Trends Tech Blog

Organizations increasingly adopting multi-cloud architectures face challenges related to agility and scalability. A study commissioned by Dynatrace shows this, and one of the results is that IT teams spend almost half their timekeeping systems.

According to Dynatrace, multi-cloud strategies have led to an increase in complexity. Monitoring and ever-changing managing environments often provide infrastructure teams with too much data. So they would have to spend a lot of time on routine manual tasks – time that is missing to accelerate innovation. This would underscore the need for increased use of AI and automation.

• One hundred percent of the companies surveyed have a multi-cloud environment and use an average of six different platforms. These include Amazon Web Services (62%), Microsoft Azure (38%), Google Cloud (23%), and IBM Red Hat (11%).
• Organizations use an average of eight different infrastructure monitoring solutions to manage multi-cloud environments. Fifty-five percent say this makes optimizing infrastructure performance and resource consumption challenges.
• According to 83 percent of IT leaders, adopting Kubernetes has made their infrastructure more dynamic and challenging to manage.
• Forty-eight percent of IT leaders believe that traditional infrastructure monitoring solutions are no longer appropriate with multi-cloud and Kubernetes.

Multi-cloud strategies are critical to keeping up with the rapid pace of digital transformation but teams are struggling to manage the complexities these environments bring, said Bernd Greifeneder, Founder and Chief Technology Officer at Dynatrace. Dependencies are growing exponentially, driven by faster deployment cadence and cloud-native architectures that drive constant change. Open-source technologies complicate this by providing teams with even more data.

Each cloud service or cloud platform has its monitoring solution to make matters worse. Teams must manually extract insights from each key and merge them with data from other dashboards for a complete picture. Companies should support their teams to reduce the time spent on manual tasks, and then they can refocus on strategic functions that deliver new, high-quality services to customers.”

• Fifty-six percent of IT leaders say observability blind spots in their multi-cloud environments lead to greater digital transformation risk because teams don’t have an easy way to monitor infrastructure end-to-end.
• Fifty-five percent of IT leaders state that infrastructure management ties up more and more resources like cloud services increases. As a result, their teams are forced to switch between different solutions and dashboards to gain insights.
• Almost half (42.5%) of their time is wasted by IT teams doing manual, grunt work to keep systems running. This results in a significant loss of productivity and missed revenue opportunities due to delayed innovation.
• More than half (60%) of IT leaders believe that traditional approaches to infrastructure monitoring need to be replaced with a platform that enables end-to-end observability across multi-cloud environments.

Infrastructure teams need AI-driven solutions that automate as many manual routine tasks as possible,” continues Greifeneder. With automatic, continuous discovery and instrumentation, teams can reduce manual effort while maintaining end-to-end observability across their hybrid, multi-cloud environments. However, observability alone is not enough. You also need access to precise answers to help teams effectively optimize their settings.

Conventional approaches cannot keep up here as they rely heavily on manual processes. Businesses need a more innovative approach that combines AI, automation, and end-to-end observability, giving teams more time to focus on accelerating innovation and optimizing usage.

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