A global survey of 450 DevOps and security practitioners published this week by Dynatrace found investments in automation have improved software quality (61%), reduced deployment failures (57%) and decreased IT costs (55%).
However, only 38% of respondents said their organization had a clearly defined DevOps automation strategy. On average, organizations have succeeded in automating just over half (56%) of their end-to-end DevOps life cycle, the survey found.
Saif Gunja, director of product marketing for Dynatrace, said the survey makes it clear that automation is still being applied to isolated workflows rather than centrally managed. That is changing, however, as more organizations embrace platform engineering to manage DevOps workflows at scale, he added.
Overall, organizations are investing in DevOps automation over the next 12 months to improve security and compliance management (55%), infrastructure provisioning and management (52%) and performance optimization (51%).
The biggest barriers preventing organizations from automating new DevOps use cases are security concerns (54%), difficulty operationalizing data (54%) and toolchain complexity (53%). The average organization relies on more than seven different tools for DevOps automation, the survey finds.
As a result, the automation that has been put in place is often too brittle to effectively scale beyond a small DevOps team, noted Gunja.
A full 71% of respondents also used observability data and insights to drive automation decisions and improvements in DevOps workflows. However, 85% also admitted they faced challenges using observability and security data to drive DevOps automation. The top three challenges facing organizations included inaccessible data (51%), siloed data (43%) and the need for data to flow through many systems (41%).
Well over half (54%) said their organization is investing in platforms to enable easier integration of tools and collaboration between teams involved in automation projects.
Finally, 59% also anticipated large language models (LLMs) such as ChatGPT and Bard would have a significant impact on DevOps, with the top three benefits expected including increased productivity and reduced manual effort (57%), improved development, security and operations collaboration (56%) and enabling teams to generate code automatically (48%).
Many organizations that have embraced DevOps are now looking to strike a balance between the concept of developers owning every application or service they developed and the need to reduce the amount of toil developers now encounter, noted Gunja. Developers typically only spend about a quarter of their time writing code so there is a clear need to reduce the current level of cognitive load developers encounter as they maintain application development environments, he added.
The challenge is finding a way to reduce that load in a way that doesn’t overly restrict the ability of developers to embrace new tools and platforms that will enable them to build applications in a more innovative fashion. One of the primary reasons many development teams embraced DevOps in the first place was to not have the way they build applications dictated to them by a centralized IT team.
One way or another, DevOps workflows will continue to be increasingly automated. Less clear at the moment, however, is exactly who within an organization will be driving those initiatives.