resources Block
Placement | job -> group -> task -> resources |
The resources
block describes the requirements a task needs to execute.
Resource requirements include memory, CPU, and more.
job "docs" {
group "example" {
task "server" {
resources {
cpu = 100
memory = 256
device "nvidia/gpu" {
count = 2
}
}
}
}
}
resources
Parameters
cpu
(int: 100)
- Specifies the CPU required to run this task in MHz.cores
(
- Specifies the number of CPU cores to reserve specifically for the task. This may not be used withint
: <optional>)cpu
. The behavior of settingcores
is specific to each task driver (e.g. docker, exec).memory
(int: 300)
- Specifies the memory required in MB.memory_max
(
- Optionally, specifies the maximum memory the task may use, if the client has excess memory capacity, in MB. See Memory Oversubscription for more details.int
: <optional>)numa
(Numa: <optional>)
- Specifies the NUMA scheduling preference for the task. Requires the use ofcores
.device
(Device: <optional>)
- Specifies the device requirements. This may be repeated to request multiple device types.
resources
Examples
The following examples only show the resources
blocks. Remember that the
resources
block is only valid in the placements listed above.
Cores
This example specifies that the task requires 2 reserved cores. With this block, Nomad will find
a client with enough spare capacity to reserve 2 cores exclusively for the task. Unlike the cpu
field, the
task will not share cpu time with any other tasks managed by Nomad on the client.
resources {
cores = 2
}
If cores
and cpu
are both defined in the same resource block, validation of the job will fail.
Memory
This example specifies the task requires 2 GB of RAM to operate. 2 GB is the equivalent of 2000 MB:
resources {
memory = 2000
}
Devices
This example shows a device constraints as specified in the device block which require two nvidia GPUs to be made available:
resources {
device "nvidia/gpu" {
count = 2
}
}
Memory Oversubscription
Setting task memory limits requires balancing the risk of interrupting tasks against the risk of wasting resources. If a task memory limit is set too low, the task may exceed the limit and be interrupted; if the task memory is too high, the cluster is left underutilized.
To help maximize cluster memory utilization while allowing a safety margin for unexpected load spikes, Nomad allows job authors to set two separate memory limits:
memory
: the reserve limit to represent the task’s typical memory usage — this number is used by the Nomad scheduler to reserve and place the taskmemory_max
: the maximum memory the task may use, if the client has excess available memory, and may be terminated if it exceeds
If a client's memory becomes contended or low, the operating system will pressure the running tasks to free up memory. If the contention persists, Nomad may kill oversubscribed tasks and reschedule them to other clients. The exact mechanism for memory pressure is specific to the task driver, operating system, and application runtime.
The memory_max
limit attribute is currently supported by the official
raw_exec
, docker
, exec
, and java
task drivers. Consult the
documentation of community-supported task drivers for their memory
oversubscription support.
Memory oversubscription is opt-in. Nomad operators can enable Memory Oversubscription in the scheduler configuration. Enterprise customers can use Resource Quotas to limit the memory oversubscription and enable or disable memory oversubscription per node pool.
To avoid degrading the cluster experience, we recommend examining and monitoring resource utilization and considering the following suggestions:
Set
oom_score_adj
for Linux host services that aren't managed by Nomad, e.g. Docker, logging services, and the Nomad agent itself. For Systemd services, you can use theOOMScoreAdj
field.Monitor hosts for memory utilization and set alerts on Out-Of-Memory errors
Set the client
reserved
with enough memory for host services that aren't managed by Nomad as well as a buffer for the memory excess. For example, if the client reserved memory is 1GB, the allocations on the host may exceed their soft memory limit by almost 1GB in aggregate before the memory becomes contended and allocations get killed.