How KeyBank used the Elastic Stack to build an enterprise monitoring solution

KeyBank, one of the largest banks in the United States, faced challenges with its decentralized monitoring systems, which resulted in slow issue resolution and performance-based customer loss. To address these issues, KeyBank adopted the Elastic Stack, deploying tools like Winlogbeat and Metricbeat across its network to gather log and metric data. This shift provided critical insights, revealing root causes such as high disk I/O and low memory. As the visibility into their systems improved, KeyBank undertook a system-wide refresh and continued to refine its architecture to handle growing data volumes without downtime. The iterative scaling approach, supported by Elasticsearch's horizontal architecture, enabled KeyBank to achieve rapid data ingestion and meet their service level agreements effectively. The transition not only improved system performance but also resulted in significant cost savings, illustrating the value of centralized data observability.

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