Software intelligence company Dynatrace has announced the results of an independent global survey of 1,300 CIOs and senior DevOps managers in large organisations.
The findings revealed the increased difficulty of maintaining software reliability and security as the demand for continuous release cycles and the rising complexity of cloud-native environments create more risk for undetected defects and vulnerabilities to escape into production.
CIOs and senior DevOps managers are looking to DevSecOps processes, the convergence of observability and security, and the increased use of AI and automation to balance accelerated innovation with reliability and security.
The research revealed that 90% of organisations say digital transformation has accelerated in the past 12 months and that 78% of organisations deploy software updates into production every 12 hours or less, 54% say they do so at least once every two hours.
The report also found that DevOps teams spend nearly a third (31%) of their time on manual tasks involving detecting code quality issues and vulnerabilities, reducing the time spent on innovation.
Furthermore, 55% of organisations make tradeoffs between quality, security, and user experience to meet the need for rapid transformation. 88% of CIOs say the convergence of observability and security practices will be critical to building a DevSecOps culture, and 90% say increasing the use of AIOps will be key to scaling up these practices.
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“It’s difficult for teams to accelerate the pace of innovation while also maintaining the highest quality and security standards,” said Bernd Greifeneder, Founder and Chief Technology Officer at Dynatrace.
He added: “More frequent software deployments, combined with complex cloud-native architectures, make it easier for errors and vulnerabilities to escape into production where they impact customer experience and create risk. There simply aren’t enough hours in the day for teams to test code as thoroughly as when they had only a single monthly deployment, but there’s no margin for error in today’s ultra-competitive, always-on economy.
“Something has to change.”
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