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DEALING WITH THE DATA CHALLENGES OF CLOUD- BASED INFRASTRUCTURE
Rafi Katanasho , APAC Chief Technology Officer and Solution Sales Vice President at Dynatrace , tells us how organizations can deal with the data challenges of cloud-based infrastructure to ensure maximum efficiency . “ To overcome this challenge , organizations are increasingly making use of what is termed Artificial Intelligence for Operations ( AIOps ) platforms ,” he says .
Throughout the past decade , cloud computing has revolutionized the way in which IT infrastructures are designed and deployed . Reliance on in-house data centers has declined as organizations embrace an ‘ X-as-a-Service ’ approach to technology .
This shift has done much to boost agility and support strategies of Digital Transformation . Cloud platforms allow organizations to be much more responsive to changes in market demand and to take advantage of new opportunities as they emerge .
In many instances , IT infrastructures are now built using multiple cloud services . This allows IT teams to select the most appropriate platform for particular applications and tie everything together as a cohesive whole .
However , while these multi-cloud environments deliver significant advantages , they also create new challenges due to their complexity and scale . Applications that span multiple platforms can often comprise millions of lines of code and generate complex interdependencies . It has reached the stage where it is now beyond human capacity to manually monitor these environments and ensure they function at maximum efficiency .
The role of AIOps
To overcome this challenge , organizations are increasingly making use of what is termed Artificial Intelligence for Operations ( AIOps ) platforms . AIOps combines Big Data and Machine Learning tools to automate IT operations and allow developers to focus on more strategic work .
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