When seconds cost millions: the importance of observability in financial transactions

In an ecosystem of instant payments and seamless digital journeys, the relationship between response time, customer experience, and revenue generation has never been more evident. Downtime is no longer seen merely as a technical problem, but as a financial and strategic risk to the business.

Recent data from the Uptime Institute shows that more than half of significant outages exceed $100,000 in losses, while approximately 20% surpass $1 million per incident. And these numbers are not necessarily associated with complete outages of your applications and infrastructure.

The most frequent scenario is much quieter. Systems continue to operate, but with slowness, intermittency, or partial service degradation. The impact ceases to appear as unavailability and begins to be reflected in abandoned transactions, reduced conversion rates, and direct revenue loss. After all, faced with a slow payment terminal, a PIX payment that takes a long time to confirm, or an unstable checkout process, how many consumers simply abandon the purchase or migrate to another payment method?

At the same time, user behavior has changed. The popularization of instant payments has redefined the concept of speed. Today, speed is no longer enough: the expectation is for immediacy. Delays of a few seconds, often imperceptible from the perspective of the ecosystem between application and infrastructure, are enough to generate friction, compromise trust, and interrupt the customer journey.

This mismatch between consumer expectations and technological complexity creates a structural challenge. A single transaction depends on dozens, and in some cases hundreds, of distributed components, including multi-cloud environments, microservices, APIs, payment gateways, anti-fraud platforms, databases, and integrations with external partners. This architecture enhances scalability and accelerates innovation, but also exponentially increases the surface area for failures.

Recent reports indicate a consistent increase in incidents related to networks, software, and third-party providers, a direct reflection of this growing operational complexity. In this scenario, traditional monitoring approaches are no longer sufficient. Knowing that a server is active or that an application is experiencing high resource utilization no longer answers the main business question: Which service is being impacted, which clients are being affected, and how much is this degradation costing?

It is precisely in this context that observability assumes a strategic role. More than just collecting metrics, it allows for the correlation of logs, metrics, traces, and events in real time to understand the complete behavior of applications.

Combined with open standards such as OpenTelemetry, artificial intelligence, and operational automation, observability transforms large volumes of telemetry into actionable insights, accelerating root cause identification and significantly reducing incident resolution time.

More importantly, it connects technical indicators to business indicators. The discussion is no longer just about the availability of technology environments, but begins to consider financial impact, customer experience, operational risk, and revenue continuity.

This change also transforms how organizations manage their environments. Lack of visibility can result in both wasted resources through oversized infrastructure and operational risks stemming from insufficient capacity at critical times. Observability allows for finding this balance, offering concrete information to optimize performance, resilience, and costs simultaneously.

As digital maturity evolves, so does the number of organizations using observability to prioritize incidents based on financial impact, customer experience, and service criticality—not just isolated operational metrics. According to Gartner, companies that adopt structured observability practices significantly reduce incident resolution time and increase operational resilience, especially in distributed and highly complex environments.

In practice, this represents a paradigm shift. Organizations are moving away from reactive action and towards predictive operation, identifying anomalous behaviors before they translate into perceived customer downtime. High-demand events only make this scenario more evident: they don't create new problems, they merely expose existing limitations. The difference lies in the ability to anticipate.

Companies that operate with low visibility tend to react under pressure, accumulating financial losses, brand damage, and loss of competitiveness. Those that invest in observability, on the other hand, are able to transform complexity into operational intelligence, adjusting their environments in real time, protecting revenue, and sustaining consistent digital experiences even under extreme conditions.

In a market where every second directly influences customer perception and financial results, simply maintaining available systems is no longer enough. The true competitive advantage lies in deeply understanding operational behavior, anticipating risks, and ensuring that every second of the digital journey generates value for the business. It is precisely at this point that observability ceases to be a technological tool and becomes a strategic asset for organizations.

^{(*) Alex Camargo is Head of Observability at Delfia, a curation of digital journeys.}