// ITS FOSS — LINUX & OPEN SOURCE
Beyond AI Applications: How openEuler Is Rethinking the Agentic Infra OS
Traditional operating systems are designed primarily to manage computing resources, including CPU scheduling, memory allocation, storage, networking, and application execution.
Agentic AI introduces another layer of complexity: infrastructure must also support the lifecycle of intelligent agents.
This includes agent deployment, task scheduling, execution isolation, context management, memory retrieval, tool invocation, observability, and recovery.
openEuler is embracing the shift toward agentic infrastructure and evolving its OS capabilities to support the development, deployment, execution, coordination, and optimization of agents across heterogeneous computing environments.
This is what they are discussing at the currently ongoing Agentic Infra OS Conference & openEuler Summit 2026.
AI agents are moving beyond conversation to execute code, call tools, interact with applications, and coordinate multi-step workflows. As these workloads scale, infrastructure faces a new set of challenges: secure execution, fast environment provisioning, efficient context reuse, persistent memory, and elastic resource management.
Traditional infrastructure was not designed around these requirements. The next evolution of the operating system must go beyond managing processes and hardware resources to support the full lifecycle of agent execution.
This is the direction behind openEuler's agentic OS: building an open, secure, and efficient software stack that connects operating system capabilities with agent runtimes, AI frameworks, data services, and heterogeneous computing resources.
The infrastructure is designed to operate across diverse computing architectures, including general-purpose processors such as x86, Arm, RISC-V, and LoongArch, as well as AI accelerators from multiple vendors. This heterogeneous approach is important because enterprise AI deployments rarely operate on a single hardware architecture or accelerator platform.
The architecture is centered on two layers: Agent Kernel, which provides foundational system-level capabilities, and Agent Service, which exposes reusable services such as secure sandboxing, memory, session management, and Tool Gateway. Around this foundation, complementary infrastructure technologies—including distributed caching and serverless data services—help support the performance, scalability, and data requirements of agent workloads.