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Bojan Zivic - V2.AI

From Failure to Success: Architecting Away Cloud Native Anti-Patterns

Abstract

Many organizations struggle with their cloud-native transformations. Applications break unexpectedly, costs spiral out of control, security gaps emerge, and teams become frustrated with complex deployments. The issue isn't the technology, it's the anti-patterns we unknowingly build into our systems.

In this session, drawing from real-world examples in ""Cloud Native Anti-Patterns,"" you'll discover:

Pattern Recognition:

How to identify the most damaging anti-patterns in cloud native architectures Early warning signs that predict system failures

Practical Refactoring Strategies:

Approaches to migrate from anti-patterns to best practices Governance models that prevent anti-patterns from emerging

Building Anti-Pattern-Resistant Systems

Observability patterns that catch problems before they cascade Deployment strategies that minimize blast radius Cultural shifts needed to sustain cloud native success

Speaker Bio

Bojan Zivic is an AWS Ambassador, Serverless AWS Community Builder, and Principal Consultant who has emerged as a prominent voice in the Cloud Native Computing Foundation ecosystem. As co-author of ""Cloud Native Anti-Patterns,"" Bojan champions the CNCF mission of making cloud native ubiquitous through his community leadership and technical expertise. He hosts and organizes the Brisbane Serverless User Group and the Sydney GitHub User Group, fostering cloud native adoption across Australia's tech community. With nine years of experience in IT, Bojan is a passionate advocate for CNCF projects and cloud native patterns. His hands-on expertise spans the entire CNCF landscape, including Kubernetes orchestration, GitOps implementations with ArgoCD, Istio service mesh architectures, and cloud native observability practices. Through his work implementing production-grade CNCF technologies and his dedication to community education, Bojan has established himself as a trusted leader in the cloud native ecosystem.