Top DevOps Statistics and Trends You Need to Know

Annually, Puppet releases the State of DevOps report sponsored by industry leaders. In 2021, they polled over 2,500 tech staff to find the answers to the major questions and collect accurate DevOps market statistics. The document stresses the “platform method for software delivery” as one of the hottest trends. It allows speeding up the development process and increasing the quality of results.

One of the major thoughts in this year’s survey is that the implementation of DevOps best practices such as automated testing and risk management makes it possible to achieve a high level of safety for software development solutions. 

Striving to share our extensive experience with all things IT, we sought to compile the most extensive guide possible on DevOps facts, statistics, and trends. What is DevOps and why your IT company needs to hire DevOps team and start implementing it today – read further. Otherwise, if you’re an established IT expert, you can move to the next section, where we discuss the leading DevOps trends for 2021.

DevOps Definition, Features, and Goals

Development and operations (DevOps) is a combination of principles, approaches, and tools that aid in regularizing and speeding up the process of developing and deploying software applications. Upon successful introduction of DevOps, engineering and optimizing the product becomes notably faster and the overall cohesion of the staff members grows. In turn, reduced developed terms permit focusing more effort upon the improvement of customer service and other core business goals.

The first spike in software development efficiency happened at the beginning of the 21st century when the first set of Agile practices was established. Agile methodologies strive to streamline and speed up the software development process while making it more reliable and meaningful.

In turn, DevOps discipline is centered on the establishment of better interaction between the departments and distributing the load more evenly. For instance, developers can integrate some unit testing into their everyday routine, while sysadmins can eliminate some of the bugs discovered during deployment independently. Successful introduction of DevOps into the business processes of a company allows:

• Reducing time to market (TTM);
• Minimizing the failure rate or new productions;
• Decreasing the lead time between fixes;
• Improving frequency and reliability of deployment;
• Reducing the mean recovery time.

Top DevOps Trends to Consider in 2024

COVID-19 pandemic and the related restrictions lead to the appearance of new trends in many areas of commerce itself and applicable spheres of activity, and DevOps is no exception. After all, it is one of those disciplines that concentrate on pushing things forward and invoking innovation. Every company should be aware of the latest trends to meet customer needs. Observe the factors that shape the current state of the DevOps market.

• The spread of microservice architecture

One advantage of such services is the rapid delivery of complex software. The other two benefits include the straightforward, hassle-free testing process and reduced costs. Finally, microservices allow for scalability and flexibility. Around 15% of specialists who tried employing this architecture stated that they have experienced notable success, while 69% reported that they apply virtualized containers for microservice-based software deployment.

• Accelerated uptake of artificial intelligence (AI) and machine learning (ML) algorithms

AI and ML are, probably, the most discussed topics in modern technology. Among everything else, they brought about a revolution in DevOps. Adoption of these technologies helps to enhance software development and operational efficiency greatly. The specific field of artificial intelligence that affects DevOps the most is predictive analytics. AI-powered analytic routines can monitor the development process and provide timely alerts, forecast possible failures, discover causes to drops in staff efficiency, detect hardware/software/security anomalies, etc.

• Infrastructure as code and GitOps

Deployment of more or less complex software products implies the preliminary creation of an environment for its launch – hardware, operating system, baseline software, and libraries, computing cluster, network and storage infrastructure, etc. – and setting the parameters of this environment. Suppose a system administrator is tasked with preparing workplaces for several employees simultaneously. In the past, this would assume a lot of manual labor, especially in the case of varying hardware.

In contrast, DevOps’ focus on automating all the routine processes to the maximum led to the emergence of infrastructure as a code (IaC) discipline. IaC is the process of managing and providing infrastructure through coded configuration templates, which minimizes the need for physical access to equipment. With it, infrastructure can be deployed and provisioned in minutes, and scaling can be planned based on mutable workloads.

The GitOps paradigm, as further advancement of IaC, implies the transfer of the best software development practices to infrastructure projects. In this case. Git repositories become the reliable source of truth about the desired state of the system: code modules describing applications, settings, and infrastructure. The deployment process is automated using familiar CI/CD tools, which increases the speed of creation, reliability, and reproducibility of solutions.

• The steady growth of the SaaS model of software distribution

The ubiquitous distribution of cloud computing led to the appearance of the Software-as-a-Service (SaaS) concept. While it is nothing new already, the sphere grows steadily year by year. Gartner DevOps statistics report predicts that the SaaS market’s value will surpass $117.7 billion in 2021. How does DevOps fit into the picture? One of the most important tools in its arsenal is constant deployment (CD) and virtualized cloud environments are the best in such a case. The app versions are deployed to the cloud, which provides it with the virtualized hardware layer and can both up- and down-scale the allocated computing resources automatically.

An app deployed to the cloud is easy to access from any connected device on the Earth. Moreover, most cloud service vendors provide customers with a variety of relative DevOps engineer statistics. Finally, the SaaS model of software distribution allows customers to save costs, previously allocated to designing the on-premise infrastructure and hiring the service personnel. More and more DevOps teams opt for multiple-cloud development methods to achieve top quality of apps, cost efficiency, and enhanced adaptability.

• DevSecOps

Security and development have always functioned separately. If a piece of software does not correspond to the security requirements and laws, the responsible team can even ban the release of such an app.

In its drive to integrate the day-to-day operation of the enterprise further, DevOps brought forth another innovative discipline- DevSecOps – that seeks to add the security team into the fold. Development, operations, and security teams should work together to reach a consensus that would reduce the time between releases to a minimum while upholding all the required security and legal requirements.

• End-to-end automation

Integrating automation in all the spheres of company activity allows reducing errors and delays attributed to human factor while letting the employees concentrate on their core responsibilities.

• Chaos engineering

This recent field of study is aimed at discovering and researching points of failure in distributed systems. Born accidentally in 2008 from Netflix’s ordeal with ongoing availability deficits despite the move from on-premise to cloud hosting, chaos engineering bears an inborn contradiction between its methods and final goal. Chaos engineering relies on the introduction of complications and extreme loads to the system and its parts to test the viability of safeguarding methods and discover the problematic plots. In turn, the end goal is to eliminate the weak links and make the system as volatile as possible even in the most critical conditions, not unlike the pentesting in the security sphere.