oam/knowledge base/kubernetes/README.md

Kubernetes

Open source container orchestration engine for containerized applications.
Hosted by the Cloud Native Computing Foundation.

Table of content

1. Components
   1. The control plane
      1. kube-apiserver
      2. etcd
      3. kube-scheduler
      4. kube-controller-manager
      5. cloud-controller-manager
   2. The worker Nodes
      1. kubelet
      2. kube-proxy
      3. Container runtime
      4. Addons
2. The API
3. Pods
   1. Quality of service
4. Security
   1. Containers with high privileges
      1. Capabilities
      2. Privileged containers vs privilege escalation
   2. Sysctl settings
5. Managed Kubernetes Services
   1. Best practices
6. Troubleshooting
   1. Run a command in a Pod right after its initialization
   2. Run a command just before a Pod stops
   3. Dedicate Nodes to specific workloads
   4. Recreate Pods upon ConfigMap's or Secret's content change
7. Examples
   1. Prometheus on Kubernetes using Helm
   2. Create an admission webhook
8. Further readings
9. Sources

Components

When you deploy Kubernetes, you get a cluster.

A K8S cluster consists of:

• one or more sets of worker machines (Nodes), which execute containers; every cluster must have at least one worker node;
• a control plane, which manages the worker Nodes and the workloads in the cluster.

The components of an application workload are called Pods. Pods are hosted by Nodes, are composed of containers, and are also the smallest execution unit in the cluster.

In production environments:

• the control plane usually runs across multiple Nodes;
• a cluster usually runs multiple Nodes, to provide fault-tolerance and high availability.

The control plane

The control plane's components make global decisions about the cluster (like scheduling) and detect and respond to cluster events (like starting up a new Pod when a deployment has less replicas then it requests).

Control plane components can be run on any machine in the cluster. For simplicity, set up scripts typically start all control plane components on the same machine, and avoid running user containers on it.

kube-apiserver

The API server exposes the Kubernetes API, and is the front end for, and the core of, the Kubernetes control plane.

The main implementation of a Kubernetes API server is kube-apiserver, which is designed to scale horizontally (scales by deploying more instances) and balance traffic between its instances.

etcd

Consistent and highly-available key value store used as Kubernetes' backing store for all cluster data.

kube-scheduler

Detects newly created Pods with no assigned Node and selects one for them to run on.

Scheduling decisions take into account individual and collective resource requirements, hardware/software/policy constraints, affinity and anti-affinity specifications, data locality, inter-workload interference, and deadlines.

kube-controller-manager

Runs controller processes.
Each controller is a separate process logically speaking, but to reduce complexity they are all compiled into a single binary and run in a single process.

Examples of these controllers are the following:

• Node controller: notices and responds when Nodes go down;
• Job controller: checks Job objects (one-off tasks) and creates Pods to run them to completion;
• EndpointSlice controller: populates EndpointSlice objects, which provide a link between Services and Pods;
• ServiceAccount controller: create default ServiceAccounts for new namespaces.

cloud-controller-manager

Embeds cloud-specific control logic, linking your cluster into your cloud provider's API and separating the components that interact with that cloud platform from the components that only interact with your cluster.

They only run controllers that are specific to your cloud provider. If you are running Kubernetes on your own premises, or in a learning environment inside your own PC, the cluster will have no cloud controller managers.

As with the kube-controller-manager, it combines several logically independent control loops into a single binary that you run as a single process. It can scale horizontally (run more than one copy) to improve performance or to help tolerate failures.

The following controllers can have cloud provider dependencies:

• Node controller: checks the cloud provider to determine if a node has been deleted in the cloud after it stops responding;
• Route controller: sets up routes in the underlying cloud infrastructure;
• Service controller: creates, updates and deletes cloud provider load balancers.

The worker Nodes

Each Node runs components which provide a runtime environment for the cluster, and sync with the control plane to maintain workloads running as requested.

kubelet

Runs as an agent on each node in the cluster, making sure that containers are run in a Pod.

It takes a set of PodSpecs and ensures that the containers described in them are running and healthy. It only manages containers created by Kubernetes.

kube-proxy

Network proxy that runs on each node and implements part of the Kubernetes Service concept.

It maintains all the network rules on nodes which allow network communication to the Pods from network sessions inside or outside of your cluster.

It uses the operating system's packet filtering layer, if there is one and it's available; if not, it forwards the traffic itself.

Container runtime

The software that is responsible for running containers.

Kubernetes supports container runtimes like containerd, CRI-O, and any other implementation of the Kubernetes CRI (Container Runtime Interface).

Addons

Addons use Kubernetes resources (DaemonSet, Deployment, etc) to implement cluster features, and as such namespaced resources for addons belong within the kube-system namespace.

The API

The API server exposes an HTTP API that lets end users, different parts of your cluster, and external components communicate with one another. This lets you query and manipulate the state of API objects in Kubernetes and can be accessed through command-line tools or directly using REST calls. The serialized state of the objects is stored by writing them into etcd.

Consider using one of the client libraries if you are writing an application using the Kubernetes API. The complete API details are documented using OpenAPI.

Kubernetes supports multiple API versions, each at a different API path (like /api/v1 or /apis/rbac.authorization.k8s.io/v1alpha1); the server handles the conversion between API versions transparently. Versioning is done at the API level rather than at the resource or field level; this ensures that the API presents a clear and consistent view of system resources and behavior, and enables controlling access to end-of-life and/or experimental APIs. All the different versions are representations of the same persisted data.

To make it easier to evolve and to extend them, Kubernetes implements API groups that can be enabled or disabled. API resources are distinguished by their API group, resource type, namespace (for namespaced resources), and name.
New API resources and new resource fields can be added often and frequently. Elimination of resources or fields requires following the API deprecation policy.

The Kubernetes API can be extended:

• using Custom resources to declaratively define how the API server should provide your chosen resource API, or
• extending the Kubernetes API by implementing an aggregation layer.

Pods

Gotchas:

• If a Container specifies a memory or CPU limit but does not specify a memory or CPU request, Kubernetes automatically assigns it a resource request spec that matches the given limit

Quality of service

See Configure Quality of Service for Pods for more information.

QoS classes are used to make decisions about scheduling and evicting Pods.
When a Pod is created, it is also assigned one of the following QoS classes:

• Guaranteed, when every Container in the Pod, including init containers, has:

  • a memory limit and a memory request, and they are the same
  • a CPU limit and a CPU request, and they are the same

  spec:
    containers:
      …
      resources:
        limits:
          cpu: 700m
          memory: 200Mi
        requests:
          cpu: 700m
          memory: 200Mi
      …
  status:
    qosClass: Guaranteed
  

• Burstable, when

  • the Pod does not meet the criteria for the Guaranteed QoS class
  • at least one Container in the Pod has a memory or CPU request spec

  spec:
    containers:
    - name: qos-demo
      …
      resources:
        limits:
          memory: 200Mi
        requests:
          memory: 100Mi
    …
  status:
    qosClass: Burstable
  

• BestEffort, when the Pod does not meet the criteria for the other QoS classes (its Containers have no memory or CPU limits nor requests)

  spec:
    containers:
      …
      resources: {}
    …
  status:
    qosClass: BestEffort
  

Security

Containers with high privileges

Kubernetes introduced a Security Context as a mitigation solution to some workloads requiring to change one or more Node settings for performance, stability, or other issues (e.g. ElasticSearch).
This is usually achieved executing the needed command from an InitContainer with higher privileges than normal, which will have access to the Node's resources and breaks the isolation Containers are usually famous for. If compromised, an attacker can use this highly privileged container to gain access to the underlying Node.

From the design proposal:

A security context is a set of constraints that are applied to a Container in order to achieve the following goals (from the Security design):

• ensure a clear isolation between the Container and the underlying host it runs on;
• limit the ability of the Container to negatively impact the infrastructure or other Containers.

[The main idea is that] Containers should only be granted the access they need to perform their work. The Security Context takes advantage of containerization features such as the ability to add or remove capabilities to give a process some privileges, but not all the privileges of the root user.

Capabilities

Adding capabilities to a Container is not making it privileged, nor allowing privilege escalation. It is just giving the Container the ability to write to specific files or devices depending on the given capability.

This means having a capability assigned does not automatically make the Container able to wreak havoc on a Node, and this practice can be a legitimate use of this feature instead.

From the feature's man page:

Linux divides the privileges traditionally associated with superuser into distinct units, known as capabilities, which can be independently enabled and disabled. Capabilities are a per-thread attribute.

This also means a Container will be limited to its contents, plus the capabilities it has been assigned.

Some capabilities are assigned to all Containers by default, while others (the ones which could cause more issues) require to be explicitly set using the Containers' securityContext.capabilities.add property.
If a Container is privileged (see Privileged container vs privilege escalation), it will have access to all the capabilities, with no regards of what are explicitly assigned to it.

Check:

• Linux capabilities, to see what capabilities can be assigned to a process in a Linux system;
• Runtime privilege and Linux capabilities in Docker containers for the capabilities available inside Kubernetes, and
• Container capabilities in Kubernetes for a handy table associating capabilities in Kubernetes to their Linux variant.

Privileged containers vs privilege escalation

A privileged container is very different from a container leveraging privilege escalation.

A privileged container does whatever a processes running directly on the Node can.
It will have automatically assigned all capabilities, and being root in this container is effectively being root on the Node it is running on.

For a Container to be privileged, its definition requires the securityContext.privileged property set to true.

Privilege escalation allows a process inside the Container to gain more privileges than its parent process.
The process will be able to assume root-like powers, but will have access only to the assigned capabilities and generally have limited to no access to the Node like any other Container.

For a Container to leverage privilege escalation, its definition requires the securityContext.allowPrivilegeEscalation property:

• to either be set to true, or
• to not be set at all if:
  • the Container is already privileged, or
  • the Container has SYS_ADMIN capabilities.

This property directly controls whether the no_new_privs flag gets set on the Container's process.

From the design document for no_new_privs:

In Linux, the execve system call can grant more privileges to a newly-created process than its parent process. Considering security issues, since Linux kernel v3.5, there is a new flag named no_new_privs added to prevent those new privileges from being granted to the processes.

no_new_privs is inherited across fork, clone and execve and can not be unset. With no_new_privs set, execve promises not to grant the privilege to do anything that could not have been done without the execve call.

For more details about no_new_privs, please check the Linux kernel documentation.

[…]

To recap, below is a table defining the default behavior at the pod security policy level and what can be set as a default with a pod security policy:

allowPrivilegeEscalation setting	uid = 0 or unset	uid != 0	privileged/CAP_SYS_ADMIN
nil	no_new_privs=true	no_new_privs=false	no_new_privs=false
false	no_new_privs=true	no_new_privs=true	no_new_privs=false
true	no_new_privs=false	no_new_privs=false	no_new_privs=false

Sysctl settings

See [Using sysctls in a Kubernetes Cluster].

Managed Kubernetes Services

Most cloud providers offer their managed versions of Kubernetes. Check their websites.

Best practices

All kubernetes clusters should:

• be created using IaC (terraform, pulumi)
• have different node pools, to be able to manage different workloads
• have a non pre-emptible node pool to host critical services like Admission Controller Webhooks

Each node pool should:

• have a meaningful name (<prefix..>-<randomid>)
• have a minimum set of meaningful labels:
  • cloud provider information
  • node information and capabilities
• sparse nodes on availability zones
• be labelled with information about the nodes' features

Troubleshooting

Run a command in a Pod right after its initialization

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
spec:
  template:
    …
    spec:
      containers:
        - name: my-container
          …
          lifecycle:
            postStart:
              exec:
                command: ["/bin/sh", "-c", "echo 'heeeeeeey yaaaaaa!'"]

Run a command just before a Pod stops

Leverage the preStop hook instead of postStart.

Hooks are not passed parameters, and this includes environment variables Use a script if you need them. See container hooks and preStop hook doesn't work with env variables

Since kubernetes version 1.9 and forth, volumeMounts behavior on secret, configMap, downwardAPI and projected have changed to Read-Only by default. A workaround to the problem is to create an emtpyDir Volume and copy the contents into it and execute/write whatever you need:

  initContainers:
    - name: copy-ro-scripts
      image: busybox
      command: ['sh', '-c', 'cp /scripts/* /etc/pre-install/']
      volumeMounts:
        - name: scripts
          mountPath: /scripts
        - name: pre-install
          mountPath: /etc/pre-install
  volumes:
    - name: pre-install
      emptyDir: {}
    - name: scripts
      configMap:
        name: bla

Dedicate Nodes to specific workloads

Leverage taints and node affinity:

1. Taint the Nodes:

   $ kubectl taint nodes 'host1' 'dedicated=devs:NoSchedule'
   node "host1" tainted
   

2. Add Labels to the nodes:

   $ kubectl label nodes 'host1' 'dedicated=devs'
   node "host1" labeled
   

3. add tolerations and node affinity to any Pod's spec:

   spec:
     affinity:
       nodeAffinity:
         requiredDuringSchedulingIgnoredDuringExecution:
           nodeSelectorTerms:
           - matchExpressions:
             - key: dedicated
               operator: In
               values:
               - devs
     tolerations:
     - key: "dedicated"
       operator: "Equal"
       value: "devs"
       effect: "NoSchedule"
   

Recreate Pods upon ConfigMap's or Secret's content change

Use a checksum annotation to do the trick:

apiVersion: apps/v1
kind: Deployment
spec:
  template:
    metadata:
      annotations:
        checksum/configmap: {{ include (print $.Template.BasePath "/configmap.yaml") $ | sha256sum }}
        checksum/secret: {{ include (print $.Template.BasePath "/secret.yaml") $ | sha256sum }}
        {{- if .podAnnotations }}
          {{- toYaml .podAnnotations | trim | nindent 8 }}
        {{- end }}

Examples

Prometheus on Kubernetes using Helm

See the example's README.

Create an admission webhook

See the example's README.

Further readings

Concepts:

• Kubernetes' security context design proposal
• Kubernetes' No New Privileges Design Proposal
• Linux kernel documentation about no_new_privs
• Linux capabilities
• Runtime privilege and Linux capabilities in Docker containers
• Container capabilities in Kubernetes
• Configure a Security Context for a Pod or a Container, specifically the Set capabilities for a Container section
• Kubernetes SecurityContext Capabilities Explained
• Best practices for pod security in Azure Kubernetes Service (AKS)
• Using sysctls in a Kubernetes Cluster
• Namespaces
• Container hooks

Tools:

• kubectl
• helm
• helmfile
• kubeval
• kubectx+kubens (alternative to kubie)
• kube-ps1
• kubie (alternative to kubectx+kubens and kube-ps1)

Sources

All the references in the [further readings] section, plus the following:

• Kubernetes' concepts
• How to run a command in a Pod after initialization
• Making sense of Taints and Tolerations
• Read-only filesystem error
• preStop hook doesn't work with env variables
• Configure Quality of Service for Pods