The History 

The term "DevOps" was popularized by a series of "DevOps Days" meetings held in 2009 in Belgium. One of the most important theoretical works on DevOps is considered to be the book by Patrick Dubois, Gene Kim, Jez Humble, and John Willis "The DevOps Handbook. How to Achieve World-Class Agility, Reliability, and Security in Technology Companies," first published in English in 2016. The founders of several software companies and independent IT consultants were prompted to do this by their accumulated experience in large projects.

However, the concept of DevOps itself originated in the early 2000s, when the IT world of large corporations faced the problem of workflow mismatch when the normal operation of a software product is disrupted by the functional and organizational separation of those who write code and those who perform its deployment and support. Product developers and maintainers often have different and even conflicting goals, department heads, and key performance indicators. Workplaces of various participants of the software lifecycle are often located in different locations. This fragmentation and disruption of communication within the company leads to longer deadlines, overtime, disrupted releases, and customer dissatisfaction.

Recommended Read: Who Is a DevOps Engineer? Job Description, Role, And Skills

The DevOps concept proposes to solve this problem by applying Agile principles not only to development and testing but also to software operation processes, i.e. deployment and support. Thus, the popularity of DevOps arose, among other things, due to the spread of Agile practices focused on speeding up the processes of delivering the finished product and increasing the number of released versions. In addition, an additional driver of DevOps development was microservice architecture, when a system consists of a set of separate loosely coupled modules, the implementation of each of which is the responsibility of one person who develops, tests, and deploys software. Due to the small size of each module (service), its architecture can be created by continuous refactoring, which reduces the laboriousness of preliminary design and allows new releases of the software 2.

Who is a DevOps Engineer

First, let's talk about what DevOps is. It's not tools or services. It's a concept, a culture, a whole set of methods, techniques, and rules of interaction between employees from different teams.

DevOps practices are aimed at uniting employees, eliminating fragmentation, and distributing responsibility for all work to each team member.

Even though web developers work on writing code, testers are responsible for its verification, and system administrators handle maintenance, all participants who are involved in creating a product take responsibility for the final result, not just for their part of the work.

The barrier between development and support has begun to dissipate. Problems are not shifted to each other, the team acts together, everyone tries to do their part in solving the problem. This is the second component of DevOps practices.

It's not just about teaming up, it's about actually solving problems

That's why the project doesn't specifically need DevOps engineers, i.e. people who implement DevOps practices in a collaborative environment, but the result that they help achieve. Some firms don't even have such a position, and the responsibilities of that person are divided among everyone involved in the project.

A DevOps engineer has to do everything to solve problems in the production and implementation of the product. To do this in his work, the specialist needs to adhere to:

  1. Automating all processes.
  2. Accelerating the release of the product.
  3. Instant feedback from consumers.

About automation is clear: all repetitive actions are performed automatically, quickly, smoothly, and clearly.

The second is an important point for the customer. All manufacturers benefit from presenting their creations before their competitors come up with something similar. This is feasible thanks to coherence in the actions of all parts of the project team. And this very unity is organized by the DevOps engineer.

Customer feedback involves making adjustments and updating the application immediately after receiving complaints from users.

From these points, it is clear that the responsibilities of a DevOps specialist extend to all stages of the web product lifecycle: from architecture selection and code writing to application release and user feedback monitoring.

What DevOps does at work

A DevOps engineer does everything that makes development faster and more efficient.

  • Creating tools and designing infrastructure for software development.
  • Automating processes. For example, check how an application works. We created it and have to check whether it's possible to log in, whether it's possible to leave a comment, how the program behaves in the mobile version, etc. DevOps engineers help to automate these checks.
  • Working with cloud technologies. "The cloud is different in the method of storing and processing data from the computer, which means the principle of its operation is different. A DevOps engineer helps organizations make the most of the cloud, minimizing risk.
  • Solving urgent tasks.
  • Integrations. For example, CI - Continuous Integration. Why it's needed. Usually, on projects, engineers write parts of common code. Sometimes it happens that code that works well on the computer where it was written won't run at all on another "machine". In CI, DevOps engineers assemble the pieces of code that different developers have made and see if they compile. And they also analyze those pieces of code and, according to the rules, make recommendations to improve security, fix potential bugs, etc.
  • Process support and monitoring.

Knowledge, skills, and personal qualities

DevOps engineers can be called multidisciplinary specialists with knowledge from different areas of IT activities: programming, monitoring, working with databases, operating systems, and building systems, orchestration, and configuration, cloud infrastructure.

A specialist must know several programming languages. First of all, it is necessary for automation. The languages Python, Bash, Ruby, Go, PowerShell will be useful. By the way, if you’re only studying, you get help with python homework to things done. It is enough to know the basics of syntax, scripts for automation, understand object-oriented programming.

Understand the operating systems to determine the server to install the application, the environment to run it in, the tools to use, and any possible errors that may occur. You must understand the general principles of any operating system but it is more common to use Windows or Linux.

A good DevOps engineer should be able to understand and work with cloud providers. They automate many processes and save time, effort, and money, which will be useful not only for the specialist but for the client as well.

And here's the other minimum you need to know:

  • Orchestration systems such as Docker and Kubernetes;
  • Chef, Ansible, Puppet configuration systems;
  • GitLab, Jenkins build systems;
  • JSON and YAML markup languages;
  • databases;
  • monitoring and alerting services;
  • logging services;
  • cybersecurity settings;
  • CI/CD processes;
  • English language;
  • DevOps periodic table.

The list of things a DevOps specialist needs to know and be able to do could go on for a long time. But only by practicing will it become clear what to learn and how to learn it.

Personal qualities are also important for a DevOps engineer:

  • systems thinking;
  • attention span;
  • good memory;
  • communication skills;
  • responsibility;
  • efficiency;
  • diligence;
  • quick learning ability.

These are only basic requirements. Specific conditions depend on employers.

DevOps automation tools

It is critical to automate and customize all testing processes to make the process faster and more efficient. This process is known as DevOps automation.

The challenges faced by a DevOps team supporting a huge IT infrastructure can be briefly divided into six categories.

  1. Infrastructure automation
  2. Configuration management
  3. Deployment automation
  4. Performance management
  5. Log management
  6. Monitoring

Let's take a look at a few tools in each of these categories and how they solve problems.

Infrastructure Automation

Amazon Web Services (AWS): because it's a cloud-based service, you don't need to be physically present in the data center. In addition, these processes are easily scalable on demand. There are no upfront hardware costs. There is the ability to automatically allocate more servers based on traffic.

Configuration management

Chef: This is a useful DevOps tool for making processes faster, more scalable, and more consistent. It can be used to facilitate complex tasks and configuration management. The DevOps team doesn't need to make changes on tens of thousands of servers. Just make the changes once and they will automatically show up on other servers.

Deployment automation

Jenkins: This tool facilitates continuous integration and testing. Jenkins helps integrate project changes more easily by quickly detecting problems after deployment.

Log management

Splunk: This tool solves problems such as consolidation, storage, and analysis of all logs in one place.

Performance management

App Dynamic: This tool monitors performance in real-time. The data collected with App Dynamic helps developers debug when problems arise.


Nagios: Nagios is one of the tools that helps DevOps teams find and fix problems.

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Also, check out DevOps Book You should read section.