Data traffic rates over network backbones have increased significantly over the past several years. Fueled by the increasing demand of Internet of things (IoT) devices which continue to be more readily integrated with our daily lives, both domestically and commercially, the average annual volume of data/ information created has almost doubled over the past two years, from 41 zettabytes in 2019 to 79 zettabytes in 2021, with a forecast of growth to 181 zettabytes by 2025 (Statista, 2021).
DevOps by the numbers - what metrics should you be keeping an eye on?
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The importance of classifying analytics
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Not all analytics are created equal
Not all analytics are created equal
Aligning the right metrics to the right use case allows for timelier reporting and reduces application risk. Credit: Dreamstime
Analytics are core to all modern software-as-a-service (SaaS) applications. There is no way to successfully operate a SaaS application without monitoring how it is performing, what it’s doing internally, and how successful it is at accomplishing its goals.
However, there are many types of analytics that modern applications need to monitor and examine. The purpose, value, accuracy, and reliability of those analytics vary greatly depending on how they are measured, how they are used, and who makes use of them.
Not all analytics are created equal
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