Wells Fargo Turns Data Overload Into Business Opportunities With Elastic Observability

Data plays a key role in enabling enterprises to make informed business decisions, however, it can also create challenges such as data sprawl. This happens when an organization’s data grows rapidly and becomes dispersed across various applications, systems, and storage locations. Such issues prevent enterprises from extracting the full benefits from their data. 

To help overcome such challenges, Elastic, a leading platform for search-powered solutions, offers a distributed tracing solution – Elastic Observability. It helps monitor data health and performance across complex technology infrastructure. This is what helped Wells Fargo turn data overload into business opportunities. 

One of the four largest banks in the U.S., Wells Fargo, has had remarkable success by deploying Elastic Observability to better observe its financial transactions through distributed tracing. The solution enabled the bank to follow user requests at every stage of its journey through its complex services and systems. 

One of the goals of the the Digital Technology and Innovation team at Wells Fargo is to monitor the customer-facing applications to help ensure maximum availability and performance of IT infrastructure. Being able to quickly identify issues allows end-to-end visibility of all financial transactions. This also allows the bank to report on risk in near real-time. 

As Wells Fargo’s IT infrastructure has evolved, so has the complexity of the systems and applications. This created the need for using observability solutions that can gather and monitor information. 

Joe Korchmar, Distinguished Engineer, Wells Fargo, and his team were responsible for picking the most suitable observability solution. Explaining his reasoning for selecting Elastic, Korchmar shared that Well Fargo required a solution that had an open architecture, offered compliance with modern industry standards, such as the W3C Trace Content, and allowed Well Fargo to own its data. 

In addition to meeting those requirements, Elastic Observability also offered tools to capture 100 percent of application traces and the unique ability to add extensions to the schema, such as payment information and customer numbers. This made the Elastic solution the ideal choice for Wells Fargo. 

Using Elastic Observability allowed Korshmar and his team to monitor and analyze application flows in near real-time to quickly identify root causes, slow performing code, and resolve issues faster. 

(Immersion Imagery/Shutterstock)

The addition of Elastic Obversabulty aligns well with Wells Fargo’s plans to migrate to a multi-cloud environment over the next decade. With its flexible deployment options, the ability to perform federated search across clusters in the data center or cloud, and data lifecycle management capabilities,  Elastic Observabitly is a solid long-term solution for a multi-cloud environment.  

“As we extend the implementation of Elastic, we are getting closer to complete observability across the enterprise, which brings benefits to all our lines of business. This will allow us to continue to improve application availability, customer response, and mean time to recover.” said Korchmar.

One of the first use cases for this solution is the banks’ login and payment systems. The Elastic Professional Services helped accelerate the deployment into successful production. According to Korchmar, Elastic Observability has enabled his team to focus on “areas that have the greatest impact on the bank’s operating costs and revenues.”  

With the deployment of the Elastic distributed tracing platform, Well Fargo has positioned itself to meet its digital transformation goals and offer solutions that can optimize finances and business performance for customers. 

Related Items

Case Study: How a Top Bank Saved $50M by Automating Data Access Controls

Wells Fargo’s New Virtual Assistant to Be Powered by Google Cloud AI

Consumer Watchdog Report: Wall Street AI Could Cause Financial Crisis