CI/CD is undergoing its biggest transformation since containers. AI is becoming a participant in every stage of the pipeline, and increasingly, in the developer workflow surrounding it. It’s expanding beyond build-test-deploy to play a foundational role across the entire software creation lifecycle. In this session, we’ll walk through three layers of this evolving, AI-powered CI/CD:

AI coding tools are helping teams produce more features faster, but they are also multiplying what happens after the code is written: more changes to test, more rollout decisions to make and more release risk to manage. Harness’s core thesis is that change is the atomic unit of risk, and as AI increases code volume,

AI and observability tools have given IT teams unprecedented visibility into their environments, but insight alone doesn’t resolve incidents. For most enterprises, the gap between detecting a problem and actually fixing it is still measured in hours, not seconds. And as AI generates more insights than teams can act on, the pressure to automate remediation

In this interactive virtual workshop, platform engineering, DevOps, and SRE teams will walk through a real application performance incident and see how an Agentic AI system investigates it step by step. By correlating telemetry from logs, metrics, and traces, the AI automatically identifies root cause, exposes service dependencies, and guides remediation.

The rapid integration of AI into the software delivery lifecycle has introduced a new era of decentralization and potential information chaos. As AI coding agents and MCP servers accelerate coding speed, traditional, fragmented scanning tools are failing. Without a unified, integrated approach, security teams are losing the critical context needed to distinguish minor alerts from

Imagine you’re the cloud engineer for a fast‑growing startup. Your Terraform code is clean, your AWS environment is stable- until an unexpected failure sends everything into chaos. Suddenly you’re diagnosing issues, repairing infrastructure, and making rapid decisions under pressure. This webinar explores how scenario‑driven, hands‑on cloud challenges help engineers build the instincts and resilience needed

Infrastructure as Code changed how we build and operate systems. It brought consistency, repeatability, and control to infrastructure provisioning. But it also exposed a deeper gap. While infrastructure became programmable, database delivery did not evolve at the same pace. Schema changes, data dependencies, and stateful systems continued to live outside the same system of delivery.

As teams work to deliver cloud infrastructure with greater consistency and confidence, strong Terraform testing practices provide a powerful foundation. This session explores how unit, integration, and security tests—using the Terraform Testing Framework—can bring reliability and clarity to infrastructure‑as‑code workflows. Attendees will learn practical ways to validate resources, modules, and configurations so infrastructure behaves as

Join us to discover how a simple yet powerful GenAI‑driven workflow can give you real‑time awareness into the Terraform resources being deployed across your cloud environments. You’ll learn how to build agentic workflows that let generative AI analyze your infrastructure, apply custom logic, and deliver contextual, actionable insights right when you need them.

What does FinOps really look like in its earliest stages? Not polished dashboards or mature processes—but messy, reactive, and often overlooked. This session explores the reality of getting started, anchored by real stories like a sudden million-dollar AI spend spike that forced FinOps into the spotlight. From unclear ownership to being left out of critical