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Kubernetes v1.21 [stable]
Kubernetes' EndpointSlice API provides a way to track network endpoints within a Kubernetes cluster. EndpointSlices offer a more scalable and extensible alternative to Endpoints.
In Kubernetes, an EndpointSlice contains references to a set of network endpoints. The control plane automatically creates EndpointSlices for any Kubernetes Service that has a selector specified. These EndpointSlices include references to all the Pods that match the Service selector. EndpointSlices group network endpoints together by unique combinations of protocol, port number, and Service name. The name of a EndpointSlice object must be a valid DNS subdomain name.
As an example, here's a sample EndpointSlice object, that's owned by the
- name: http
By default, the control plane creates and manages EndpointSlices to have no
more than 100 endpoints each. You can configure this with the
flag, up to a maximum of 1000.
EndpointSlices can act as the source of truth for kube-proxy when it comes to how to route internal traffic.
EndpointSlices support three address types:
- FQDN (Fully Qualified Domain Name)
EndpointSlice object represents a specific IP address type. If you have
a Service that is available via IPv4 and IPv6, there will be at least two
EndpointSlice objects (one for IPv4, and one for IPv6).
The EndpointSlice API stores conditions about endpoints that may be useful for consumers.
The three conditions are
ready is a condition that maps to a Pod's
Ready condition. A running Pod with the
condition set to
True should have this EndpointSlice condition also set to
ready is NEVER
true when a Pod is terminating. Consumers should refer
serving condition to inspect the readiness of terminating Pods. The only exception to
this rule is for Services with
spec.publishNotReadyAddresses set to
true. Endpoints for these
Services will always have the
ready condition set to
Kubernetes v1.26 [stable]
serving condition is almost identical to the
ready condition. The difference is that
consumers of the EndpointSlice API should check the
serving condition if they care about pod readiness while
the pod is also terminating.
serving is almost identical to
ready, it was added to prevent breaking the existing meaning
ready. It may be unexpected for existing clients if
ready could be
true for terminating
endpoints, since historically terminating endpoints were never included in the Endpoints or
EndpointSlice API to begin with. For this reason,
ready is always
false for terminating
endpoints, and a new condition
serving was added in v1.20 so that clients can track readiness
for terminating pods independent of the existing semantics for
Kubernetes v1.22 [beta]
Terminating is a condition that indicates whether an endpoint is terminating.
For pods, this is any pod that has a deletion timestamp set.
Each endpoint within an EndpointSlice can contain relevant topology information. The topology information includes the location of the endpoint and information about the corresponding Node and zone. These are available in the following per endpoint fields on EndpointSlices:
nodeName- The name of the Node this endpoint is on.
zone- The zone this endpoint is in.
In the v1 API, the per endpoint
topology was effectively removed in favor of
the dedicated fields
Setting arbitrary topology fields on the
endpoint field of an
resource has been deprecated and is not supported in the v1 API.
Instead, the v1 API supports setting individual
These fields are automatically translated between API versions. For example, the
value of the
"topology.kubernetes.io/zone" key in the
topology field in
the v1beta1 API is accessible as the
zone field in the v1 API.
Most often, the control plane (specifically, the endpoint slice controller) creates and manages EndpointSlice objects. 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, Kubernetes defines the
endpointslice.kubernetes.io/managed-by, which indicates the entity managing
The endpoint slice 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 are owned by the Service that the endpoint
slice object tracks endpoints for. This ownership is indicated by an owner
reference on each EndpointSlice as well as a
label that enables simple lookups of all EndpointSlices belonging to a Service.
In some cases, applications create custom Endpoints resources. To ensure that these applications do not need to concurrently write to both Endpoints and EndpointSlice resources, the cluster's control plane mirrors most Endpoints resources to corresponding EndpointSlices.
The control plane mirrors Endpoints resources unless:
- the Endpoints resource has a
endpointslice.kubernetes.io/skip-mirrorlabel set to
- the Endpoints resource has a
- the corresponding Service resource does not exist.
- the corresponding Service resource has a non-nil selector.
Individual Endpoints resources may translate into multiple EndpointSlices. This will occur if an Endpoints resource has multiple subsets or includes endpoints with multiple IP families (IPv4 and IPv6). A maximum of 1000 addresses per subset will be mirrored to EndpointSlices.
Distribution of EndpointSlices
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 control plane tries to fill EndpointSlices as full as possible, but does not actively rebalance them. The logic is fairly straightforward:
- Iterate through existing EndpointSlices, remove endpoints that are no longer desired and update matching endpoints that have changed.
- Iterate through EndpointSlices that have been modified in the first step and fill them up with any new endpoints needed.
- If there's still new endpoints left to add, try to fit them into a previously unchanged slice and/or create new ones.
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.
Due to the nature of EndpointSlice changes, endpoints may be represented in more than one EndpointSlice at the same time. This naturally occurs as changes to different EndpointSlice objects can arrive at the Kubernetes client watch / cache at different times.
Clients of the EndpointSlice API must iterate through all the existing EndpointSlices associated to a Service and build a complete list of unique network endpoints. It is important to mention that endpoints may be duplicated in different EndpointSlices.
You can find a reference implementation for how to perform this endpoint aggregation
and deduplication as part of the
EndpointSliceCache code within
Comparison with Endpoints
The original Endpoints API provided a simple and straightforward way of tracking network endpoints in Kubernetes. As Kubernetes clusters and Services grew to handle more traffic and to send more traffic to more backend Pods, the limitations of that original 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 object, those Endpoints objects could get quite large. For Services that stayed stable (the same set of endpoints over a long period of time) the impact was less noticeable; even then, some use cases of Kubernetes weren't well served.
When a Service had a lot of backend endpoints and the workload was either scaling frequently, or rolling out new changes frequently, each update to the single Endpoints object for that Service meant a lot of traffic between Kubernetes cluster components (within the control plane, and also between nodes and the API server). This extra traffic also had a cost in terms of CPU use.
With EndpointSlices, adding or removing a single Pod triggers the same number of updates to clients that are watching for changes, but the size of those update message is much smaller at large scale.
EndpointSlices also enabled innovation around new features such dual-stack networking and topology-aware routing.