github
/
k3s
mirror of https://github.com/k3s-io/k3s
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

clarifications

pull/6/head
Marek Biskup 2015-06-16 17:38:36 +02:00
parent 6674913f92
commit 5a2b96c455
1 changed files with 9 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
docs/replication-controller.md
View File

@ -4,9 +4,9 @@
A _replication controller_ ensures that a specified number of pod "replicas" are running at any one time. If there are too many, it will kill some. If there are too few, it will start more. Unlike in the case where a user directly created pods, a replication controller replaces pods that are deleted or terminated for any reason, such as in the case of node failure or disruptive node maintenance, such as a kernel upgrade. For this reason, we recommend that you use a replication controller even if your application requires only a single pod. Think of it similarly to a process supervisor, only it supervises multiple pods across multiple nodes instead of individual processes on a single node. A replication controller delegates local container restarts to some agent on the node (e.g., Kubelet or Docker).
As discussed in [life of a pod](pod-states.md), `ReplicationController` is *only* appropriate for pods with `RestartPolicy = Always` (Note: If `RestartPolicy` is not set, the default value is `Always`.). `ReplicationController` should refuse to instantiate any pod that has a different restart policy. As discussed in [issue #503](https://github.com/GoogleCloudPlatform/kubernetes/issues/503#issuecomment-50169443), we expect other types of controllers to be added to Kubernetes to handle other types of workloads, such as build/test and batch workloads, in the future.
As discussed in [life of a pod](pod-states.md), `ReplicationController` is *only* appropriate for pods with `RestartPolicy = Always`. (Note: If `RestartPolicy` is not set, the default value is `Always`.) `ReplicationController` should refuse to instantiate any pod that has a different restart policy. As discussed in [issue #503](https://github.com/GoogleCloudPlatform/kubernetes/issues/503#issuecomment-50169443), we expect other types of controllers to be added to Kubernetes to handle other types of workloads, such as build/test and batch workloads, in the future.
A replication controller will never terminate on its own, but it isn't expected to be as long-lived as services. Services may be composed of pods controlled by multiple replication controllers, and it is expected that many replication controllers may be created and destroyed over the lifetime of a service. Both services themselves and their clients should remain oblivious to the replication controllers that maintain the pods of the services.
A replication controller will never terminate on its own, but it isn't expected to be as long-lived as services. Services may be composed of pods controlled by multiple replication controllers, and it is expected that many replication controllers may be created and destroyed over the lifetime of a service (for instance, to perform an update of pods that run the service). Both services themselves and their clients should remain oblivious to the replication controllers that maintain the pods of the services.
## How does a replication controller work?
@ -20,15 +20,15 @@ Pods created by a replication controller are intended to be fungible and semanti
### Labels
The population of pods that a `ReplicationController` is monitoring is defined with a [label selector](labels.md), which creates a loosely coupled relationship between the controller and the pods controlled, in contrast to pods, which are more tightly coupled. We deliberately chose not to represent the set of pods controlled using a fixed-length array of pod specifications, because our experience is that that approach increases complexity of management operations, for both clients and the system.
The population of pods that a replication controller is monitoring is defined with a [label selector](labels.md#label-selectors), which creates a loosely coupled relationship between the controller and the pods controlled, in contrast to pods, which are more tightly coupled to their definition. We deliberately chose not to represent the set of pods controlled using a fixed-length array of pod specifications, because our experience is that that approach increases complexity of management operations, for both clients and the system.
The replication controller should verify that the pods created from the specified template have labels that match its label selector. Though it isn't verified yet, you should also ensure that only one replication controller controls any given pod, by ensuring that the label selectors of replication controllers do not target overlapping sets.
Note that `ReplicationController`s may themselves have labels and would generally carry the labels their corresponding pods have in common, but these labels do not affect the behavior of the replication controllers.
Note that replication controllers may themselves have labels and would generally carry the labels their corresponding pods have in common, but these labels do not affect the behavior of the replication controllers.
Pods may be removed from a replication controller's target set by changing their labels. This technique may be used to remove pods from service for debugging, data recovery, etc. Pods that are removed in this way will be replaced automatically (assuming that the number of replicas is not also changed).
Similarly, deleting a replication controller does not affect the pods it created. Its `replicas` field must first be set to 0 in order to delete the pods controlled. In the future, we may provide a feature to do this and the deletion in a single client operation.
Similarly, deleting a replication controller does not affect the pods it created. Its `replicas` field must first be set to 0 in order to delete the pods controlled. (Note that the client tool, kubectl, provides a single operation, [stop](kubectl_stop.md) to delete both the replication controller and the pods it controlls. However, there is no such operation in the API at the moment)
## Responsibilities of the replication controller
@ -58,11 +58,14 @@ Ideally, the rolling update controller would take application readiness into acc
The two replication controllers would need to create pods with at least one differentiating label, such as the image tag of the primary container of the pod, since it is typically image updates that motivate rolling updates.
Rolling update is implemented in the client tool
[kubectl](kubectl_rolling-update.md)
### Multiple release tracks
In addition to running multiple releases of an application while a rolling update is in progress, it's common to run multiple releases for an extended period of time, or even continuously, using multiple release tracks. The tracks would be differentiated by labels.
For instance, a service might target all pods with `tier in (frontend), environment in (prod)`. Now say you have 10 replicated pods that make up this tier. But you want to be able to 'canary' a new version of this component. You could set up a `ReplicationController` with `replicas` set to 9 for the bulk of the replicas, with labels `tier=frontend, environment=prod, track=stable`, and another `ReplicationController` with `replicas` set to 1 for the canary, with labels `tier=frontend, environment=prod, track=canary`. Now the service is covering both the canary and non-canary pods. But you can mess with the `ReplicationController`s separately to test things out, monitor the results, etc.
For instance, a service might target all pods with `tier in (frontend), environment in (prod)`. Now say you have 10 replicated pods that make up this tier. But you want to be able to 'canary' a new version of this component. You could set up a replication controller with `replicas` set to 9 for the bulk of the replicas, with labels `tier=frontend, environment=prod, track=stable`, and another replication controller with `replicas` set to 1 for the canary, with labels `tier=frontend, environment=prod, track=canary`. Now the service is covering both the canary and non-canary pods. But you can mess with the replication controllers separately to test things out, monitor the results, etc.
[![Analytics](https://kubernetes-site.appspot.com/UA-36037335-10/GitHub/docs/replication-controller.md?pixel)]()