Use Docker’s CPU and memory flags to put explicit resource ceilings on an agent, then control its host-file access separately with narrowly scoped mounts. A practical baseline is --cpus for a hard CPU cap, --memory for a hard memory limit, read-only mounts for inputs, and a dedicated writable location only where the agent must save output. These controls depend on host kernel and cgroup support; they do not make an unrestricted Docker daemon safe to expose.
Start with the right Docker controls
Docker documents that, by default, a container has no resource constraints and can use as much of a resource as the host kernel scheduler allows. Resource limits and filesystem permissions solve different problems: CPU and memory flags do not restrict which host files a mounted path exposes, while a read-only mount does not limit resource use.
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The examples below use docker run. Replace agent-image with your image and adjust paths and limits to the workload. No single CPU or memory value is appropriate for every agent; measure the workload and leave host headroom.
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Use --cpus for a hard ceiling
For most workloads, --cpus is the straightforward way to limit CPU time:
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docker run --cpus="1.5" agent-imageDocker’s documented example says that on a two-CPU host, this setting allows the container to use at most 1.5 CPUs. It corresponds to a CPU period of 100,000 microseconds and a quota of 150,000 microseconds. The period normally stays at its 100,000-microsecond default; the quota is the time allowance before the scheduler throttles the container. You can set the underlying values directly with --cpu-period and --cpu-quota, but usually do not need to.
Use --cpuset-cpus to choose eligible cores
Core affinity controls where the container may run, not its overall CPU percentage. For example, --cpuset-cpus="0-3" permits cores 0 through 3, while --cpuset-cpus="1,3" permits cores 1 and 3. Use affinity when placement matters; combine it with --cpus if you also need a hard ceiling.
Do not treat CPU shares as a cap
--cpu-shares assigns a relative weight when containers compete for CPU. It affects priority under contention, but does not reserve a fixed amount or prevent a container from using spare CPU cycles. Choose --cpus when you need a ceiling.
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Apply a hard memory limit
Use --memory (or -m) to set the container’s maximum memory allowance:
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docker run --memory="2g" agent-imageThe value here is an example, not a recommended agent size. Docker documents a minimum accepted memory setting of 6 MB, but a valid minimum is not a practical sizing guide. Measure the agent’s working set under representative use and allow enough headroom for the host and other workloads.
Use a reservation only as a soft threshold
--memory-reservation is a soft limit that applies under memory pressure; it is not a promise that usage will remain below that amount. Set it lower than --memory for the reservation to take precedence. For example:
docker run --memory="2g" --memory-reservation="1g" agent-imageUnderstand the combined memory-and-swap allowance
--memory-swap only has meaning when paired with --memory. A positive value sets the combined memory-plus-swap allowance, not an additional amount of swap. Setting it equal to the memory limit disables swap for the container. If omitted, Docker documents that the container may use swap up to the memory limit in addition to RAM, when host swap is available. A value of zero is treated as unset. Frequent swapping can slow an agent substantially, so choose based on whether you prefer more time to recover under pressure or stricter memory behavior.
Do not use free inside a container as proof of its own swap allowance: it reports host swap, not a reliable container-specific limit.
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Plan for out-of-memory kills
On Linux, when memory is insufficient, the kernel may kill processes. Test the agent’s actual memory needs and size the host and container budget accordingly. Docker warns against disabling OOM killing without also setting a memory limit; disabling it is not a substitute for a defined budget.
Control filesystem access with mounts
Expose only the paths the agent needs
A bind mount gives the container access to a host path and is writable by default. Processes in the container can modify or delete files within a writable mounted path. Avoid broad mounts such as the host root; mount only a specific input or output directory.
For input that should not be changed, mark the mount read-only:
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docker run
--mount type=bind,source="$PWD/input",target=/input,readonly
agent-imageThe agent can read files under /input but cannot write through that mount. A read-only mount narrows this exposure; it does not isolate the container from every other attack surface.
Choose storage based on persistence and host access
| Storage | Can the container write? | Persists after container stops or is removed? | Direct host path access |
|---|---|---|---|
| Bind mount | Yes by default; use readonly or ro for read-only access. |
Host files remain; the mount itself does not define a separate persistence lifecycle. | Yes, it maps a specified host path. |
| Docker volume | Yes by default; volumes can also be mounted read-only. | Designed for persistent data; lifecycle is managed by Docker. | Not as a directly specified host path; Docker manages where volume data resides. |
| tmpfs | Yes, while mounted. | No. Data disappears when the container stops or restarts, or the host reboots. | No persistent host directory is shared. |
Use a volume for persistent or write-intensive container data, a bind mount when direct host/container file sharing is needed, and tmpfs for temporary state that must not persist. If the agent only needs to read a mounted volume, mount it read-only as well.
Make the container filesystem read-only where practical
For a stricter baseline, make the container’s root filesystem read-only if the application supports it, then add narrowly scoped writable locations for required output, cache, or temporary state. Keep inputs read-only and avoid exposing sensitive host directories unnecessarily. Applications that expect to write into their root filesystem may need explicit writable mounts to run correctly.
On Docker Desktop, the daemon runs inside a Linux VM, so a bind mount refers to a path made available to that daemon rather than directly exposing the entire host filesystem. Bind mounts are created on the daemon host; account for that distinction when interpreting host paths.
Combine limits and least-access mounts
This example gives an agent a 1.5-CPU ceiling and a 2 GB memory ceiling, makes its input read-only, and provides a separate writable output directory:
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docker run --rm
--cpus="1.5"
--memory="2g"
--mount type=bind,source="$PWD/input",target=/input,readonly
--mount type=bind,source="$PWD/output",target=/output
agent-imageThese numbers are illustrative. Create the output directory first, and grant the agent only the write access its task requires. Add a memory reservation or explicit swap policy only after deciding how the workload should behave under memory pressure.
Verify that limits are enforceable on the host
Docker’s resource controls depend on kernel support. Check docker info for warnings if a limit is not behaving as expected. In rootless Docker, Docker’s guidance says cgroup-related resource flags such as --cpus and --memory require cgroup v2 and systemd. Without those prerequisites, do not assume the flags provide the intended enforcement.
Namespaces isolate process and network views, while cgroups account for and limit resources; neither makes access to the Docker daemon harmless. A user who can control the daemon may be able to create containers with host filesystem access. Protect daemon/API access and validate container parameters, especially when a service accepts requests to launch agent workloads.
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Docker also documents a docker sbx create command for its agent sandbox feature, with CPU and memory sizing and workspace options such as omitting a workspace bind mount or using a read-only private clone. These options belong to that feature and should not be assumed to exist in every Docker Engine installation. Check the command’s availability and current behavior in Docker’s documentation before building a workflow around it.
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