DevOps 2021: Trends and Prospects

According to numerous studies, the share of DevOps in 2017 was $2.9 billion. According to Hackernoon, implementing DevOps practices from 2018 to 2019 increased by 7%. IDC estimates the DevOps market will grow to $6.6 billion by 2022.

Does all this mean that we need to prepare for changes in IT infrastructure in accordance with the requirements of DevOps? No. However, 2021 puts forward an ultimatum – either you automate processes, or you will be left behind. Experts from Boosty Labs – DevOps consulting service and smart contract development company ( – share their vision of the key DevOps tendencies.


DevOps is not a set of separate tools. This is an ideology that is completely different from the development we are used to. Gartner claims that 80% of IT companies will implement DevOps methodologies by 2021. Comparing this to 40% in 2017, it is clear that the competition in the market dictates its requirements – agility, efficiency and flexibility.

While DevOps will strengthen its position in automation in 2021, automation will not take over most of the manual tasks in IT.

“… Every automated system must be designed to keep people in charge,” says Forrester.

This quote from Forbes is regarding the crash of two Boeing 737 Max. The crew simply did not understand what actions the automated system was performing, since an important detail was overlooked during development – human participation. And this, of course, confirms the need for people to control automated systems.

In its report, Gartner calls automation hyper-automation, which is absolutely true. In 2021 automation will be integrated into all stages of software development – from market analysis to release management.

Test automation will play a huge role in 2021. Manual testing and monotonous primitive testing are a thing of the past. Smart and automated software testing is taking off at a rapid pace this year.

Artificial Intelligence and Data Science

In the recent past, how did testers roll their eyes every time a speaker at an IT conference brought up the topic of AI? Just a few years later, more and more companies are adopting AI-powered testing tools. 2021 will become a new era – smart automated testing.

Of course, the development of automated testing is still human, and this will not change for at least a few years.

In addition, AI is used to analyze monitoring data and automatically scale infrastructure based on metrics. Cloud providers already offer this capability with auto-scaling teams. Online services have shown their advantages over offline services in 2020, when many countries were forced to quarantine. As a result, we saw that it is only a matter of time before companies move to the cloud and automate infrastructure. This is why AI and data science will play an important role in automation solutions in 2021, of course, according to their capabilities.

Monitoring and automatic recovery

It’s no secret that we are moving closer to automation that ensures the functionality of IT infrastructures and keeps them running. Automatic recovery has already become a big event in the IT world. While there is no need to use AI to keep the system running around the clock, just under 80% of companies have implemented this solution.

The truth is that the share of self-healing services is growing rapidly in the market, as this solution is closely related to the elimination of the human factor. Automatic recovery means quick response and therefore no maximum cost.

To ensure fast and effective system recovery and security, companies use AI-powered solutions to analyze logs and detect suspicious activity that can lead to downtime. Monitoring metrics to identify unknown patterns are key to keeping the system up and running, and machines have proven to be far more efficient and responsive to alerts than humans.

One of the main trends in IT is to allow people to focus on designing and building technologies that will take care of the rest. 2020-2021 will be the milestones in smart automation, and DevOps Assembly Lines are a good example of this.

DevOps Build Conveyor Lines

DevOps build assembly lines are designed to enable smart, error-free scripted production.

The introduction of the continuous integration and code delivery pipeline (CI/CD Pipelines) was one of the trends of 2019, and this year companies are investing in the development of conveyor belts – assembly conveyor lines. This methodology aims to automate and integrate different parts of the software development process: development itself (continuous integration), configuration, testing, SecOps, and delivery of code to production.

The introduction of the DevOps assembly line was inevitable and obvious, since it is a bridge that connects separate processes, and, moreover, already built – take it and use it.


Security has been the main objection to cloud hosting until today. The solution we’ve all been waiting for is AI integration. Analyzing traffic and user behavior, detecting non-standard activity – all these indicators analyzed by AI will allow us to react faster or set up a security system that will respond to warnings and take preventive measures. AI algorithms will be used to detect any attack-like activity to prevent system failures.

It is clear that in the near future, artificial intelligence and data science will play a huge role in transforming DevOps – not only in testing and security, but also in automating the entire infrastructure.

Everything is like code

One of the trends in 2019 was “Infrastructure as code”. It has been widely used in companies around the world, but is no longer sufficient to provide compatibility in the market. The “Everything as code” approach involves referring to all parts of the system as code – storing what is described in the code in a repository, for example, GitHub.

Stored parts represent the infrastructure and configuration of communications switches, clean servers, operating systems, build configurations, application properties, and deployment configurations. Any part can be recreated in a minute with one click. This also applies to the automation of CI/CD pipelines and the design of the system as code (network and software diagrams, packet flow, etc.)

As you can see, maintenance of the system doesn’t longer require special skills, and this is not a revolution in automation, but another step towards leaving all the tedious work to the machines.

Containerization and Kubernetes

Kubernetes is still the TOP among orchestration solutions, in fact, becoming a monopoly among orchestrators. Companies that used their own orchestration solutions are now migrating to Kubernetes to be able to leverage the proposed functionality. Even Docker Swarm now offers a transcript of your application syntax in Kubernetes; Rancher uses Kubernetes at its core.


Over the past few years, microservices have consistently been trending IT trends. However, a tip for anyone considering a microservices infrastructure: it makes sense to build it ONLY if you already have a fast-growing application that needs to scale out. Then, and only then, will it be effective to “cut” parts of your existing infrastructure and make them microservices one at a time.

Follow the trends

Automation has become mainstream and its implementation includes autoscripts and pipelines, as well as AI and data science. Together, these practices will gradually begin to perform manual tasks. But don’t worry, no one will lose their jobs due to robotization, and any human work will turn into something more – something that a robot cannot do. For example, manual testers will start creating automated tests and then improve them, while sysadmins will practice DevOps, etc. One thing remains clear – if companies want to increase uptime and recover quickly, they need to automate processes.

Thus, 2021 is a time of true digital transformation for DevOps. The key to success is studying trends, testing new tools, experimenting.