DevOps It’s more than an industry buzzword for agile computing – it’s the only way to get software releases out of the home at the speed business demands, while maintaining quality and security. Increasingly, artificial intelligence and machine learning are being brought in to aid the process. Given the pace of releases, the process is simply too large for anyone to manually supervise. It works well for many IT stores.
This is the word from GitLab, which released a file exploratory study Of the 5,001 managers and technology professionals who have experienced significant growth in their DevOps practices in the past 12 months alone. In 2022, a large segment of respondents (47%) indicated that DevOps or DevSecOps was their preferred methodology, an increase of five percentage points over 2021.
The survey shows that with this rise in DevOps comes an increased cadence in software delivery. 7 in 10 DevOps teams (70%) release code on a continuous basis – defined as once a day, or every few days – an increase of 63% from last year. At least 60% of developers release code faster than before. 35% said they code twice as fast, while 15% code three to five times faster. 8% said the blade exits the door five times faster.
To facilitate this, more high-level automation is being applied to software delivery – the survey found that 62% of DevOps teams are practicing ModelOpsGovernance and lifecycle management of AI models. At least 31% of teams are actively using AI and machine learning algorithms for code review, more than double last year’s figure. The survey also found that 37% of teams are using AI/machine learning in software testing (up from 25%), and another 20% plan to introduce it this year. 19% plan to roll out AI/machine learning-powered tests in the next 2-3 years.
Ironically, the method of code release – where the software is designed and then put up on the wall for QA teams or users – is still prevalent in many stores. Survey authors report that the percentage of teams using Waterfall is up 16% this year compared to last year. They added that Water/Scrum/Fall practitioners saw a 23% jump from last year.
The survey also shows that DevOps roles continue to shift. Developers handle operations, operations focus on the cloud or platform architecture, and security professionals take on hands-on training within development teams.
Toolchain extension and security are cited as the most pressing challenges for DevOps-based software deployments, the survey showed. Toolchain standardization is a high priority focus, with 69% of managers or professionals seeking to integrate their toolchains to address monitoring challenges, development delays, and negative impact on the developer experience. Nearly 40% of developers spend between a quarter and a half of their time maintaining or integrating complex tool chains – more than double the percentage since 2021.
Security has overtaken cloud computing as the number one investment area across DevOps teams. However, despite the desire to shift security to the left, many companies are still emerging in their approach and results – only 10% of respondents reported receiving an additional budget for security. Additionally, 50% of security professionals in the survey reported that developers failed to identify security issues – the equivalent of 75% of vulnerabilities.
When asked what they can use to do their jobs better, the developers in the study seek more and better code review, automated testing, and better planning (all at 31%). Strongest AI/ML for writing and reviewing code came in second place (27%) followed by code reuse (26%). The survey authors concluded, “These responses do not represent any significant deviation from what developers said last year, and may underscore how difficult it is to make systematic changes to process and technology.”