Greg Eppel

Your operational telemetry is growing faster than your team. Learn how agentic AI can work across your observability stack, correlating metrics, logs, and traces to detect issues, identify root cause, and initiate remediation without waiting for a human to connect the dots.

The promise of AI in software development is clear - faster delivery, fewer incidents, and teams focused on innovation rather than toil. But how do you move beyond isolated AI tools to a coordinated workforce of AI agents that truly transform your SDLC?

When you are faced with an application disruption or operational incident, it is critical to resolve the issue as quickly as possible before it impacts your customers. For modern containerized or serverless applications, this challenge is magnified due to their distributed nature.

Are you confident you can quickly identify service problems and resolve performance issues at scale? Isolating and remediating performance problems in the cloud, particularly with modern, distributed, microservice architectures is challenging.

Setting up the right instrumentation for operational visibility and observability across your enterprise can be complex, costly, and time-consuming, from acquiring the right tool sets to correlating the data between them. In this session, we cover various ways in which you can gain operational visibility and insight into your environment using such services as Amazon CloudWatch, AWS X-Ray, and...

In this session, learn how to easily debug and trace unhandled errors, performance bottlenecks, and customer impact in the distributed nature of a microservices architecture. Please bring your laptop.

In this workshop, we show you how to develop and implement a workload monitoring plan. Learn how to implement and use logs, metrics, dashboards, events, and alarms to quickly and effectively respond to changes in your AWS environment.