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Home Cybersecurity

Multicloud environment complexities putting digital transformation at risk

New York Tech Editorial Team by New York Tech Editorial Team
January 20, 2022
in Cybersecurity
0
Enterprises are embracing the multicloud, turning to providers for strategy
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Dynatrace announced the findings of an independent global survey of 1,300 CIOs and senior IT practitioners involved in infrastructure management. The research reveals the challenges organizations face as they overwhelmingly turn to multicloud architectures to achieve the agility and scalability needed to keep up with the pace of digital transformation.

multicloud environment digital transformation

Multicloud strategies have led to a surge in complexity, with infrastructure teams drowning in data as they try to monitor and manage their constantly changing environments. As a result, teams are spending more time on manual, routine tasks, limiting their ability to accelerate innovation and highlighting the need for increased use of AI and automation.

Multicloud strategies critical to keeping up with digital transformation

  • 99% of organizations have a multicloud environment, with the average spanning 5 different platforms. These include Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Red Hat, and others.
  • Organizations rely on 7 different infrastructure monitoring solutions, on average, to manage multicloud environments, and 57% say this makes it difficult to optimize infrastructure performance and resource consumption.
  • 81% of IT leaders say their use of Kubernetes has made their infrastructure more dynamic and challenging to manage.
  • 56% of IT leaders say traditional infrastructure monitoring solutions are no longer fit for purpose in a world of multiple clouds and Kubernetes.

“Multicloud strategies have become critical to keeping up with the rapidly accelerating pace of digital transformation, but teams are struggling to manage the complexity that these environments bring,” said Bernd Greifeneder, CTO at Dynatrace.

“Dependencies are growing at an exponential pace, driven by faster deployment frequency and cloud-native architectures that bring constant change. Open-source technologies complicate things by adding even more data for teams to deal with. Compounding the issue, each cloud service or platform has its own monitoring solution.

“To build a complete picture, teams are forced to manually extract insights from each solution and then piece these together with data from other dashboards. Organizations must find a way to help these teams reduce the time they spend on manual tasks and refocus on strategic work that delivers new, high-quality services for customers.”

Additional findings

  • 61% of IT leaders say observability blind spots in their multicloud environments are becoming a greater risk to digital transformation as teams find themselves without an easy way to monitor their infrastructure end-to-end.
  • 58% of IT leaders say infrastructure management is a growing drain on resources as their use of cloud services has increased, and their teams are forced to switch between different solutions and dashboards to gain insights.
  • 42% of IT teams’ time is wasted on manual, routine work to “keep the lights on” across their environments, creating a major productivity drain and leading to missed revenue opportunities due to delays to innovation.
  • 56% of IT leaders believe traditional infrastructure monitoring approaches must be replaced with a platform that can provide end-to-end observability across multicloud environments.

“Infrastructure teams need AI-driven solutions that can automate as many of their routine, manual tasks as possible,” continued Greifeneder. “With automatic, continuous discovery and instrumentation, teams can reduce manual effort while maintaining end-to-end observability across their hybrid, multicloud environments. However, observability alone isn’t enough. Access to precise answers that help teams optimize their environments effectively and efficiently is also needed.

“Traditional approaches simply can’t keep up, due to their heavy reliance on manual work. Organizations need a more intelligent approach, combining AI, automation, and end-to-end observability, to free up teams’ time, and enable them to focus on speeding innovation and optimizing user experiences.”

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