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Limiting Container Resources with Cgroups

The cgroups (control groups) functionality of the Linux kernel allows you to limit and meter the resources used by a process, or group of processes. Using cgroups you can limit memory and CPU usage. You can also rate limit block IO, network IO, and control access to device nodes.

There are two versions of cgroups in common use. Cgroups v1 sets resource limits for a process within separate hierarchies per resource class. Cgroups v2, the default in newer Linux distributions, implements a unified hierarchy, simplifying the structure of resource limits on processes.

Running {Singularity} Inside a Cgroup

Because {Singularity} starts a container as a simple process, rather than using a daemon, you can limit resource usage by running the singularity command inside an existing cgroup. This is convenient where, for example, a job scheduler uses cgroups to control job limits. By running singularity inside your batch script, your container will respect the limits set by the scheduler on the job's cgroup.

systemd-run

As well as schedulers you can use tools such as systemd-run to create a cgroup, and run {Singularity} inside of it. This is convenient on modern cgroups v2 systems, where the creation of cgroups can be delegated to users through systemd. Without this delegation root privileges are required to create a cgroup.

For example, assuming your system is configured correctly for unprivileged cgroup creation via systemd, you can limit the number of CPUs a container run is allowed to use:

$ systemd-run --user --scope -p AllowedCPUs=1,2 -- singularity run mycontainer.sif
  • --user instructs systemd that we want to run as our own user account.
  • --scope will run our command in an interactive scope that inherits from our environment. By default the command would run as a service, in the background.
  • -p AllowedCPUs=1,2 sets a property on our scope, so that in this case systemd will then setup a cgroup limiting our command to using CPU 1 and 2 only.
  • The double hyphen -- separates options for systemd-run from the actual command we wish to execute. This is important so that systemd-run doesn't capture any flags we might need to pass to singularity.

You can read more about how systemd can control resources uses at the link below, which details the properties you can set using systemd-run.

https://www.freedesktop.org/software/systemd/man/systemd.resource-control.html

Using Singularity to Create a Cgroup

{Singularity} 3.9 and above can directly apply resource limitations to systems configured for both cgroups v1 and the v2 unified hierarchy. Resource limits are specified using a TOML file that represents the resources section of the OCI runtime-spec: https://github.com/opencontainers/runtime-spec/blob/master/config-linux.md#control-groups

On a cgroups v1 system the resources configuration is applied directly. On a cgroups v2 system the configuration is translated and applied to the unified hierarchy.

Under cgroups v1, access restrictions for device nodes are managed directly. Under cgroups v2, the restrictions are applied by attaching eBPF programs that implement the requested access controls.

Note

{Singularity} does not currently support applying native cgroups v2 unified resource limit specifications. Use the cgroups v1 limits, which will be translated to v2 format when applied on a cgroups v2 system.

Examples

To apply resource limits to a container, use the --apply-cgroups flag, which takes a path to a TOML file specifying the cgroups configuration to be applied:

$ sudo singularity shell --apply-cgroups /path/to/cgroups.toml my_container.sif

Note

The --apply-cgroups option can only be used with root privileges.

Limiting Memory

To limit the amount of memory that your container uses to 500MB (524288000 bytes), set a limit value inside the [memory] section of your cgroups TOML file:

[memory]
    limit = 524288000

Start your container, applying the toml file, e.g.:

$ sudo singularity run --apply-cgroups path/to/cgroups.toml library://alpine

After that, you can verify that the container is only using 500MB of memory. This example assumes that there is only one running container. If you are running multiple containers you will find multiple cgroups trees under the singularity directory.

# cgroups v1
$ cat /sys/fs/cgroup/memory/singularity/*/memory.limit_in_bytes
  524288000

# cgroups v2 - note translation of memory.limit_in_bytes -> memory.max
$ cat /sys/fs/cgroup/singularity/*/memory.max
524288000

Limiting CPU

CPU usage can be limited using different strategies, with limits specified in the [cpu] section of the TOML file.

shares

This corresponds to a ratio versus other cgroups with cpu shares. Usually the default value is 1024. That means if you want to allow to use 50% of a single CPU, you will set 512 as value.

[cpu]
    shares = 512

A cgroup can get more than its share of CPU if there are enough idle CPU cycles available in the system, due to the work conserving nature of the scheduler, so a contained process can consume all CPU cycles even with a ratio of 50%. The ratio is only applied when two or more processes conflicts with their needs of CPU cycles.

quota/period

You can enforce hard limits on the CPU cycles a cgroup can consume, so contained processes can't use more than the amount of CPU time set for the cgroup. quota allows you to configure the amount of CPU time that a cgroup can use per period. The default is 100ms (100000us). So if you want to limit amount of CPU time to 20ms during period of 100ms:

[cpu]
    period = 100000
    quota = 20000

cpus/mems

You can also restrict access to specific CPUs (cores) and associated memory nodes by using cpus/mems fields:

[cpu]
    cpus = "0-1"
    mems = "0-1"

Where the container has limited access to CPU 0 and CPU 1.

Note

It's important to set identical values for both cpus and mems.

Limiting IO

To control block device I/O, applying limits to competing container, use the [blockIO] section of the TOML file:

[blockIO]
    weight = 1000
    leafWeight = 1000

weight and leafWeight accept values between 10 and 1000.

weight is the default weight of the group on all the devices until and unless overridden by a per device rule.

leafWeight relates to weight for the purpose of deciding how heavily to weigh tasks in the given cgroup while competing with the cgroup's child cgroups.

To apply limits to specific block devices, you must set configuration for specific device major/minor numbers. For example, to override weight/leafWeight for /dev/loop0 and /dev/loop1 block devices, set limits for device major 7, minor 0 and 1:

[blockIO]
    [[blockIO.weightDevice]]
        major = 7
        minor = 0
        weight = 100
        leafWeight = 50
    [[blockIO.weightDevice]]
        major = 7
        minor = 1
        weight = 100
        leafWeight = 50

You can also limit the IO read/write rate to a specific absolute value, e.g. 16MB per second for the /dev/loop0 block device. The rate is specified in bytes per second.

[blockIO]
    [[blockIO.throttleReadBpsDevice]]
        major = 7
        minor = 0
        rate = 16777216
    [[blockIO.throttleWriteBpsDevice]]
        major = 7
        minor = 0
        rate = 16777216

Limiting Device Access

You can limit read (r), write (w), or creation (c) of devices by a container. Like applying I/O limits to devices, you must use device node major and minor numbers to create rules for specific devices or classes of device.

In this example, a container is configured to only be able to read from or write to /dev/null:

[[devices]]
    access = "rwm"
    allow = false
[[devices]]
    access = "rw"
    allow = true
    major = 1
    minor = 3
    type = "c"

Other limits

{Singularity} can apply all resource limits that are valid in the OCI runtime-spec resources section, except native unified cgroups v2 constraints. Use the cgroups v1 limits, which will be translated to v2 format when applied on a cgroups v1 system.

See https://github.com/opencontainers/runtime-spec/blob/master/config-linux.md#control-groups for information about the available limits. Note that {Singularity} uses TOML format for the confiuration file, rather than JSON.