Chris Kozlowski

Barclays delivers financial services across a global estate spanning thousands of applications and tens of thousands of servers. As part of a multi-year observability transformation, Barclays is building end-to-end visibility across critical customer journeys while modernizing how telemetry data is collected, managed and operationalized across the enterprise. As data volumes and system complexity continue to grow, Barclays is evolving its observability architecture to improve correlation across telemetry sources, reduce operational overhead, and enable faster decision-making for engineering and operations teams.

AI is accelerating how software gets built, but it’s also raising the stakes on control and reliability. In this session, we explore how teams can move faster without losing sight of risk. As AI reshapes development workflows, the conversation will examine how organizations maintain visibility, enforce standards and ensure systems behave as expected. Speakers will share lessons learned on balancing speed with stability, and what it takes to scale both in modern engineering environments.

In this workshop, follow Amazon best practices to help organizations build a consistent approach to workload monitoring and observability. The goal is to create a strategy that aligns business and operational metrics.