How to change the culture of the company for growth? A task like “How to teach an elephant to dance?”, Where the elephant is your IT infrastructure, and dance is your DevOps practice. However, most elephants in the modern IT market already perform this dance perfectly.
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 IT infrastructure changes according to DevOps’ requirements? No, it doesn’t. However, 2021 puts forward an ultimatum — either you automate processes, or you will be left behind. So, here it is, the primary trend.
Automation
DevOps is NOT a set of separate tools! This is an ideology that is entirely different from the development we are used to. Gartner claims that 80% of IT companies will implement DevOps methodologies in 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 with humans at the center,” says Forrester. This quote from Forbes regarding the crash of two Boeing 737 Max. The crew did not understand what actions the automated system was performing since a critical detail was overlooked during development — human participation. And this, of course, confirms the need for people to control automated systems.
In their report, Gartner calls automation hyper-automation, which is absolutely right. In 2021, automation will be integrated into all software development stages — from market analysis to release management.
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. Speaking of smart…
Artificial Intelligence and Data Science
Remember how testers rolled 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.
Besides, 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 showed their advantages over offline services in 2020 when many countries were forced to quarantine themselves. 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.
Speaking of capabilities, AI is already being used for data analysis and proactive monitoring.
Monitoring and automatic recovery
It’s no secret that we are moving closer to automation to ensure IT infrastructures’ functionality and keep them running. Automatic recovery is already a significant 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 snowballing in the market, as this solution is closely related to eliminating the human factor. Automatic recovery means quick response and, therefore, reducing costs.
Companies use AI-powered solutions to analyze logs and detect suspicious activity that can lead to downtime to ensure fast and effective system recovery and security. Monitoring metrics to identify unknown patterns are crucial 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. 2021 will be the milestones for smart automation, and DevOps Assembly Lines are an excellent example of this.
DevOps Assembly Lines
A holistic strategy, no matter what is developed, will go into production. Seriously, DevOps build assembly lines are designed to enable smart, scripted error-free production.
The introduction of the continuous integration and code delivery pipeline (CI / CD Pipelines) was one of the trends of 2020, and this year companies are investing in the development of conveyor belts — assembly conveyor lines. This methodology aims to automate and integrate different software development processes: development itself (continuous integration), configuration, testing, SecOps, and code delivery to production.
The DevOps assembly line’s introduction was inevitable and obvious, as it is a bridge that connects separate processes and is already built — just take it and use it.
DevSecOps
Security has been the main objection against 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 soon, artificial intelligence and data science will play a massive role in transforming DevOps — not only in testing and security but also in automating the entire infrastructure — “Everything as Code.”
Everything as Code
One of the trends in 2020 was Infrastructure as Code. It has been widely used in companies worldwide 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 structures, application properties, and deployment configurations. Any element can be recreated in a minute with one click. This also applies to the automation of CI / CD pipelines and the system’s design as code (network and software diagrams, packet flow, etc.)
As you can see, the system’s maintenance is no longer required special skills, and this is not a revolution in automation but another step towards leaving all the tedious work to the machines.
Containerization & Kubernetes
You’re not surprised, are you? Of course, it should come as no surprise that Kubernetes is still the TOP among orchestration solutions, becoming a monopoly among orchestrators. Companies that have used their own orchestration solutions are now migrating to Kubernetes to leverage the proposed functionality. Even Docker Swarm now offers a transcript of your application syntax in Kubernetes; Rancher uses Kubernetes at its core.
Microservices
Microservices have been trending IT trends over the last few years. However, a tip for anyone considering a microservices infrastructure: it makes sense to build one ONLY if you already have a fast-growing application that needs to scale out. Then, and only then, it will be sufficient 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 auto scripts and pipelines and 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 real digital transformation for DevOps. Explore these trends, try new tools, experience setbacks, celebrate success, experiment — this is the only way to success. Happy and comfortable DevOps transformation!
