Cgroups - Deep Dive into Resource Management in Kubernetes

There's a lot of "magic" that happens behind the scenes to make whole Kubernetes work. One of those is resource management and resource allocation done by Linux cgroups.

In this article we will take a deep dive into what cgroups are, how Kubernetes uses them to manage Node resources, and how we can take advantage of them beyond setting resource requests and limits on Pods.

What are Cgroups?

First things first - What are cgroups anyway? - Control Groups, or cgroups for short, are a Linux kernel feature that takes care of resource allocation (CPU time, memory, network bandwidth, I/O), prioritization and accounting (aka how much is container using?). Additionally, besides being a Linux primitive, cgroups are also a building block of containers, so without cgroups there would be no containers.

As the name implies - the cgroups are groups, so they group processes in parent-child hierarchy, which forms a tree. So, if - for example - parent cgroup is assigned 128Mi of RAM, then sum of RAM usage of all of its children cannot exceed 128Mi.

This hierarchy lives in /sys/fs/cgroup/, which is the cgroup filesystem (cgroupfs). There you will find sub-trees for all Linux processes. Here we're interested in how cgroups impact scheduling and resources assigned/allocated to our Kubernetes Pods, so the part we care about is kubepods.slice/:

└── kubepods.slice/
    ├── kubepods-besteffort.slice/
    │   └── ...
    ├── kubepods-guaranteed.slice/
    │   └── ...
    └── kubepods-burstable.slice/
        └── kubepods-burstable-pod<SOME_ID>.slice/
            ├── crio-<CONTAINER_ONE_ID>.scope/
            │   ├── cpu.weight
            │   ├── cpu.max
            │   ├── memory.min
            │   └── memory.max
            └── crio-<CONTAINER_TWO_ID>.scope/
                ├── cpu.weight
                ├── cpu.max
                ├── memory.min
                └── memory.max

All the Kubernetes cgroups are located in kubepods.slice/ subdirectory, which has further kubepods-besteffort.slice/, kubepods-burstable.slice/ and kubepods-guaranteed.slice/ subdirectories for each QoS (Quality-of-Service) type. Under these directories you will find directories for each Pod and inside those, further directories for each container.

At each level there are files such as cpu.weight or cpu.max that specify how much of the particular resource - e.g. CPU - can this group use. For clarity, the above file-tree only shows these files at the deepest level.

Finally, here at leaves of tree are the files that describe how much memory (memory.min and memory.max), CPU (cpu.weight and cpu.max) or other resources each container gets to work with. These files are a direct translation of the resource requests and limits defined in Pod manifests. However, if you were to look at these files, the values you would find there actually don't seem related to the requests and limits, so what do they mean and how did they get there?

How Does It Work?

Let's now walk through all the steps to better understand how the Pod requests and limits get translated/propagated all the way to files in /sys/fs/....

We begin with simple Pod definition that includes memory and CPU requests/limits:

# kubectl apply -f pod.yaml
apiVersion: v1
kind: Pod
    run: webserver
  name: webserver
  - image: nginx
    name: webserver
        memory: "64Mi"
        cpu: "250m"
        memory: "128Mi"
        cpu: "500m"

When we create/apply this Pod manifest, the Pod gets assigned to a Node and the kubelet on the Node takes this PodSpec and passes it to Container Runtime Interface (CRI), e.g. containerd or CRI-O, which translates it to lower level OCI JSON spec that describes the container that will be created:

  "status": {
    "id": "d94159cf8228addd7a29beaa3f59794799e0f3f65e856af2cb6389704772ffee",
    "metadata": {
      "name": "webserver"
    "image": {
      "image": ""
    "imageRef": ""
  "info": {
    "runtimeSpec": {
      "hostname": "webserver",
      "linux": {
        "resources": {
          "memory": {
            "limit": 134217728,
            "swap": 134217728
          "cpu": {
            "shares": 256,
            "quota": 50000,
            "period": 100000
          "pids": { "limit": 0 },
          "hugepageLimits": [{ "pageSize": "2MB", "limit": 0 }],
            "memory.high": "107374182",
            "memory.min": "67108864"

As you can see from the above, this spec includes cgroupsPath which is the directory where the cgroup files will be located. It also includes the already translated requests and limits under the info.runtimeSpec.linux.resources (we will talk about what these means a bit later).

This spec is then passed to lower-level OCI container runtime - most likely runc - which talks to systemd driver which creates systemd scope unit and also sets values in the files in cgroupfs.

To first inspect the systemd scope unit:

# Find the container ID:
crictl ps
029d006435420  ...    6 minutes ago  Running  webserver  0        72d13807f0ab1  webserver

# Find the slice and scope
systemd-cgls --unit kubepods.slice --no-pager
Unit kubepods.slice (/kubepods.slice):
│ ├─kubepods-burstable-pod6910effd_ea14_4f76_a7de_53c333338acb.slice
│ │ └─crio-029d0064354201e077d8155f2147907dfe8f18ef2ccead607273d487971df7e0.scope ...
│ │   ├─6166 nginx: master process nginx -g daemon off;
│ │   ├─6212 nginx: worker process
│ │   └─6213 nginx: worker process
│ ├─kubepods-burstable-pod3fee6bda_0ed8_40fa_95c8_deb824f6de93.slice
│ └─ ...
│   └─...
│     └─...

systemctl show --no-pager crio-029d0064354201e077d8155f2147907dfe8f18ef2ccead607273d487971df7e0.scope
# More info

We first find the container ID using crictl ps, which is CRI equivalent of docker ps. In the output of this command we see our Pod webserver and the container ID. We then use systemd-cgls which recursively shows control groups content. In its output we see the group with our container's ID, which is crio-029d006435420.... Finally, we use systemctl show --no-pager crio-029d006435420... which gives us the systemd properties which were used to set the values in cgroup files.

To then inspect the cgroups filesystem itself:

cd /sys/fs/cgroup/kubepods.slice/kubepods-burstable.slice/
ls -l kubepods-burstable-pod6910effd_ea14_4f76_a7de_53c333338acb.slice
-rw-r--r-- 1 root root 0 Dec  3 11:46 cpu.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 cpu.weight
-r--r--r-- 1 root root 0 Dec  3 11:46 hugetlb.2MB.current
-rw-r--r-- 1 root root 0 Dec  3 11:46 hugetlb.2MB.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 io.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 io.weight
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.high
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.low
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.min

cat .../cpu.weight  # 10

#                  $MAX  $PERIOD
cat .../cpu.max  # 50000 100000

cat .../memory.min  # 67108864

cat .../memory.max  # 134217728

We go to the directory kubepods-burstable-pod6910effd_ea14_4f76_a7de_53c333338acb.slice which was listed in the output of systemd-cgls. This is the cgroup directory for the whole webserver Pod. Here we find the individual cgroup files. The files and the values that we mostly care about are cpu.weight, cpu.max, memory.min and memory.max as these are the ones that describe CPU and memory requests/limits of the Pod, but what do the values mean?

  • cpu.weight - This is the CPU request. It is converted to the so-called weight (also called "shares"). It's in range 1 - 10000 and describes how much CPU will the container get in comparison to other containers. If you had only 2 processes on the system and one would have 2000 and the other 8000, then the former would get 20% and the latter 80% of CPU cycles. In this case 250m equals to 10 "shares", so if we were to run Pod with 450m CPU request, then it would get 18 "shares".
  • cpu.max - This is the CPU limit. The values in the file indicate that the group may consume up to $MAX in each $PERIOD duration. max for $MAX indicates no limit. In this case: consume 50000 / 100000, therefore at most 0.5 (500m) CPU.
  • memory.min - This is memory request in bytes. This is only set if memory QoS is enabled in the cluster (explained later)
  • .
  • memory.max - A memory usage hard limit in bytes. If a cgroup's memory usage reaches this limit and can't be reduced, the OOM killer is invoked in the cgroup and the container gets killed.

There's a lot of other files besides these 4, however none of them can be currently set through Pod manifests.

As a side note, if you want to poke around yourself, an alternative/faster way to find these values might be to get the path to the cgroupfs from container runtime spec mentioned earlier:

POD_ID="$(crictl pods --name webserver -q)"
crictl inspectp -o=json $POD_ID | jq .info.runtimeSpec.linux.cgroupsPath -r
# Output (a path to Pod's pause container):
# kubepods-burstable-pod6910effd_..._53c333338acb.slice:crio:72d13807f0ab1a3860478d6053...745a50e5e296ddd7570e1fa9
# Translates to
ls -l /sys/fs/cgroup/kubepods.slice/kubepods-burstable.slice/kubepods-burstable-pod6910effd_..._53c333338acb.slice/

-rw-r--r-- 1 root root 0 Dec  3 11:46 cpu.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 cpu.weight
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.high
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.low
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.max
-rw-r--r-- 1 root root 0 Dec  3 11:46 memory.min


Apart from enforcing the resource allocation, cgroups are also used for monitoring resource consumption. This is done by cAdvisor component included in kubelet. Looking at the cAdvisor metrics also serves as an easier way to view the cgroups files values.

To view cAdvisor metrics you can use:

# Directly on the node:
curl -sk -X GET  "https://localhost:10250/metrics/cadvisor" \
  --key /etc/kubernetes/pki/apiserver-kubelet-client.key \
  --cacert /etc/kubernetes/pki/ca.crt \
  --cert /etc/kubernetes/pki/apiserver-kubelet-client.crt

# Remotely using "kubectl proxy"
kubectl proxy &
# [1] 2933

kubectl get nodes
NAME        STATUS   ROLES           AGE   VERSION
some-node   Ready    control-plane   7d    v1.25.4

curl http://localhost:8001/api/v1/nodes/some-node/proxy/metrics/cadvisor

If you have access to the cluster Node, then you can get the metrics directly from kubelet API using the first curl command above. Alternatively, you can use kubectl proxy to get access to the Kubernetes API Server and run curl from local specifying one of your nodes in the path.

Regardless of which option you use, you will get a huge list of metrics which will look like this sample.

Some of the more interesting metrics you will find there are:

# Memory limit defined for that container (memory.max)
  pod="webserver"} 1.34217728e+08

# If the CPU limit is "500m" (500 millicores) for a container and
# the "container_spec_cpu_period" is set to 100,000, this value will be 50,000.
# cpu.max 1st value
container_spec_cpu_quota{...} 50000

# The number of microseconds that the scheduler uses as a window when limiting container processes
# cpu.max 2nd value
container_spec_cpu_period{...} 100000

# CPU share of the container
# cpu.weight
container_spec_cpu_shares{...} 237

And as a final summary of the whole propagation and translation from Pod manifest all the way to cgroupfs, here's a little table:

Pod SpecSystemdCgroups FSCadvisor Metric
limits.cpuCPUQuotaPerSecUSeccpu.maxcontainer_spec_cpu_quota (_period)

Why Should You Care?

With all the newly acquired knowledge about cgroups in Kubernetes, there's a question, "Why even bother learning this, when Linux and Kubernetes does all the work for us?". Well, deeper understanding is always beneficial in my opinion, and you never know when you will need this knowledge for debugging. More importantly though, knowing how it works, makes it possible to implement and take advantage of some advanced features:

  • For example Memory QoS, which was briefly mentioned earlier. Most people don't know this, but currently - as of Kubernetes v1.26 - memory requests in Pod manifest are not taken into consideration by container runtime and are therefore effectively ignored. Additionally, there's no way to throttle memory usage and when container reaches memory limit, it simply gets OOM killed. With introduction of Memory QoS feature, which is currently in Alpha, Kubernetes can take advantage of additional cgroup files memory.min and memory.high to throttle a container instead of straight-up killing it. (Note: The memory.min value in the earlier examples is populated only because Memory QoS was enabled on the cluster.)
  • Another possible advanced application for cgroups could be a container-aware OOM killer - let's say you have a Pod with logging sidecar, if the Pod reaches memory usage limit, then the main container in the Pod might get killed because of memory consumption of the sidecar. With container-aware OOM killer, we could in theory configure the Pod so that the sidecar is killed first when memory limit is reached.
  • Thanks to cgroups, it's also possible to run Kubernetes components, such as kubelet or CRI in rootless mode (using this Alpha feature), which is great for security.
  • And finally, It's also good to have some knowledge of cgroups if you're a Java developer, because JDK looks at the cgroup files to understand how much CPU and memory is available.

And these are just the tip of the iceberg. There are many more things that cgroups can help us with and chances are, that in the future we will see more resource management features added to Kubernetes, for example for managing other types of resources such disk throttling, network I/O or resource pressure (PSI).

Closing Thoughts

While a lot of the things in Kubernetes might seem like a magic, when you look closely you will find out that it's really just a clever use of core Linux components and features, and resource management is no exception as we've seen in this article.

Additionally, while cgroups might seem like an implementation detail from point of view of a cluster operator and user, having understanding of how they work can be beneficial when troubleshooting difficult issues or when using advanced features like the ones described in previous section.