Your DevOps learning roadmap is broken! - Career

⚠️ Update ⚠️
If you are looking for the solution for this dilemma, then check this out: How to become a DevOps Engineer in 2024 with the Dynamic DevOps Roadmap.

Can you read it? Probably not, it's already broken!

As of 2023, the DevOps Engineer role remains one of the top 10 most in-demand jobs across all industries (not just the tech field!) And that was the case for the last 5 years at least and is expected to continue for the foreseeable future.

While DevOps is a hot topic all the time, it's in particular hard to start DevOps engineer as your first job. Many engineers believe that it's not possible at all to begin as a DevOps professional without first working as a developer or in operations (I totally disagree with that!).

Almost every day, I see people struggling on their way to start as fresh/junior DevOps engineers. They usually follow some roadmap (typically roadmap.sh/devops). But still, they cannot land their first job, and sadly, many of them eventually give up!

This blog post explains why most of roadmaps don't work for DevOps roles and won't help you start your first job as a DevOps engineer. Also, the post discusses the best way to start in a DevOps role without prior work experience. While it might not work for everyone, I can say that it has been successful with all the people I have mentored in the last couple of years.



In 2023 starting a DevOps engineer role is challenging because the DevOps model has various implementations and patterns. It's even more complicated (but still possible) if that's your first job without previous software industry experience. Yet, many learning roadmaps like roadmap.sh/devops still follow a linear path (i.e., learn some topic to the end, then move to another, and so on) which doesn't work well with the DevOps role because a skilled DevOps engineer is a T-Shaped skilled. Adopting a dynamic MVP learning roadmap increases your chances of entering the market and starting your first job as a DevOps engineer without previous software hands-on experience.

DevOps Topologies

First, let's start with the DevOps model itself. Being a high-level methodology that can be implemented in various ways makes it super challenging. Hence, the DevOps engineer role has no unified definition or standard requirements.

I will not delve into the cliché DevOps is not a role, it is a culture (because in reality, it doesn't work like that! DevOps is not just a culture, and it is also a role), but here I want to emphasize that not all DevOps engineers are the same!

Here I want to mention "DevOps Topologies" which covers different team structures that implement DevOps. It shows many bad and good DevOps patterns.

Given that no one-size-fits-all team topology works for every organization, it's wrong to say it's not possible to start your career as a DevOps engineer. But there are situations where it's extremely challenging to do so, such as being the sole DevOps engineer in a team or even in a company.

So, what can you do to increase your chances of landing your first job as a DevOps engineer? You should have T-shaped skills and leave no stone unturned in your learning journey!

T-Shaped Skills

The "T-Shaped skills" helps DevOps engineers to efficivtly handle various challanges.

The T-shaped skills refer to combining broad and deep skills in a specific field. The horizontal bar of the "T" represents a broad range of general knowledge and skills across different disciplines or areas, and the vertical stem of the "T" represents deep expertise in a specific area. It's simply a mix between being a specialist and generalist at the same time!

The T-shaped skills will help you to work in companies with different DevOps patterns. You can easily transition between different areas in the DevOps spectrum. Not only that but also it will help you to handle new challenges effectively. In fact, the best DevOps engineers I have come across possessed T-shaped skills.

Does it mean there's no I-shaped DevOps engineer who specializes in certain areas and no little knowledge in other areas? I would say it's possible, but it may limit the available opportunities and companies you can work with.

Actually, as you progress in your career, it's better to develop more specialization (i.e., more vertical stems), and after a couple of years in the industry, your next step should be Pi-Shaped skills (search also for M-Shaped and Comb-Shaped skills, but it's a topic for another post).

To summarize this section, you should aim to gain exposure to various areas of DevOps practices and technologies without delving too deep into each one, yet, you need to dive in-depth into some of them (according to the market or organizations your target). And due to that, your roadmap shouldn't be linear but follow the MVP-style approach!

MVP Learning Roadmap

You probably heard before about the "Minimum Viable Product" or MVP, a basic version of a product with enough features to satisfy early users and gather feedback for further development, which's commonly associated with Agile methodologies. Interestingly, this approach can also be applied to learning roadmaps too!

Over the years, I saw people want to start their career as DevOps but completely lost! That's probably because they try to progress in a linear fashion. Typically they will follow some roadmap like roadmap.sh/devops and start learning the topics one by one top down. I.e., they spend a couple of weeks with Linux, then a month learning programming language, then some time with the containers, and more time with Kubernetes. And several months passed, and they found themselves stuck in the middle of the roadmap but still unable to get any job because many topics were untouched!

The truth is that the linear vertical learning path DOES NOT WORK in the DevOps field! You need to follow an MVP-style learning roadmap where you learn in iterations and touch multiple parts at the same time (not necessarily equally). Each iteration should focus on a primary topic while exploring related side topics. So after a month, you already know about each topic in the roadmap, and after the 2nd month, you have the basics, and after the 3rd month, you have a good base, and so on.

By adopting an MVP-style learning roadmap, you can ensure that you cover various aspects of DevOps while continuously building upon your knowledge. This approach allows for a more well-rounded understanding and a better chance of landing your first job as a DevOps engineer.

3 different high-level roadmaps models with different approaches to learning, the first two from the left follow the MVP-style, and the last one is linear.

  • The model on the left iterates horizontally in equal chunks over each area (good). It's simple and straightforward, each area (e.g., OS and code, containers and cloud, etc) has a fixed weight based on importance in the daily work. You don't need to think a lot about the next step, from the left to the right, you learn about each area and reach basic knowledge in all of them.

  • The model in the center iterates horizontally in dynamic chunks over each area (better). It's the same as the previous one but a bit more advanced, where it needs hands-on knowledge to decide the right weight for each area (based on many factors like targeted market or learner skills or background). This approach is more efficient; however, it requires guidance from an experienced DevOps engineer (e.g., a mentor or career coach) to define the weights correctly. It's even more critical when you have some sort of constraints like time or so (they are usually there in career shifts).

  • The model on the right iterates vertically over each area (bad). Don't do that! It has several drawbacks. For example, it delays your market fit, where in most cases, you cannot work as a DevOps engineer until you have completed all areas. Additionally, there is no space to review your learning approaches or holistic feedback in general. Finally, it's missing the connection between different areas, at the end of the day at work, you don't use a single skill at a time. I actually saw many disappointed people in the middle of the roadmap because they still didn't get the full picture.

So to ensure a more effective learning journey, it's recommended to adopt an MVP-style learning roadmap that allows for iterative learning across multiple areas while also considering the relevance and importance of each area in real-world DevOps work.

The Solution!

⭐ Check out the Dynamic Roadmap content ⭐

A dynamic MVP-style learning roadmap is one of the best ways to start as a DevOps engineer.

Let's put everything together. The Based on my experience mentoring people in different stages (starting their first job, career shift, moving to another work style or company), I have found that the approach of using a dynamic MVP-style roadmap with hands-on projects designed by an experienced DevOps engineer has been highly successful. That means each project will cover all DevOps areas used in the job. It's also essential to understand the targeted market and organizations because, with different DevOps topologies, the DevOps engineer role requirements vary.

In conclusion, to start working DevOps engineer, you don't need to know "everything" about the software development life cycle (SDLC), nor start as Dev or Ops and then switch to DevOps. In many DevOps topologies, you can secure your first job as a DevOps engineer if you invest enough time in learning (not only the technical aspects) and follow an MVP-style roadmap. Also, undoubtedly having a senior DevOps on both ends (during the learning and in the company where you apply) will make your start much easier.

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Hello, my name is Ahmed AbouZaid, I'm a passionate Tech Lead DevOps Engineer. 👋

With 16+ years of open-source contributions, 12+ years of professional hands-on experience in DevOps, and an M.Sc. in Data Engineering from Edinburgh Napier University (UK), I enjoy facilitating the growth of both businesses and individuals.

I specialize in Cloud-Native and Kubernetes. I'm also a Free/Open source geek and book author. My favorite topics are DevOps transformation, automation, data, and metrics.

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