Introduction
At the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit, Chris Li opened his memory-management-track session with a critical observation: the kernel's control-group (cgroups) subsystem works well for resource management, but falls short for other use cases. His proposed enhancement, called policy groups, aims to address these shortcomings—though a consensus on the feature's final shape remains elusive.
The Role of Control Groups
Control groups (cgroups) are a fundamental Linux kernel feature that allows administrators to allocate, prioritize, and manage system resources among processes. They excel in hierarchical resource partitioning—for example, limiting CPU or memory usage for a set of containers. However, as Li explained, cgroups were primarily designed for resource control, not for implementing flexible, fine-grained memory management policies that modern workloads demand.
Shortcomings in Memory Management
Li identified several pain points with using cgroups for advanced memory management:
- Rigid hierarchy: Cgroups require a strict parent-child tree structure, which can be overly restrictive for complex, multi-tenant environments where policies need to overlap or be applied dynamically.
- Limited policy granularity: Existing cgroup interfaces provide memory limits and pressure notifications, but lack native support for more nuanced policies such as proportional allocation, priority-based reclaim, or adaptive throttling.
- Integration challenges: External tools and userspace daemons often have to implement custom logic to enforce policies that cgroups cannot express directly, leading to duplication and maintenance overhead.
These shortcomings become acute in data-intensive applications, virtualized environments, and real-time systems where memory behavior must be fine-tuned.
Policy Groups: A Proposed Solution
To overcome these limitations, Li presented policy groups—a new kernel abstraction that builds on cgroups but extends them with programmable policy support. Key features include:
- Flexible grouping: Policy groups allow overlapping membership, meaning a process can belong to multiple policy groups simultaneously, each enforcing different aspects of memory behavior.
- Policy rules engine: Instead of static limits, policy groups define rules that the kernel interprets at runtime. For example, a rule could state: "If memory pressure exceeds 80%, reclaim from group A before group B."
- Userspace collaboration: Policy groups provide a well-defined API for userspace daemons to register policies and receive feedback, enabling adaptive strategies without kernel modifications.
Li demonstrated a prototype where policy groups improved memory utilization in a container orchestrator by 15% compared to pure cgroup limits, by dynamically balancing memory across containers based on QoS classes.
The Road Ahead: Challenges and Discussions
Despite the promising results, the proposal sparked lively debate in the summit session. Several developers expressed concerns:
- Complexity vs. benefit: Adding a new subsystem could bloat the kernel and create competition with existing cgroup controllers. Some argued that existing pressure-stall information (PSI) and proactive reclaim mechanisms could be extended instead.
- Performance overhead: Runtime policy evaluation might introduce latency, especially on fast memory paths. Li acknowledged this and suggested caching compiled policies.
- Security and isolation: Overlapping groups could accidentally leak information about memory usage patterns between tenants. Li proposed using per-policy access controls and audit logging.
By the end of the session, no clear consensus emerged. Attendees agreed that more prototyping, performance benchmarking, and community discussion are needed before policy groups can be considered for mainline inclusion.
Conclusion
Chris Li's policy groups concept offers a compelling vision for making Linux memory management more adaptable and programmable. While the road to consensus is long, the conversation at the 2026 Summit has already started to shape how the kernel community might evolve cgroups to meet the demands of next-generation workloads. As Li concluded, "The current model is good enough for many, but not for all. We need to keep pushing boundaries."