A multinational investment bank was growing at an exponential rate, thanks to its hybrid cloud-based Hadoop data analytics platform supporting and feeding all its global operations with valuable, actionable insights. Data was obviously driving its growth. However, this influx of data soon became a problem for the bank. In this case study, we share how Pepperdata helped them overcome the challenge. Fill out the form to download it now, or keep reading for more.
The Challenge: More Data, More Spend
The trouble began as soon as the volume of ingested data started doubling year after year. To handle this massive surge of data, the bank had to scale its data infrastructure up to enhance its capabilities and add extra compute resources to keep the platform going at an optimal rate. Since this was a hybrid setup, the bank also had to deal with costs associated with a physical, on-premise data center: maintenance, climate control, support, security, and real estate.
As soon as management scaled up and expanded its IT infrastructure, the bank was quickly confronted with a huge increase in their cloud and data expenses. As much as data was imperative in driving their growth, the banking firm realized they needed to quickly keep their costs manageable lest everything spirals out of control.
The Solution: Performance and Cost Optimization Through Pepperdata
The Fortune 100 bank turned to Pepperdata to help them prevent their IT infrastructure spending from becoming a serious runaway problem.
With Pepperdata, the company found a more effective way to look into their data infrastructure, scale automatically, and optimize workload performance while still meeting business-critical SLAs and keeping their cloud spend under total control. Soon after, the bank achieved a 30% increase in server utilization and capacity, equivalent to hundreds of nodes.
Interested in how the Pepperdata solution did it? Download the case study now to read the details.