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Block device IO engine

For all Firecracker versions prior to v1.0.0, the emulated block device uses a synchronous IO engine for executing the device requests, based on blocking system calls.

Firecracker 1.0.0 adds support for an asynchronous block device IO engine. Support is currently in developer preview. See this section for more info.

The Async engine leverages io_uring for executing requests in an async manner, therefore getting overall higher throughput by taking better advantage of the block device hardware, which typically supports queue depths greater than 1.

The block IO engine is configured via the PUT /drives API call (pre-boot only), with the io_engine field taking two possible values:

The Sync variant is the default, in order to provide backwards compatibility with older Firecracker versions.

Example configuration

curl --unix-socket ${socket} -i \
     -X PUT "http://localhost/drives/rootfs" \
     -H "accept: application/json" \
     -H "Content-Type: application/json" \
     -d "{
             \"drive_id\": \"rootfs\",
             \"path_on_host\": \"${drive_path}\",
             \"is_root_device\": true,
             \"is_read_only\": false,
             \"io_engine\": \"Sync\"
         }"

Host requirements

Firecracker requires a minimum host kernel version of 5.10.51 for the Async IO engine.

This requirement is based on the availability of the io_uring subsystem, as well as a couple of features and bugfixes that were added in newer kernel versions.

If a block device is configured with the Async io_engine on a host kernel older than 5.10.51, the API call will return a 400 Bad Request, with a suggestive error message.

Performance considerations

The performance is strictly tied to the host kernel version. The gathered data may not be relevant for modified/newer kernels than 5.10.

Device creation

When using the Async variant, there is added latency on device creation (up to ~110 ms), caused by the extra io_uring system calls performed by Firecracker. This translates to higher latencies on either of these operations:

  • API call duration for block device config
  • Boot time for VMs started via JSON config files
  • Snapshot restore time

For use-cases where the lowest latency on the aforementioned operations is desired, it is recommended to use the Sync IO engine.

Block IOPS and efficiency

The Async engine performance potential is showcased when the block device backing files are placed on a physical disk that supports efficient parallel execution of requests, like an NVME drive. It's also recommended to evenly distribute the backing files across the available drives of a host, to limit contention in high-density scenarios.

The performance measurements we've done were made on NVME drives, and we've discovered that:

For read workloads which operate on data that is not present in the host page cache, the performance improvement for Async is about 1.5x-3x in overall efficiency (IOPS per CPU load) and up to 30x in total IOPS.

For write workloads, the Async engine brings an improvement of about 20-45% in total IOPS but performs worse than the Sync engine in total efficiency (IOPS per CPU load). This means that while Firecracker will achieve better performance, it will be at the cost of consuming more CPU for the kernel workers. In this case, the VMM cpu load is also reduced, which should translate into performance increase in hybrid workloads (block+net+vsock).

Whether or not using the Async engine is a good idea performance-wise depends on the workloads and the amount of spare CPU available on a host. According to our NVME experiments, io_uring will always bring performance improvements (granted that there are enough available CPU resources).

It is recommended that users perform some tests with examples of expected workloads and measure the efficiency as (IOPS/CPU load).

Developer preview status

View the release policy for information about developer preview terminology.

The Async io_engine is not yet suitable for production use. It will be made available for production once Firecracker has support for a host kernel that implements mitigation mechanisms for the following threats:

Threat 1: PID exhaustion

The number of io_uring kernel workers assigned to one Firecracker block device is upper-bounded by:

(1 + NUMA_COUNT * min(size_of_ring, 4 * NUMBER_OF_CPUS)

This formula is derived from the 5.10 linux kernel code, while size_of_ring is hardcoded to 128 in Firecracker.

Depending on the number of microVMs that can concurrently live on a host and the number of block devices configured for each microVM, the kernel PID limit may be reached, resulting in failure to create any new process.

Kernels starting with 5.15 expose a configuration option for customising this upper bound. Once possible, we plan on exposing this in the Firecracker drive configuration interface.

Threat 2: worker thread resource consumption

The io_uring kernel workers are spawned in the root cgroup of the system. They don’t inherit the Firecracker cgroup, cannot be moved out of the root cgroup and their names don't contain any information about the microVM's PID. This makes it impossible to attribute a worker to a specific Firecracker VM and limit the CPU and memory consumption of said workers via cgroups.

Starting with kernel 5.12 (currently unsupported), the Firecracker cgroup is inherited by the io_uring workers.

Path to GA

We plan on marking the Async engine as production ready once an LTS linux kernel including mitigations for the aforementioned mitigations is released and support for it is added in Firecracker.

Read more about Firecracker's kernel support policy.