A recent global survey of 1,300 CIOs and technology leaders, including 100 in Australia, reveals that organisations continue to turn to multicloud environments and cloud-native architectures for rapid transformation and secure innovation. However, traditional AIOps models are unable to manage the surge of data resulting from this modern cloud ecosystem adoption, highlighting the necessity for a mature AI, analytics, and automation strategy. The survey was reportedly conducted independently and its findings were announced by Dynatrace, a leader in unified observability and security.

According to the findings in the report, titled "The state of observability 2024: Overcoming complexity through AI-driven analytics and automation strategies," 76% of organisations claim that their technology stack's complexity has increased over the past year, with 36% forecasting a continuous increase. On average, organisations are using a multicloud environment that spans across a staggering 14 different platforms and services. Furthermore, 94% of technology leaders assert that multicloud complexity makes delivering excellent customer experiences more challenging, while 84% state it makes applications harder to protect.

The research also revealed that 87% of technology leaders believe cloud-native technology stacks are producing an overwhelming amount of data beyond the capability of human management. On average, organisations are utilising nine different monitoring and observability tools to manage applications, infrastructure, and user experiences. Moreover, 89% of the technology leaders surveyed claim that the number of tools, platforms, dashboards, and applications they rely on aggravates the complexity of managing a multicloud environment.

"Cloud-native architectures have become mandatory for modern organisations, offering the speed, scale, and agility they need to deliver innovation. However, the considerable amount of data they produce makes monitoring and securing applications increasingly difficult," Bernd Greifeneder, CTO at Dynatrace, commented. "Consequently, critical business objectives like customer experience are suffering, and it is getting harder to protect against complex cyber threats."

The survey additionally revealed that 78% of technology leaders believe manual approaches to log management and analytics are unable to keep pace with their technology stack's rate of change and data production volumes. Furthermore, 77% of technology leaders suggest that the time spent by their teams maintaining monitoring tools and preparing data for analysis diverts time from innovation. Despite 68% of organisations adopting AIOps to reduce the complexity of managing their multicloud environment, all the surveyed technology leaders agree that probabilistic machine learning approaches have hampered the value delivered by AIOps due to the manual effort needed to gain reliable insights.

In conclusion, Greifeneder commented, "Organisations require advanced AI, analytics, and automation capabilities to overcome the complexity of modern technology stacks. By unifying diverse data, retaining its context, and powering analytics and automation with a hypermodal AI that combines multiple techniques... teams can unlock a wealth of insights from their data to drive smarter decision-making, intelligent automation, and more efficient ways of working."