To power their customer intelligence products, Zeotap uses Apache Spark to run big data processes. However, as Zeotap’s client base grew, and their Spark usage intensified, they experienced laggy performance and increased spending.
For Zeotap, visibility into their big data infrastructure was a major concern. The company had previously leveraged SparkLens to gain some degree of visibility and generate data visualizations. However, linking data across multiple clusters and workflows and monitoring multiple jobs was proving to be very difficult.
In this case study, we explore how Pepperdata helped Zeotap improve their big data performance and cut down their spending. Interested in how the Pepperdata solution executed all of this? Download the case study now to read the details.
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