DevOps Trends To Watch Out For in 2020
Changing your company’s culture to favor growth is like teaching an elephant how to dance. The elephant is your IT infrastructure, and the dance is adopting development and operations (DevOps) practices.
Learning new trends in DevOps means you could transform and adjust in time to be competitive. Because, guess what, most of the elephants in the modern IT market already know the dance.
In 2017, the DevOps share of the market stood at $2.9 billion. According to Hackernoon, there was a 17% boost in DevOps adoption in 2018, and the IDC estimates the DevOps market will grow to $6.6 billion by 2022.
Does this mean transforming our IT infrastructures in accordance with DevOps requirements is just something that’s nice to do?
What it does mean is that 2020 brings up an ultimatum—either you automate the processes with DevOps practices or get left behind.
But don’t worry, because in this post, I’ll give you a full view of the latest DevOps trends, the main focus of DevOps, and relevant practices to implement in 2020.
DevOps is not a set of separate tools. It’s an ideology that is completely different from the development we’re used to.
Eighty percent of IT companies will have shifted to DevOps methodologies by 2021, Comparing this to 40% in 2017, it’s absolutely clear that competition on the market requires being quick, effective, and flexible.
Although DevOps will strengthen its position in automation in 2020, this won’t be the year when robots take over the majority of the manual jobs in IT.
“… every automated system must be designed with humans at the center,” says Forrester.
This quote was used by Forbes in the context of two Boeing 737 Max crashes. The crew simply did not understand what the automated system was doing because the importance of human participation was neglected during development.
This situation proves the need for automated systems that are supervised by humans to complement fast action with a human’s vision of the situation.
Gartner refers to automation as “hyperautomation” in its report, which seems apt since in 2020-2021, automation will be integrated into all stages of software development, from market analysis to release management.
Manual and monkey testing will be a thing of the past. This year will kick-start smart and automated software testing. Speaking of smart …
AI and Data Science
Remember testers rolling their eyes when a speaker at an IT conference called for AI? Only a few years later, AI-powered testing tools are being adopted for quality assurance in more and more companies.
2020 might prove to be the beginning of a new era in smart/automated testing.
To be fair, the development of automated testing is still a human’s job, and this is not going to change for several years.
However, AI is used to analyze monitoring data and autoscale the infrastructure depending on what metrics show. Cloud providers already offer this possibility with Auto Scaling Groups.
More importantly, online services showed their advantages over offline ones during the 2020 pandemic, when many countries were forced into quarantine and therefore remote work.
As a result, we can clearly see that it is only a matter of time before companies migrate to clouds and automate their infrastructures.
This is why AI and data science will very likely make up a large part of automation solutions in 2020 and beyond.
Indeed, AI is already used for data analysis and preventive monitoring, as we’ll see in the next section.
Monitoring and Automated Recovery
It’s no secret that we’re moving toward automating activities that ensure IT infrastructure functionality and keep it running.
Automated recovery has already become the next big thing in the IT world. Even though there’s no need to use AI to keep systems alive 24/7, near 80% of companies have implemented automated recovery.
The share of self-healing services on the market is growing quickly, as this solution is closely related to the elimination of the human factor. Automated recovery means fast reaction, and correspondingly, no cost peaks.
To ensure fast and effective recovery and system security, companies are using AI-powered solutions for log analysis and suspicious activity detection that could cause downtime.
Monitoring metrics to determine unknown patterns is the #1 key to keeping your system healthy. Machines have also proven to be much more productive and proactive than humans in reacting to alerts.
One major trend in the IT sphere is letting people concentrate on development and building machines that take care of everything else.
2020 will become a milestone for advancements made in smart automation. One good example of this is DevOps assembly lines.
DevOps Assembly Lines
Definition of a holistic strategy: No matter what you develop, it will find its way to production.
Jokes aside, DevOps assembly lines are designed to ensure a smart and error-free path to production performed by scripts.
While continuous integration/continuous delivery (CI/CD) pipeline implementation was one of 2019’s trends, this year companies are investing in building a “pipeline for pipelines”—assembly lines.
This methodology aims to automate and connect different parts of the software development process: the development itself (continuous integration), configuration, testing, SecOps, and delivery to production.
Adoption of DevOps assembly lines has been both inevitable and obvious, as they are already built and are a bridge between separate processes.
So far, security has been the main argument against cloud computing. The solution that we’ve all been waiting for is AI integration.
AI analysis of metrics such as traffic, user behavior, and out-of-pattern activity detection will enable us to react more quickly or set up a security system that will react to alerts and take preventive action.
AI algorithms will be used to detect any attack-like activity to prevent system failures.
Obviously, artificial intelligence and data science will play a huge part in DevOps transformation in the near future—not only in tests and security but also in automation of the whole infrastructure.
Everything as Code
One of the trends of 2019 was Infrastructure as Code. It was widely used in companies worldwide; however, it’s no longer enough to ensure compatibility on the market.
The Everything as Code approach refers to treating all parts of the system as code and keeping it in a repository such as GitHub.
The stored parts are infrastructure and configuration of communication switches, bare-metal servers, operating systems, build configurations, application properties, and deployment configurations. Any part can be recreated in a minute with only one click.
Everything as Code also refers to automating CI/CD pipelines and system design as code (network and software diagrams, packet flows, etc.)
Current system maintenance doesn’t require many specific skills. This is not a revolution in automation, but it is one more step toward leaving all of the tedious work to machines.
Containerization and Kubernetes
You aren’t surprised, right? No wonder Kubernetes is still on top of other orchestration solutions: It has basically become a monopolist among orchestrators and continues to grow in 2020.
Companies who used their own orchestrating solutions are now migrating to Kubernetes. Even Docker Swarm now offers to transcribe your application’s syntaxis into Kubernetes, and Rancher is using Kubernetes in its core.
Over the past few years, microservices have consistently appeared in IT trends, and 2020 is no exception.
However, here’s a piece of advice for anyone considering a microservice infrastructure: It makes sense to build it ONLY if you already have a fast-growing application with a need for horizontal scaling.
Then and only then will it be effective to cut out pieces of your existing infrastructure and restrict them to microservices one-by-one.
However, for platforms that need to scale quickly and safely, like e-commerce solutions, it is highly recommended to consider migration to microservices.
Picture this. You are running a successfully-launched e-store that is growing bigger every week. Boom! Quarantine! (Not so hard to picture this, right?) Traffic is insanely high during the day, and it goes back to normal at night. There are constant website failures due to the high load.
Although there are several ways to solve this issue, whether you’re on the cloud on on-premise servers, you wouldn’t have to worry about this with a microserviced infrastructure. You wouldn’t have lost those users who couldn’t reach your website when they needed it and would have saved on hiring a DevOps team during the high season.
Try Out the Trends
Automation has become a major focus, and its implementation involves automation scripts and pipelines, as well as AI and Data Science. Together, these practices will gradually take over manual tasks.
But rest assured, nobody needs to worry about losing their job to a robot.
Every human job will transform into something bigger, something that a robot can’t do. For example, manual testers will start creating automation tests and then improve them, System administrators will practice DevOps, etc.
One thing remains clear: If companies want to increase their uptime and recover quickly, they need to automate their processes.
2020 seems to be a real digital transformation for DevOps. Look up these eight trends, try new tools, fail, succeed, experiment—this is the only way to the top.
Happy DevOps transformation and good luck!