How to become a DevOps engineer – 5 easy steps
Do you want to become a DevOps engineer? Maybe you’re a beginner trying to break into tech and unsure how to proceed. Or perhaps you’re trying to scale up for a new job in the DevOps field, but you’re facing some difficulties.
How to become a DevOps engineer? What technologies are required to become a DevOps engineer? How long does it take to become a DevOps engineer?
If you relate to these questions, you aren’t alone! Charting a new path for yourself can feel overwhelming without a guide. Luckily, the process isn’t as complicated as it seems and all of these questions have already been answered for you.
Find out how to become a DevOps engineer in the article below.
To become a DevOps engineer, you should:
• Learn the basics of computer Science (Client-server architecture, Linux, Networking, Programming);
• Master major DevOps tools (Cloud, Automation, Containers, Monitoring, CICD);
• Build several hands-on projects;
• Pass one or more certification exams;
With the right resources and right commitment, it’s realistic to become a DevOps engineer in less than 6 months. And with the help of an experienced DevOps practitioner, this timeframe can be even shorter.
Read a real-life example in our most recent case study here: From Biologist to DevOps Engineer in record Time
Stick with us as we break down the topic in more detail.
Step 1 – Learn the basics
Client-server and 3-tier architecture
All of DevOps is focused on running multi-tier architectures. As an aspiring DevOps engineer, start by understanding architecture systems.
Client-server architecture is an architecture system with one or more clients and the server that responds to their requests. A client is any device that accesses and uses services. Servers are separate hardware/software that provides functions to clients. All of the parts of the system are independent and communicate over a network.
Multitier architecture is a client-server architecture system that separates data processing and application function systems. With separate systems, you can easily manipulate applications, whether for scaling, replication in another format, modular edits, or additional layers or tiers.
Multi-tier architectures are split into several layers, although most commonly there are 3 of them. We call these patterns 3-tier architectures.
The most notable feature of the 3-tier architecture is the independence of the layers. You can make changes to one tier without affecting the rest of the system. A typical 3-tier infrastructure looks like this:
Below the frontend is the application tier, also referred to as the backend. Primarily, this layer communicates information. Think of the backend as the middleman—it processes and stores the data received from the frontend and also extracts results from the layer below it, the data layer.
The data tier is the bottommost tier of the architecture. This is where all of the data is stored and retrieved. Any major data management tasks such as backups and high availability take place here, as well the data storage itself.
Understanding multilevel systems are essential for DevOps work because all modern systems (such as Netflix, Amazon, and Twitter) are multilevel. This means DevOps engineers work with these concepts every day.
First, what is Linux? Linux is a family of open-source operating systems, all based on something that we call the Linux kernel, which is the lowest level of the system. You interact with Linux every day — it runs on everything from routers and smart home devices to automobiles and gaming consoles. Many of the most popular names in technology — Android, Chromebook, Tesla, and others — run on a Linux Kernel. Websites and servers also run Linux. This makes it essential learning for a DevOps engineer.
A DevOps engineer should be comfortable with Linux. While you don’t need to be able to do something as technically complicated as recompiling a kernel, you do at least need a general understanding of Linux. You should be capable of doing the following tasks:
Connecting to a server using SSH. SSH, or Secure Shell, is a Linux-based protocol for connecting securely to a remote computer. This allows you to manipulate that remote computer from your own local device. For example, you can use SSH to connect to a client’s server and help them solve a technical issue.
Manipulating files and directories. Many of the most basic Linux commands involve files and directories. It’s helpful to know commands like “copy”, “remove”, and “create directory”.
Managing services. Services (we also call these daemons) are applications that run constantly in the background from the moment a device is turned on. Each service controls software. Starting, stopping, and status-checking are important basics of service management for a DevOps engineer.
Installing additional software using a package manager. Simply put, a package is a program that you install on a server. The package manager tells you what software you have on your device. Here, you can execute actions like installing, upgrading or removing software.
Check out these helpful Linux books below(clickable). Pick one, go through it (maybe with a cup of strong coffee by your side), and you will be ready from the Linux standpoint.
All Linux servers that DevOps engineers maintain are distributed across the globe and interconnected via Transmission Control Protocol (TCP) networks. Networking using the TCP is an essential theoretical concept to DevOps work. Think of Networking as a massive system of communication and information sharing.
Similarly to Linux, you don’t need to be a Networking expert, but you do need some general understanding of key concepts.
In particular, you need to understand the layers of the Open Systems Interconnection (OSI) model, how they are translated into the TCP/IP model, understand how routing works, and be capable of doing some basic networking troubleshooting. It sounds like a lot (and it is!), so let’s break it down into smaller pieces.
Firstly, what is the OSI model? The OSI model was the first almost universally-adopted standardized model for network communication. It contains seven layers that describe how computers communicate across networks. Today, the TCP/IP model is a much simpler model based on the OSI model. But if you can understand the seven layers of the OSI model, you’ll be in perfect shape to understand and work within the TCP/IP model.
From the bottom up (least to most human-computer interaction), the seven OSI layers are:
- Physical Layer: The physical cable or wireless connection itself. It converts raw data into electrical, radio, or optical signals between the connected devices.
- Data Link Layer: Transfers data from one host to another on the same network.
- Network Layer: Transfers data from one host to another across different networks.
- Transport Layer: Acknowledges successful data transmission and retransmits data if the transmission failed.
- Session Layer: Builds, manages, and terminates connections between hosts.
- Presentation Layer: Manages processes, such as data encoding, encryption, and compression.
- Application Layer: The final, uppermost layer with direct human-computer interaction. You interact with this everyday. For example, http, email, and DNS are all application-layer protocols.
Key concepts in the TCP/IP model
The TCP/IP model is a reliable set of connection-based end-to-end Internet Protocols (IP) that connects applications in a network and facilitates data exchange between them. A protocol defines how data is passed between computers.
The TCP/IP model simply combines OSI layers 5, 6, and 7 into one Application Layer and OSI layers 1 and 2 into a single Network Access Layer.
Routing. Clients need a way to identify the type of information being conveyed when they send requests. Ports help with this: unique numbers that identify both the host and the service in a transaction.
Each set of information being passed over a network is called a packet. The goal is to build a path that gets the packet to its destination as efficiently and securely as possible. We call each segment on the path a route. There are five types of routes that can be used. When routing, you create a routing table that shows all of the routes a packet will follow.
There are two types of routing in the TCP/IP model: static and dynamic. In Static routing, you manually maintain the routing table. This is good when you only need to communicate between a few networks. The more networks you add, though, the more challenging it is to manually keep track of everything. In this case, you’d use dynamic routing, where the routing table gets automatically updated.
Networks can be massive though—much more so than you may need for your task. In this case, you can subnet by splitting one network into smaller networks.
IP addresses and subnetting. You’ve probably heard of an IP address – the unique number that identifies a device on a network. An IP address has two parts: the client/host address and the network address. You should know how to calculate a subnet mask, which separates the client and network addresses. It also determines the number of IP addresses that can be used in one subnetwork.
Basic TCP/IP troubleshooting. As we all know, technology doesn’t always cooperate. As a DevOps engineer, you should know how to resolve common problems in a TCP/IP network. Take the time to study where common problems occur, how to find what type of problem is occurring, and how to resolve them. You should be fluent with tools like ping, traceroute, dig, netstat, nmap, and tcpdump.
Servers connected via the internet don’t produce value on their own; what makes them valuable are the actual programs, or software, that run on the server. And where there is a program, there must be a DevOps engineer behind it (that’s you!) that understands how to maintain the system as a whole.
If coding sounds intimidating, you’ll be happy to know that DevOps engineers aren’t full-time coders. However, successful engineers benefit from understanding the code they’re maintaining.
There are multiple programming languages, but if you can pick only one, go with Python. It’s powerful, yet easy, and doesn’t require a lot of heavy lifting to get started.
In Python or any other programming language, you’ll need an understanding of general concepts. Check out some coding vocabulary below:
A variable is a reserved memory location that stores all of the values assigned to it. Values can be any type of data from numerics to words and lists of objects.
A loop provides information about the order of a series of consecutive instructions and the number of times they will be repeated. This is helpful when you want to execute a block of code several times in a row.
Conditions are commands that set the rules for making decisions in code. The decision to take one action or another depends on whether the defined condition evaluates as true or false. If-then-else is a common construction for conditional statements. Essentially, IF the code evaluates one way, THEN X action will be taken. ELSE Y action happens.
A function is a type of subroutine (set of organized codes that perform a task) that returns a value. Common built-in functions include things like print(), but you can also define your own.
Step 2 – Learn DevOps tools
Gone are the days of reliance on physical on-site servers. Instead, the cloud – the global network of remote server internet-based computing—has taken its place. There are a number of major cloud platforms used by most companies. These include Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Each offers its own set of services managed by its respective provider at large global data centers. DevOps engineers are masters of the craft of managing applications in the cloud.
One of the major benefits of cloud computing is that you never need to physically touch hardware. Instead, there are programming interfaces for every action. This opens up opportunities for automation. Effective DevOps teams are able to manage tens of thousands of virtual cloud servers with the help of modern automation tools.
One example of automation in action is Infrastructure as Code (IaC). As its name implies, IaC codifies the management of IT infrastructures, which allows for a lot more flexibility (and automation) than manual processes. As with the cloud, there are a number of tools to choose from, but we recommend Terraform for automation projects—it’s an open-source tool that facilitates IaC.
Terraform’s code is in the HashiCorp Configuration Language (HCL). You can write the code in blocks, arguments, and expressions and then execute a terraform plan to test the execution of your code. You can then use terraform to apply the changes across cloud providers.
As soon as you have your servers provisioned, you need to install software, download updates, and tweak some OS-level parameters. Here is where another important aspect is called Configuration Management comes into play. The brightest example of a configuration management tool is Ansible.
Knowing containers is now an industry-standard in DevOps. But what are they? Containers are single package units of software containing all of the necessary code and elements. They can be run anywhere, just like a cloud. DevOps engineers will benefit from understanding and learning, containers. The two biggest players in this field are Kubernetes and Docker.
Kubernetes is an open-source system that helps engineers automize the deployment, management, and scaling of containers. Using Kubernetes, you can cluster together hosts that run containers and efficiently manage them, troubleshoot, and scale. Docker is like Kubernetes, but it only runs individual containers.
As a DevOps engineer, much of your work is dedicated to maintaining smoothly operating systems for your team that are intuitive, efficient, and working correctly. All of these tasks add up, which is why you’ll want a good way to monitor everything, collect metrics, and intervene to fix issues. There are tools to help you with this! These include monitoring technologies like Prometheus, Grafana, and ELK.
Developers need to be able to deliver code into environments—whether that be testing new functionality or delivering an update across the system. Ci\Cd, which stands for the combined Continuous Integration and Continuous Delivery]Deployment, automates the process. You will want to know how a Ci\Cd pipeline works—the series of steps for executing Ci\Cd.
A typical pipeline process involves a Ci server such as Jenkins pulling code from GitHub or any other version control system, building artifacts, testing them, and then deploying.
Step 3 – Build a hands-on project
Once you are comfortable with the theoretical concepts and technical basics of DevOps engineering, it’s time to get your hands dirty and build some real projects. The best way for you to master DevOps tools—and show others your expertise—is by practicing. This will give you confidence in your skills and demonstrate your capabilities to potential employers.
Start with something simple, like building the infrastructure to run a website. This will include a virtual network, several load-balanced web servers, and a database.
After you practice basic skills, you can raise the bar. Now try hosting that same website using Kubernetes. That task itself can be revised, upgraded, and built upon infinitely.
Depending on your priorities and goals, you can complicate your project further by adding features mentioned previously such as monitoring and log management, Ci/Cd, or improving security aspects. The possibilities are endless. In this way, all of the DevOps skills outlined above build on each other to give you a well-rounded and increasingly technical understanding of DevOps.
Every project that you build should be automated using tools such as Terraform and code uploaded to GitHub. This will make the project reusable, much easier to troubleshoot, and most importantly, you will use it as a portfolio to show to your potential employers. Having an actual project built from scratch sets you up for success. It shows future employers that you have the skills for their job and are ready to jump right into the work.
Step 4 – Get certified
It is important not only to learn theory but to get certified. Certifications give you credibility in your field by formally asserting your expertise in a topic. Because certifications are standardized with a certain level of expected rigor, they are trustworthy badges of ability. A certification on your resume instantly professionalizes you in your field.
In most cases, getting a certification requires taking an exam.
AWS Certified Cloud Practitioner
The AWS Certified Cloud Practitioner exam shows your overall knowledge of the AWS cloud system. It covers four main domains: cloud concepts, security and compliance, technology, billing, and pricing. This is a great way to demonstrate a conceptual understanding of the AWS cloud without requiring you to do any highly technical tasks like coding, designing infrastructure, or troubleshooting. Expect to answer 50 multiple choice/multiple response questions in 90 minutes.
AWS Certified Solutions Architect Associate
This exam is usually the next step in any AWS Certification journey. An AWS Solution architect evaluates a business’s needs and creates or integrates cloud systems to meet that need. An AWS Certified Solutions Architect Associate confirms your ability to perform the solutions architect role on AWS. You’ll want to have some experience designing and implementing solution systems on AWS before you take this exam. The four domains you will be tested on are designing resilient architectures, designing high-performance architectures, designing secure applications and architectures, and designing cost-optimized architectures. It’s significantly harder than the AWS Cloud Practitioner test, but it’s much more valued by the community. You’ll respond to 65 multiple choice/multiple response questions in 120 minutes.
Red Hat Certified System Administrator
The Red Hat Certified Systems Administrator test validates your core Linux administration skills. This is a three-hour-long hands-on exam that asks you to do real-world Linux tasks that a DevOps engineer would do in their workplace.
This exam will test your ability to: understand and use essential tools; create simple shell scripts; operate running systems; configure local storage; create and configure file systems; deploy, configure, and maintain systems; and manage basic networking, users, groups, security, and containers.
Kubernetes exams – KCNA, CKA, CKAD
Kubernetes and Cloud Native Associate (KCNA)
The KCNA exam tests both your knowledge and skills in Kubernetes and in cloud-native ecosystems as a whole. If you want to work in cloud-native technologies, you’ll find this certification extremely helpful. You will be tested on deploying applications using kubectl commands, Kubernetes architecture, the cloud-native landscape and projects, and principles of cloud-native security. This is a 90-minute online multiple-choice exam and the only Kubernetes exam that is theoretical.
Certified Kubernetes Administrator (CKA)
A CKA can do the basic installation, operation, configuration, and management of Kubernetes-based systems. The CKA certification gives employers official confirmation of this. Over two hours, you’ll complete performance-based tasks in a command line. Expect to be tested on Kubernetes networking, storage, security, maintenance, logging and monitoring, application lifecycle, troubleshooting, API object primitives, and basic use-case ability.
Certified Kubernetes Application Developer (CKAD)
Demonstrate your ability to design, build, and deploy cloud-native applications for Kubernetes by taking the CKAD exam. You should be able to work with container images, apply cloud-native application concepts and architectures, and work with/validate Kubernetes resource definitions. When you register, you automatically get two attempts at the exam.
HashiCorp offers the Terraform Certified Associate exam for engineers who work in the cloud and want to guarantee that they know the basics of Terraform and automation. The exam will require you to: understand IaC, Terraform, Terraform Cloud, and Enterprise capabilities; use Terraform CLI; interact with Terraform modules; navigate Terraform workflow; implement and maintain state; and read, generate, and modify the configuration. It’s one hour of multiple-choice questions.
Step 5 – Connect with an expert
A lot goes into a successful DevOps career, and it can be challenging to navigate it alone. Between figuring out what skills to learn, identifying the most relevant tools, learning coding basics, selecting exams, and getting certified, it’s easy to get overwhelmed.
This is why we recommend connecting with an expert. Your expert mentor can help alleviate some of this decision fatigue, guide you through the entire process, meet you where you’re at, and support you through challenges along the way. Your DevOps mentor fills this need and does the work of finding someone for you by connecting you with established experts in the field.
Experts are actively engaged in the most cutting-edge technologies of the field. Your mentor will make sure you are learning up-to-date things as the field evolves, putting you in the best position for scoring a job doing the most exciting work in DevOps.
A DevOps job, like any other tech job, requires learning new skills. Having a mentor to review your progress is vital to grasping new concepts.
Additionally, mentors help you troubleshoot when you encounter difficulties. Maybe your code isn’t working as it should. Maybe there’s that one concept that you just don’t understand by reading a book alone. Maybe you’re trying to break out of the pack as you create a project for your portfolio. With an expert by your side, you’ll be able to resolve any problems that arise.
DevOps is an exciting and ever-growing field, and this is just an introduction. Take the next step! Get your start in DevOps engineering by signing up for Your DevOps Mentor. Let us help you.
Apply for the individual mentorship program here: https://yourdevopsmentor.com/apply/