APIs of BPF Ring Buffer

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The BPF ring buffer (ringbuf) introduces a new and powerful mechanism for efficient data exchange between the Linux kernel and user-space. As a part of the BPF subsystem, the ring buffer provides a flexible and performant solution for transferring data collected by BPF programs. In this blog post, we will explore the semantics and APIs of the BPF ring buffer and understand why it is a significant improvement over other alternatives.


Semantics of the BPF Ring Buffer


The BPF ring buffer is presented to BPF programs as an instance of the BPF map of type BPF_MAP_TYPE_RINGBUF. This design choice offers several advantages over alternative approaches. Initially, the idea of representing an array of ring buffers, similar to BPF_MAP_TYPE_PERF_EVENT_ARRAY, was considered. However, this approach would limit the flexibility of looking up ring buffers using arbitrary keys. To address this concern, the BPF_MAP_TYPE_HASH_OF_MAPS was introduced. This alternative provides the ability to implement various topologies, from a single shared ring buffer for all CPUs to complex applications with hashed or sharded ring buffers.

Another alternative considered was introducing a new concept of a generic “container” object alongside BPF maps. However, this approach would require significant additional infrastructure for observability and verifier support without providing any substantial benefits over using a map. By leveraging the existing BPF map infrastructure, the BPF ring buffer remains familiar to developers, integrates seamlessly with tooling like bpftool, and simplifies the BPF program development process.

Key and value sizes in the BPF ring buffer are enforced to be zero, while the max_entries parameter specifies the size of the ring buffer, which must be a power of 2.


APIs for BPF Ring Buffer


The BPF ring buffer provides two sets of APIs to BPF programs for efficient data transfer.

  1. bpf_ringbuf_output()

The bpf_ringbuf_output() function allows copying data from one place to the ring buffer, similar to bpf_perf_event_output(). While this API incurs an extra memory copy, it is useful when the record size is not known to the verifier beforehand. Additionally, its similarity to bpf_perf_event_output() simplifies the migration process from using perf buffers to the BPF ring buffer.

  1. bpf_ringbuf_reserve()bpf_ringbuf_commit()bpf_ringbuf_discard()

The reservation and commit APIs split the data transfer process into two steps, providing more control and efficient memory usage.

bpf_ringbuf_reserve() reserves a fixed amount of space in the ring buffer. If successful, it returns a pointer to the reserved memory within the ring buffer. BPF programs can then use this pointer similarly to accessing data inside array or hash maps. Unlike bpf_ringbuf_output(), this API avoids the need for extra memory copies, especially when dealing with records larger than the BPF stack space allows. However, it restricts the reserved memory size to a known constant size that the verifier can verify.

Once the BPF program has prepared the data within the reserved memory, it can either bpf_ringbuf_commit() the record or bpf_ringbuf_discard() it. The commit operation marks the record as ready for consumption by the user-space consumer, while the discard operation indicates that the record should be ignored. Discard is useful for advanced use cases, such as ensuring atomic multi-record submissions or emulating temporary memory allocation within a single BPF program invocation.


Querying Ring Buffer Properties and Fine-Grained Control


In addition to the reservation and commit APIs, the BPF ring buffer provides a helper function called bpf_ringbuf_query() that allows querying various properties of the ring buffer. Currently, four properties are supported:

1. BPF_RB_AVAIL_DATA This property returns the amount of unconsumed data currently present in the ring buffer. It provides valuable insights into the data availability and can be used for monitoring and debugging purposes.

2. BPF_RB_RING_SIZE The BPF_RB_RING_SIZE property returns the size of the ring buffer. Knowing the size is essential for efficiently managing data transfer and ensuring optimal performance.

3. BPF_RB_CONS_POS and BPF_RB_PROD_POS These properties return the current logical position of the consumer and producer, respectively. They provide a snapshot of the ring buffer’s state at the moment of querying. However, it’s important to note that these values might change by the time the helper function returns, as the ring buffer’s state is highly changeable. Therefore, these properties are primarily useful for debugging, reporting, or implementing heuristics that consider the dynamic nature of the ring buffer.

One such heuristic involves fine-grained control over poll/epoll notifications regarding new data availability in the ring buffer. By using the BPF_RB_NO_WAKEUPand BPF_RB_FORCE_WAKEUP flags in conjunction with the output/commit/discard helpers, BPF programs gain a high degree of control over notifications. This fine-grained control enables more efficient batched notifications and allows for optimized data consumption. It’s important to note that the default self-balancing strategy of the BPF ring buffer is usually sufficient for most applications, providing reliable and efficient performance out of the box.




The BPF ring buffer introduces a powerful mechanism for efficient data transfer between the Linux kernel and user-space. With its flexible semantics and well-designed APIs, it outperforms other alternatives and provides developers with a high-performance solution for data exchange. The split reservation/commit process and the ability to query ring buffer properties offer fine-grained control and efficient memory usage. By leveraging the BPF map infrastructure and integrating with existing tooling, the BPF ring buffer simplifies development and ensures compatibility with the broader BPF ecosystem. Whether you’re working on real-time analytics, monitoring, or any other data-intensive application, the BPF ring buffer is a valuable tool for achieving optimal performance and scalability in your BPF programs.

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