The heat is on. The tension in the kitchen is tangible as a team of chefs rushes to impress hungry guests on a busy Saturday night. Dozens of ingredients and cooking utensils are strewn across the kitchen, causing confusion and slow preparation. With so much to keep track of, problems are going undetected — as chefs rush to plate their dishes, a pot of soup boils over and leaves a puddle on the floor. The noise is overwhelming as pots and pans sizzle and clash, chefs shout incoming orders, and timers blare in unison. The kitchen is on fire, but each chef must maintain composure to keep customers happy.

A chef preoccupied with tracking down all the ingredients they need may be slower to realize that food is burning on the stove, or that customers across the restaurant are losing their patience over delayed service. Similarly, in the disorganized “kitchen” that is your digital landscape, massive (and growing) data volumes can make you slower to anticipate and notice problems. When your ITOps team can’t study siloed data holistically, you’ll be slower to discover monitoring and troubleshooting issues. If you’re not efficiently collecting, managing, and storing growing data volumes, something is bound to slip through the cracks. This may cause you to miss critical insights hidden within large volumes of data, delaying incident detection and resolution and impacting user experience.