Dynatrace (NYSE: DT), a leader in unified observability and security, announced today the results of the Annual Global CIO Report, an independent global survey of 1,300 CIOs and technology leaders from large organizations. The research reveals that companies are continuing to adopt multicloud environments and cloud-native architectures to enable rapid transformation and secure innovation.
Despite the speed, scale, and agility that these modern cloud ecosystems enable, companies are struggling to manage the vast amount of data they generate. These research findings highlight the need for a consolidated strategy of AI, analytics, and automation that goes beyond traditional AIOps models to drive lasting business value. The report, “The state of observability 2024: Overcoming complexity through AI-driven analytics and automation strategies,” is available for download.
The research results include:
– 86% of Spanish organizations report that the complexity of their technological stack has increased in the last 12 months, with 51% stating it will continue to grow.
– The report reveals that the average multicloud environment in Spain spans 11 different platforms and services.
– In the Spanish context, 82% of technology leaders claim that multicloud complexity makes it harder to deliver exceptional customer experiences, while the international percentage is 87%. They also say that this complexity makes applications harder to secure (79%).
– 84% of Spanish technology leaders say that cloud-native technology stacks produce a data explosion that surpasses human management capacity. Globally, this percentage increases to 86%.
– On average, organizations in Spain use 12 different monitoring and observability tools to manage applications, infrastructure, and user experience.
– 85% of global technology leaders say that the increasing number of tools, platforms, dashboards, and applications they rely on adds complexity to managing a multicloud environment. In Spain, 74% of leaders share this view.
“Cloud-native architectures have become a mandatory requirement for today’s businesses, providing the speed, scale, and agility they need to deliver innovation,” says Bernd Greifeneder, CTO of Dynatrace. “These architectures reflect an increasingly wide variety of cloud platforms and services to support even the simplest digital transaction. The enormous amount of data they produce makes it increasingly difficult to monitor and secure applications. As a result, critical business aspects such as customer experience are affected, and protecting against advanced cyber threats becomes increasingly challenging.”
Other study conclusions:
– In Spain, 71% of tech leaders state that manual approaches to managing and analyzing logs cannot keep pace with the changes in their technological stack and the volumes of data it produces.
– 81% of technology leaders globally say that the time their teams spend maintaining monitoring tools and preparing data for analysis detracts from innovation. In Spain, this percentage rises to 85%, indicating that the majority share this view.
– 76% of Spanish organizations have already adopted AIOps to reduce the complexity of managing their multicloud environment, and another 21% plan to do so in the next 12 months.
– Worldwide, 97% of technology leaders say that probabilistic machine learning approaches have limited the value offered by AIOps due to the manual effort required to obtain reliable insights.
“Without the ability to transform large volumes of diverse data from cloud-native architectures into contextually relevant real-time insights, IT, development, security, and business teams struggle to understand what is happening in their environment and lack the necessary answers to resolve issues quickly and decisively,” Greifeneder adds. “While many organizations turn to AIOps, they often find limited value due to the reliance on probabilistic methods, which can be inaccurate and slow to implement. To overcome the complexity of modern technology stacks, organizations need advanced AI, analytics, and automation capabilities. By unifying diverse data, preserving its context, and empowering analytics and automation with hypermodal AI that combines multiple techniques, including causal, predictive, and generative AI, teams can gain valuable insights from their data to make more informed decisions, intelligent automation, and more efficient ways of working.”
### Methodology
This report is based on a global survey conducted by Coleman Parkes and commissioned by Dynatrace of 1,300 CIOs, CTOs, and other senior technology leaders involved in IT operations and DevOps management in large companies with more than 1,000 employees. The sample included 200 respondents in the US, 100 in Latin America, 600 in Europe, 150 in the Middle East, and 250 in Asia Pacific.