EndpointSlices provide a simple way to track network endpoints within a Kubernetes cluster. They offer a more scalable and extensible alternative to Endpoints.
In Kubernetes, an EndpointSlice contains references to a set of network endpoints. The EndpointSlice controller automatically creates EndpointSlices for a Kubernetes Service when a selectorAllows users to filter a list of resources based on labels. is specified. These EndpointSlices will include references to any Pods that match the Service selector. EndpointSlices group network endpoints together by unique Service and Port combinations. The name of a EndpointSlice object must be a valid DNS subdomain name.
As an example, here’s a sample EndpointSlice resource for the
apiVersion: discovery.k8s.io/v1beta1 kind: EndpointSlice metadata: name: example-abc labels: kubernetes.io/service-name: example addressType: IPv4 ports: - name: http protocol: TCP port: 80 endpoints: - addresses: - "10.1.2.3" conditions: ready: true hostname: pod-1 topology: kubernetes.io/hostname: node-1 topology.kubernetes.io/zone: us-west2-a
By default, EndpointSlices managed by the EndpointSlice controller will have no more than 100 endpoints each. Below this scale, EndpointSlices should map 1:1 with Endpoints and Services and have similar performance.
EndpointSlices can act as the source of truth for kube-proxy when it comes to how to route internal traffic. When enabled, they should provide a performance improvement for services with large numbers of endpoints.
EndpointSlices support three address types:
Each endpoint within an EndpointSlice can contain relevant topology information. This is used to indicate where an endpoint is, containing information about the corresponding Node, zone, and region. When the values are available, the following Topology labels will be set by the EndpointSlice controller:
kubernetes.io/hostname- The name of the Node this endpoint is on.
topology.kubernetes.io/zone- The zone this endpoint is in.
topology.kubernetes.io/region- The region this endpoint is in.
The values of these labels are derived from resources associated with each endpoint in a slice. The hostname label represents the value of the NodeName field on the corresponding Pod. The zone and region labels represent the value of the labels with the same names on the corresponding Node.
By default, EndpointSlices are created and managed by the EndpointSlice
controller. There are a variety of other use cases for EndpointSlices, such as
service mesh implementations, that could result in other entities or controllers
managing additional sets of EndpointSlices. To ensure that multiple entities can
manage EndpointSlices without interfering with each other, a
endpointslice.kubernetes.io/managed-by label is used to indicate the entity
managing an EndpointSlice. The EndpointSlice controller sets
endpointslice-controller.k8s.io as the value for this label on all
EndpointSlices it manages. Other entities managing EndpointSlices should also
set a unique value for this label.
In most use cases, EndpointSlices will be owned by the Service that it tracks
endpoints for. This is indicated by an owner reference on each EndpointSlice as
well as a
kubernetes.io/service-name label that enables simple lookups of all
EndpointSlices belonging to a Service.
The EndpointSlice controller watches Services and Pods to ensure corresponding EndpointSlices are up to date. The controller will manage EndpointSlices for every Service with a selector specified. These will represent the IPs of Pods matching the Service selector.
By default, EndpointSlices are limited to a size of 100 endpoints each. You can
configure this with the
--max-endpoints-per-slice kube-controller-managerControl Plane component that runs controller processes.
flag up to
a maximum of 1000.
Each EndpointSlice has a set of ports that applies to all endpoints within the resource. When named ports are used for a Service, Pods may end up with different target port numbers for the same named port, requiring different EndpointSlices. This is similar to the logic behind how subsets are grouped with Endpoints.
The controller tries to fill EndpointSlices as full as possible, but does not actively rebalance them. The logic of the controller is fairly straightforward:
Importantly, the third step prioritizes limiting EndpointSlice updates over a perfectly full distribution of EndpointSlices. As an example, if there are 10 new endpoints to add and 2 EndpointSlices with room for 5 more endpoints each, this approach will create a new EndpointSlice instead of filling up the 2 existing EndpointSlices. In other words, a single EndpointSlice creation is preferrable to multiple EndpointSlice updates.
With kube-proxy running on each Node and watching EndpointSlices, every change to an EndpointSlice becomes relatively expensive since it will be transmitted to every Node in the cluster. This approach is intended to limit the number of changes that need to be sent to every Node, even if it may result with multiple EndpointSlices that are not full.
In practice, this less than ideal distribution should be rare. Most changes processed by the EndpointSlice controller will be small enough to fit in an existing EndpointSlice, and if not, a new EndpointSlice is likely going to be necessary soon anyway. Rolling updates of Deployments also provide a natural repacking of EndpointSlices with all pods and their corresponding endpoints getting replaced.
The Endpoints API has provided a simple and straightforward way of tracking network endpoints in Kubernetes. Unfortunately as Kubernetes clusters and Services have gotten larger, limitations of that API became more visible. Most notably, those included challenges with scaling to larger numbers of network endpoints.
Since all network endpoints for a Service were stored in a single Endpoints resource, those resources could get quite large. That affected the performance of Kubernetes components (notably the master control plane) and resulted in significant amounts of network traffic and processing when Endpoints changed. EndpointSlices help you mitigate those issues as well as provide an extensible platform for additional features such as topological routing.
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