In this interview, Swapnil Bhartiya speaks with Yaron Schneider, Co-Creator of Dapr, about building resilient and autonomous AI agents on Kubernetes. Unlike many experimental frameworks, Dapr Agent extends the battle-tested Dapr workflows to ensure durability, fault tolerance, and seamless rehydration—even across pod or cluster failures. Schneider shares insights into how developers are automating DevOps, customer support, and CI/CD workflows, while bridging CNCF-native tooling with AI workloads. Learn how Dapr Agent is paving the way for production-grade agentic systems.
In this interview, learn about:
What makes Dapr unique in the CNCF ecosystem for application developers
How Dapr Agents provides durability and resilience that other AI frameworks lack
Real-world use cases from DevOps automation to customer success
The pain points that led to Dapr Agents’ creation
Community feedback and future roadmap including Anthropic MCP integration
Plans for C# and Java support beyond Python
Whether you’re a developer looking to build production-ready AI agents or interested in the intersection of AI and cloud-native technologies, this interview provides essential insights into the future of autonomous AI systems on Kubernetes.
Hashtags: #Dapr #AI #Kubernetes #CloudNative #CNCF #Agents #DevOps #MachineLearning #Containers #OpenSource
