AI is automating basic coding tasks right you can ask JGP to write a function and it does it you can use GitHub copilot to complete your code and so on. So junior level coding tasks are being automated by AI rapidly. This means that the value of basic coding skills is decreasing. What took a junior developer days to do can now be done in minutes with AI assistance. But here is what AI cannot do well. architecture decisions, system design, infrastructure planning, understanding how all pieces of your system fit together, knowing when to use which tool and why, troubleshooting complex distributed systems. So these are architect level skills and DevOps is fundamentally an architect role. You're not just writing code. You are designing CI/CD pipelines. You are architecting cloud infrastructure. You are making decisions about security, scalability, reliability. You are connecting development and operations. You are solving problems that require deep understanding of the entire system, not just one specific part of it. So AI can help you work faster but it cannot replace the strategic thinking and system level understanding that DevOps engineers bring to the table. So while AI is reducing the value of basic coding skills, it's actually increasing the value of DevOps skills. Here's the second way AI is changing everything for DevOps. And this is the part most people miss or don't even realize. AI and machine learning projects themselves need DevOps skills. So let me explain what that means. Think about it. Building a machine learning model is just the beginning. That model needs to be deployed, monitored, updated, scaled just like any other application. But actually it's more complex because machine learning models need data pipelines, model versioning, AB testing infrastructure, continuous retraining

systems and all of this requires DevOps expertise and this is why MLOps which essentially is DevOps but applied to machine learning is exploding right now. So MLOps is basically 80% DevOps plus some machine learning specific knowledge. So every company who is building AI features now or is building an AI platform or tool needs engineers who can automate model deployment, manage training infrastructure, ensure models run reliably in production which are skills of DevOps engineering. So this means that the impact of AI on DevOps demand is actually twofold. First, AI is making DevOps skills more valuable by automating basic coding while leaving architect level work untouched. And second, AI projects themselves are creating massive demand for DevOps skills. Every new AI initiative requires DevOps infrastructure. So, it's not just one trend driving demand. It's two powerful trends converging at the same time. And companies that were hesitant about DevOps are now allin because of that. budgets are being allocated, teams are being built, job openings are being posted, but qualified people with these skills is still extremely scarce and rare. And this is why I'm telling you, if you are thinking about this career path, start now, not next year or in two years. Start now and you're going to have a much easier entry point into this field. Now, let me tell you one important point about why companies are struggling so much to find people with DevOps skills. It's not because DevOps is impossibly hard. It's because DevOps requires a specific combination of skills that most people don't have. Traditional developers, for example, they know coding but not infrastructure. Traditional system administrators know infrastructure but not modern development practices and devops sits right in the middle. You need to understand a combination of multiple things because as I said this is an architect role which naturally means that you need to have a complete overview of everything of the entire IT systems and then be able to zoom in into any area of that system and that's also what makes it so incredibly valuable. So this is a list of things you need to understand if you want to be that highly valuable skilled DevOps engineer. First of all, how applications are built and deployed, which is the software development side. You also need to understand how infrastructure works and scales, which is the cloud infrastructure side, but also working with servers, networking and so on. On top of that, and this is probably one of the most important skills of a DevOps engineer, is how to automate everything. Automating infrastructure provisioning and configuration, automating application deployment, testing, automating everything possible to remove bottlenecks from the systems. And as I mentioned before, another critical thing is how to implement security in all parts of the systems. And finally, how to monitor and troubleshoot those systems. And as you say, it is a broad skill set. And most people coming from either development or operations side do not have the full picture. They're always missing important parts of the knowledge which creates a skill gap. And that's why positions stay open for so long. There are system administrators that try to get into DevOps. They're software engineers that try to upskill themselves to become DevOps engineers or to take on DevOps tasks. But to be a really skilled, well-rounded DevOps engineer, you need to have knowledge of the entire system. You need to have much broader knowledge, which is exactly what's missing today on the market. But here's the [snorts] opportunity. Once you have this combination of skills, you become incredibly valuable because you can speak both languages. You can work with developers and understand their needs. operations and understand their constraints. You can bridge the gap and deliver extremely high value for your team and the company overall. And companies are paying really high salaries for this. And it's not just about money. These roles often come with flexibility, remote work options, interesting technical challenges, higher respect and status for the role. Of course, because companies need DevOps skills, they're not hiring DevOps as a nice to have. They are hiring because their entire business depends on reliable, scalable, secure infrastructure and processes. When your company's application goes down, when deployments fail, when security gets

breached, that's when you realize how critical DevOps is. And companies understand this. Now, that's why they're desperate to find people with these skills. Now, before we continue, I want to give a quick shout out to Control Plane, who is the sponsor of this video. I just explained how companies need engineers who can handle cloud infrastructure. But the reality is that many enterprises are not running on just AWS or just Azure. They're running multi cloud environments plus on premise infrastructure all at the same time. And managing all of this, the different cloud providers, the on-remise systems, the security policies, the compliance requirements across everything, it's incredibly complex. And control plane is the platform that makes it much easier because they provide a unified single platform where you can deploy secure manage your entire infrastructure from one central place. So your workloads run agnostically with 99. 999% availability and extremely low latency out of the box. And the impact is real. We're talking about 60 to 80% cloud cost reduction. So, if you want to understand more, make sure to check out controlplane. com for a 30-day free trial and see for yourself how they are simplifying multicloud infrastructure management. And now, let's continue with the video. Now, here's the good news for you. You don't need years to become job ready in DevOps. You need six to nine months of dedicated learning. That's it. But not for just junior entrylevel job. We've prepared hundreds of people within this time frame for mid-level to senior DevOps engineer positions. And that's actually a really short time frame for something so valuable. But only if done right. And that's the key here, if done right. Because you can be learning for a whole year or multiple years without structure and just piecing together different resources and still struggle to even get an entry-level DevOps position or to feel confident about basic DevOps skills because your knowledge is scattered and all over the place with tons of missing pieces. So that's why how you learn and what structure you follow is so important. So let me give you that structure and road map so you don't waste month or years in learning. Let's start with the road map of what to actually learn. And honestly, if you looked at DevOps road maps online, like including our DevOps road map, you probably already have a general idea of what you need to learn. But let me quickly show you what consistently appears in actual job descriptions. For example, look at this job posting for a DevOps engineering position with a pretty high salary. What do they need? CI/CD knowledge, which is designing, developing, maintaining CI/CD pipelines. Infrastructure is code using tools like Terraform. Developing automation scripts and tools to streamline operations that's Python and bash scripting. experience with Linux, knowledge of Git, Docker, Terraform, and one of the major cloud platforms that's usually AWS or Azure, familiarity with Kubernetes, so container orchestration, and experience with monitoring and logging tools, which is Prometheus, Graphana, and so on. Or here's another one. See, that's an AI company, AI platform for human intelligence. And you see same pattern. Your key responsibilities are design, implement, maintain CI/CD pipelines using tools like Jenkins, GitHub actions, Terraform, build, deploy and manage containerized applications with Docker and Kubernetes in cloud native environments AWS GCP automating infrastructure provisioning configuration and monitoring to support continuous delivery. That's Terraform, Enzible, Prometheus and so on. So same skills, CI/CD pipelines, containers, Kubernetes, infrastructures, code, cloud monitoring. These skills pop up again and again in job descriptions consistently. And if this sounds familiar, yes, those tools are exactly what we cover in our DevOps boot camp that you will learn how to combine and build real DevOps processes with the same skill that you will actually need at an actual job. This means here is your road map to learning these skills. First of all, start with fundamentals with Linux and networking. Then move on to git and bash scripting. After that

move to docker. Once you've learned about docker and containers, then get into the I call this a backbone of DevOps, which is CI/CD. So pick one of Jenkins, GitLab, GitHub actions to learn how to build CI/CD pipelines and this is core of DevOps. This is the absolute requirement. So do not watch Kubernetes tutorials or do a Terraform course if you don't know these fundamental skills properly yet. Remember I mentioned structured learning. The order of what you learn in which sequence matters a lot here. It's like building a house. First you lay the foundation and then you build on top of it one by one. You can't start building a house from a fifth floor. So watching a Kubernetes tutorial when you don't have Linux skills, when you don't know Git, Docker or you haven't ever built a CI/CD pipeline is like starting to build a house from a fifth floor directly. It just doesn't work right. there is nothing to tie that knowledge or build that knowledge on top of. So invest as much time as possible to get the foundational knowledge right first. So once you have that then you move on to learning one major cloud platform. AWS is a great choice because it's by far the most widely used one but it doesn't really matter because the underlying concepts of any cloud platforms is essentially the same. And always remember you need to learn these skills in combination with each other. So just learning cloud and having absolutely no reference of how to integrate CI/CD pipeline to deploy to the cloud environment that is exactly what leaves you with skill gaps because you don't know how to combine these technologies and platforms together. So once you have added cloud knowledge to your existing fundamental foundational skill set then you move into Kubernetes and you build Kubernetes knowledge on top of everything that you've learned before. After Kubernetes as a next step learn infrastructure as code with Terraform and last but not least understand how to monitor and troubleshoot production systems which is monitoring stack like Prometheus, Grafana, ELK stack and so on. And as I mentioned there are two most important things in a road map and how you learn things. First one is a sequence. You start with a foundation then you build the first floor then the second floor and so on. You don't start at floor five which a lot of people are doing. Learning new skills without having an actual foundation underneath. So that's one. The second one is probably even more important is learning each skill on top of the other. So you don't build a first floor here of this house and then go to another house and build a second floor there. You are stacking your skills on top of each other instead of learning them completely in isolation. So you don't just learn Kubernetes exists in its own bubble but you learn Kubernetes in the context of cloud platform like how do you create a Kubernetes cluster on AWS then how do you integrate CI/CD pipeline to Kubernetes cluster how do you automate provisioning and configuring cluster on a cloud infrastructure with Terraform and so on. So you integrate and mix these tools together to build end-to-end processes. And this is exactly the order that makes sense. And learning this entire DevOps skill set in this sequence with a proper depth would take you 6 to 9 months part-time if done with structure and dedication. But the reality is for people to learn for years making only very little progress because they are learning in the wrong way. Why or how do I know? I see this over and over again with our students. When I ask them about their previous DevOps learning experience before they finally decided to take our trainings, almost without exception, they all tell me about the same mistakes that held them back for months, sometimes years. And the biggest one is learning each tool separately without building proper production grade complex projects hands-on like we do in our program. And you can even see some of these conversations in this career playlist where I personally sat down with our graduates and talked about their real DevOps journey including the detours, the struggles during learning, what they tried, what they didn't work for them, what worked for them, and how they eventually got to their goal, not just the happy path. So you can identify some of the mistakes that you are doing now. Okay. So you have a road map now that tells you what to learn and you probably seen DevOps road maps including ours. So this should not be the big news for you. But here is what a road map does not tell you and this is critical. How much

do you need to learn of each technology and how do you combine them? And this is exactly where most people get overwhelmed even when they have a road map and a structure. That's where they get stuck. They see learn Kubernetes on a road map and think okay I'll start learning Kubernetes but Kubernetes is massive. Do you need to know everything? Do you learn CRDs? Do you learn Helm? Do you learn EKS? When do you stop or where do you draw the line? So the road map leaves you overwhelmed. You don't know the depth required. You don't know how to connect Docker knowledge with Kubernetes knowledge with CI/CD knowledge or infrastructure as code tools in a practical way. And that's why I want to share with you the most common learning mistakes that I see over and over again which you should avoid at all costs if you want to become highly skilled DevOps engineer without wasting years. Mistake number one isolated course help. That's what I call it. People take a Docker course, then a Kubernetes course, then a Terraform course, but they learn each technology in isolation. They never understand how these tools connect or fit into end-to-end DevOps processes. So, you end up with fragmented knowledge. You know, individual tools, but you cannot build complete solutions from them. And this obviously leaves you feeling like an imposer because you don't understand how everything fits together. Mistake number two is surface level learning and sandbox environments. And I hear this constantly from our students. They copy pasted code without understanding the why behind each tool or they only worked in playground environments where everything is already configured for you. Here is what happens in this scenario. You feel great during the course. Everything works. You get your achievement confettes and feel good about your progress. But then you start a job, a real one, and you need to build real infrastructure from scratch and you're completely lost because you've never done it before. You have been learning in sandbox playground environment without building things from scratch yourself. And in our DevOps boot camp, we flip this around. Learning is not always comfortable because you're working with real environments, troubleshooting real issues, building from scratch. But when you start your job, you feel confident because you already have practice of doing this stuff in the training itself. So you are challenged during learning so that it can feel easier during the actual job. Because what would you rather have feeling good while learning but being completely lost on the job or the other way around? Being challenged while learning so that you can feel effortlessly good once you start the actual job. The next mistake is not understanding time and opportunity cost versus money. Because you always pay a price, either with your time and frustration or with your money. People try to piece together their education with free resources or cheap $50 courses. They spend years jumping from course to course, still feeling insecure. They think that they're saving money, but they're paying with years of their time. And here's something to consider the opportunity cost. Let's say if you spend 3 years trying to learn DevOps instead of 6 months, that's not just 3 years of your time wasted. That's 3 years of not earning high salary. Let's say very conservatively, you could be earning $2,000 more per month with if you had those highly demanded DevOps skills, which is 24,000 a year. And over three years, that's 72K in lost income that you could have had if you learned those skills. So that cheap $50 course suddenly became very expensive because of what it's costing you now. And I think it just becomes clear when you see it from this perspective. The next mistake is learning in silence. People think that just learning is enough. They study quietly, build projects locally, then sit back hoping that great jobs will just appear. It doesn't always work that way. Our students who have the most success share their learning on LinkedIn. They share what they're learning and building. They engage with the community and recruiters start lending in their inbox daily. But here's what's interesting. They don't even do anything crazy here. They simply do the basics. They fill out their LinkedIn profile. They link to the projects that they have built during the boot camp. They link to our DevOps certification that they get at the end of the boot camp. They just add the skills that they learned in their profile description and

maybe make a post or two celebrating that they successfully completed the program and earned the digital certificate that we issue. That's really it. That's all the work that they do. That's all it takes. And suddenly they come up in search results when recruiters are looking for DevOps engineers or people see their posts and what they have been learning and that's how most of them have landed multiple attractive job offers not just one. So you don't need thousands of followers or daily posting you just need to be visible so that people can find you and discover you when they search for DevOps engineers. Now the good news is that all these mistakes that I just mentioned are very easily avoidable. Structure your learning. Invest your time and money wisely. Calculating the opportunity cost. Practice building instead of just passively learning and document your knowledge. That's how you go from beginner to being job ready and confident in your skills in six to nine months instead of struggling for years. And look, if you want a structured path where these mistakes are already eliminated, where you get community support, that's exactly why we created our devos boot camp. But honestly, I'm happy if you can piece this together yourself with free resources and with all the advice that I gave you in this video and achieve the same result yourself. I will be equally happy with that. So, whatever path you decide to follow, if I can give you one main takeaway from all this is to actually build things when learning. Don't just watch tutorials passively absorbing the knowledge. build actual projects that combine these skills. That's where the learning happens. The bottom line is the world needs a lot of skilled DevOps engineers. Now, the industry literally needs you and incredibly high demand is out there. Now, it's literally on you how you can take advantage of that. Now, let me leave you with this. 10 years ago, people who learned software engineering early had incredible opportunities. They got in before the market was saturated. They built careers. They grew with industry. And many of them are now senior engineers, tech leads, and even running their own companies. That same opportunity exists now in DevOps. But unlike 10 years ago, everything moves faster now. AI is accelerating the pace of any development. So the window of opportunity will close faster this time. You probably have maybe few years of this golden period where demand vastly exceeds supply. So the question is are you going to take advantage of it or wait and watch the window close because you're waiting for the perfect moment? Because if you're serious about it, start today. Check out job descriptions in your market. Start with Linux fundamentals. Build actual projects. follow a structured path, whether it's through our free resources or boot camp or your own research. But this time next year, you could be working as a confident DevOps engineer, earning a good salary, working on interesting technical problems and building a career in one of the most in demand fields in tech today. Or one year from now, you could still be thinking about it while the opportunity passes by. The choice is obviously yours. I hope I was able to motivate you, inspire you to take action, whatever your next step is going to be, to take this opportunity. Thank you for watching and I'll see you in the next video.