Anticipates latencies and intervenes based on event tracing as part of Elastic Observability.
Realizes the direct impact of applications performance on business processes with Kibana and Canvas.
A leading top-tier French financial services group that operates globally, has improved its performance and operational efficiency through the adoption of Elastic. With a rich history, the institution believes in a mission of protecting assets, financing projects, and protecting clients in their day-to-day lives and professional activities. Like any bank, its success depends on the information systems and applications that are the foundation of the business.
This international bank runs hundreds of applications and websites, continuously adding to this mix to launch new products and provide traders and business clients with the tools they need to manage services.
“When you look at the range of activities, it’s extremely broad,” says the Observability Manager. “It could be financing products specific to assets such as forex trading or fixed income, on the one hand, and then an application used by the IT team to run our systems on the other.”
The bank must constantly monitor the performance of its applications to deliver outstanding client service, protect the business against security breaches, and identify opportunities for innovation. It needed a comprehensive view across its applications to bridge the technical and business layers and ensure end-to-end monitoring. Its legacy application performance monitoring technology prevented the bank from having this level of visibility to be more successful.
Providing a cost-efficient solution to tackle this need, specifically for its internal customers and IT technicians, has been the mission of the Monitoring team. They chose Elastic Observability as their group standard for monitoring - deployed on Elastic Cloud Enterprise (ECE) to provide the comprehensive overview expected across their applications. The manager describes Elastic Observability as a game changer that enables the bank to monitor applications across hybrid architectures, on Microsoft Azure cloud platform, AWS, and on-premise.
Also, Elasticsearch, combined with the Elastic Kibana data visualization interface, delivers an at-a-glance view of how the bank’s applications are performing while, at the same time, triggering actions to the appropriate end user. This benefits the business at multiple levels: from alerting security to possible fraudulent activity to fixing coding issues that result in faster applications and better customer experiences.
The IT team describes how Elastic Observability enables monitoring across the bank's technology ecosystem by defining four fundamental infrastructure layers: hardware, disks, and CPUs; individual apps; application chains; and, ultimately, business processes.
“One of our biggest challenges in the past was demonstrating genuine business value and ROI generated from our IT investments, especially the apps that power the organization. With Elastic, we can trace this value from our hardware all the way to end users, including traders and clients.”
In practice, the bank can now monitor the split-second business processes that make the difference between trading success and failure. For example, application latency can slow the delivery of critical market data to a trader’s desk.
“Elastic Observability allows us to integrate data from the entire application chain, monitor that data, spot latencies, and alert the specific trading desk to the exact trades that could be affected.”
The Global Head of IS Strategy & Architecture states, “We can potentially support 90% of our applications with Elastic. We have all the information in the same place and available in Elasticsearch, and we can visualize it with Kibana. This means we have the same user interface for everything from raw technical data to meaningful business information.”
In the past, the bank used simple metrics monitoring to track the performance of an application. While this often provided quite granular data, it was time-consuming and complicated to apply to every app. Focusing solely on metrics didn’t give the business value they needed to understand the business impact of their applications’ performance.
Since implementing Elastic Observability, the bank has benefited from true event-based monitoring. “Previously, our metrics only provided basic, low-level data from different systems. We were just skimming the surface of what was available,” says the Observability Manager “We also wanted to go beyond just logging data because of the costs associated with processing and enriching the data to make it useful.”
Now, with Elastic, the bank can move to tracing, encompassing a wider, continuous view of an application.
Equally important, Elastic is flexible enough to run its observability clusters on Microsoft Azure, via Elastic Cloud Enterprise (ECE), and on-premises. Deploying on Elastic Cloud Enterprise has also been a key differentiator for the bank. From the start, the monitoring team was looking for a solution that was both cost-efficient and capable of scaling.
“By deploying Elastic Observability on Elastic Cloud Enterprise, we were able to reach a 30% ROI within a year,” says the Observability Manager. Building on this success, the team has ambitious goals for the future. They aim to deploy APM across all their global operations and further leverage Machine Learning capabilities to monitor and optimize all critical applications within the group.
Elastic Consulting Services have also been helping accelerate time to value with on-going remote services and enablement sessions. “The Elastic Consultants are extremely thorough and very efficient. The best practices provided so far during our journey have been invaluable in setting up our large clusters for specific applications,” says the Observability Manager.
Through this training, the team realized the improvement in the speed with which they can now add an app to the Elastic Observability environment. “In the past, adding an app to our monitoring environment would take a few days. Today it can be done in a few minutes,” he says. “This reduction in time and expenses means we can refocus budgets on more business-related activities and benefits.” This results in greater coverage of the bank’s applications, “Up to 40% of the applications that we are now adding to the service were not monitored in the past,” he adds.
Looking forward, the bank is confident that the Elastic deployment will scale to monitor most of their applications. They also plan to add machine learning to analyze application data in Kibana and automatically detect anomalies.
“We are already monitoring more than 800 applications using Elastic which helps my team save between 10% to 30% on their budget and 2 to 5 engineer workdays per application,” he says. “Just as important, it sends a clear message about how monitoring can benefit the entire business, not just the technical function. In the future, we hope to be able to add features such as cross-cluster search and bring these benefits to the majority of our business activities worldwide.”