Jul 01 2026
Management

Q&A: Splunk Expert Explains How Financial Institutions Can Get Started With Observability

While traditional monitoring notifies when a system is down, observability explains why to ensure customer services aren’t impacted.

Financial services need to maintain the ability to conduct high-speed transactions across complex ecosystems. In the past, to minimize downtime, financial institutions often used separate tools for reactive alerting; manual root-cause analysis; and logs, metrics and application performance management. Today, observability allows for correlated telemetry across systems, automated root-cause insights, and business-level visibility with anomaly detection powered by artificial intelligence.

Observability is also converging with security to detect threats faster and reduce tool sprawl. However, the amount of data created, existing tool sprawl, legacy systems and skills gaps can make it challenging for financial institutions to upgrade from traditional monitoring to modern observability.

BizTech spoke with Greg Leffler, director of developer evangelism and lead evangelist for observability at Splunk, about what financial services institutions (FSIs) need to know about observability — including benefits, obstacles and best practices — to ensure their program reduces burden on IT and security teams while maintaining compliance.

DISCOVER: Get a how-to guide for building observability that drives clear actions.

BIZTECH: What is observability, and how does it differ from monitoring?

LEFFLER: Observability is the ability to measure a system’s internal states by examining its outputs, specifically, the telemetry data (metrics, logs and traces) generated across applications, infrastructure and networks. It lets you answer questions about your entire business using data.

While traditional monitoring simply tells you when a system is down, observability tells you why. It moves systems from a reactive posture to a proactive one. Financial institutions can use an observability practice to detect and remediate issues before they impact services for customers.

BIZTECH: How do you define “full-stack observability” in the context of banking?

LEFFLER: While banking has always been a complex industry, today’s increasingly digital landscape adds an entirely new layer of complexity. To stay competitive, banks have to adopt modern engineering methods, running huge numbers of microservices and adopting new features which require various AI models and cloud infrastructure. A comprehensive observability practice provides a unified view of the entire digital half of the banking business, which is critical to business success. This includes every digital function such as payments, fraud detection, customer authentication and loan origination. 

Unlike traditional monitoring, end-to-end observability gives banks a full picture of telemetry across every component of their IT environment and beyond. Increasingly, financial services applications integrate third-party services such as fraud detection, payment processing and device integrity. This makes it exponentially easier to proactively identify the most critical components and address issues as they arise, thereby limiting their impact on customers.

With end-to-end observability, financial institutions can discover the effect that these third-party dependencies, customer ISPs, etc., have on overall customer experience and business health.

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BIZTECH: What are the benefits of observability for financial institutions?

LEFFLER: Today’s banking customers expect an always-available digital experience that gives them seamless access to their money whenever they need it, and if they don’t get it from you, there’s a competitor only a tap away. A strong observability practice helps banks stay ahead of the costly outages and performance issues that can disrupt customer trust and experience.

With a comprehensive observability practice, banks also gain a stronger resilience posture — enabling teams to identify, respond to and recover from incidents faster. They also are able to prioritize IT response. It’s impossible to respond to everything at the same time. Using observability lets banks prioritize response based on business impact. Leading organizations are already seeing the impact: According to Splunk’s 2025 State of Observability Report, 65% of practitioners say their observability practice is positively impacting revenue. As digital banking expectations continue to rise, observability is becoming a critical business driver, not just an IT function.

BIZTECH: What are some common obstacles financial services institutions face related to observability?

LEFFLER: A challenge that financial services institutions may face is tool sprawl. Many organizations operate across a mix of on-premises and cloud environments, often relying on separate monitoring and observability tools for each. This creates fragmented visibility and makes it difficult to gain a unified view of the entire IT environment, or to prioritize issues based on the impact they have to the bottom line. Overcoming tool sprawl starts with consolidating data and workflows into a centralized observability strategy that can provide consistent visibility across systems, regardless of where applications or infrastructure reside.

Another common issue is alert fatigue. IT teams are often overwhelmed by large volumes of alerts, many of which may not be critical, increasing the risk that high-priority issues get overlooked. With an AI-powered comprehensive observability practice, banks can unify visibility across environments and use intelligent automation to help surface and prioritize the alerts that matter most to the business.

DISCOVER: Follow this how-to guide for building observability that drives clear actions.

BIZTECH: What are some best practices for establishing an observability practice at an FSI?

LEFFLER: There is no one-size-fits-all approach to observability for financial services institutions. Leaders need to implement an observability practice and strategy that best fits the unique needs and complexity of their business. 

That said, in general, teams should standardize on OpenTelemetry to create a vendor-neutral foundation that supports visibility across increasingly complex hybrid IT environments. This not only improves interoperability across tools and teams but also helps streamline operations and improve customer outcomes. It also makes sure that the instrumentation work only needs to be done once, enabling FSIs to choose the right observability tooling without the concern of vendor lock-in.

Reducing alert noise is another critical priority. Too many low-value alerts can overwhelm IT teams and contribute to alert fatigue, making it harder to quickly identify and respond to the issues that matter most. By prioritizing high-impact alerts, institutions can maximize IT resources and give teams more time to focus on strategic initiatives instead of reactive troubleshooting. FSIs must adopt tooling that can tie alerts to business impact and use this data to prioritize response and reduce the effects of alert fatigue.

Finally, financial institutions should take a deliberate approach to introducing AI into their observability practice. Starting with lower-risk use cases — such as alert triage, correlation and root cause analysis — allows teams to build trust in AI over time. When implemented thoughtfully, AI can help empower IT teams with faster insights and greater efficiency, enabling them to operate more proactively and resiliently. There are many concerns around AI usage, especially in a regulated industry like FSI, but it’s absolutely critical to develop a plan and start adoption to reduce the risk of being left behind.

BIZTECH: How does observability help financial institutions achieve security and compliance goals?

LEFFLER: In financial services, security and compliance need to operate in lockstep, and observability provides the visibility and guardrails to support both. It helps institutions detect risk earlier, maintain control across complex environments, and ensure consistent adherence to policies and regulations — while also reinforcing tighter collaboration between security and compliance teams. According to the State of Observability report, 64% of teams that work across both functions report fewer application and infrastructure performance issues, highlighting the value of this unified approach.

As AI becomes more embedded in financial workflows, observability also plays a critical role in ensuring use cases like fraud detection, credit scoring and customer-facing AI services remain transparent, auditable and compliant with evolving regulations.

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BIZTECH: What role does observability play in supporting banking modernization efforts?

LEFFLER: Before modernization can streamline and bring simplicity, it brings complexity. Each new API, AI-powered service and integration brings with it a set of variables that can affect your IT architecture in various ways. Observability promotes architectural integrity as you move from complexity to simplicity.

For example, many banks have to operate in a hybrid IT environment to simultaneously meet business scale requirements and strict regulatory requirements. Sometimes, this can materialize as the coexistence of decade-old legacy systems and modern microservices. Due to the disparate nature of this infrastructure, there can be blind spots within IT architecture. Observability removes those blind spots, thereby allowing modernization to create new opportunities without creating new liabilities. Support for what some consider “legacy” technology that powers millions of transactions a day (e.g. mainframes) has been something that some observability vendors have ignored, but thanks to the community-driven nature of OpenTelemetry, this support gets better every day, including new enhanced support for IBM Z.

Observability also is powering board-level initiatives such as revenue forecasting and customer experience strategy. Observability makes product roadmaps clearer and promotes alignment as product development begins. A comprehensive observability practice is the thread that ties together the health of the tech stack with the business performance of financial institutions. Being able to determine how IT changes impact customer satisfaction, business health and revenue is a game changer for FSI.

BIZTECH: Is there anything we haven’t covered that you think would be useful for financial institutions to know about observability?

LEFFLER: Financial institutions have a great opportunity to lean more into agentic observability. Boards and customer experience teams expect adoption of AI in customer-facing roles, such as chatbots.

To further explain, when chatbots fail, they tend to go quietly. They degrade slowly and subtly. As a result, the observability necessary to track this slow failure (e.g. degraded quality, cost and trust signals) must exist in addition to tracking more traditional availability golden signals. Agentic observability can not only help track essential new metrics but also begin remediation processes if necessary.

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