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Networking Reference

This section of the Kubernetes documentation provides reference details of Kubernetes networking.

1 - Protocols for Services

If you configure a Service, you can select from any network protocol that Kubernetes supports.

Kubernetes supports the following protocols with Services:

When you define a Service, you can also specify the application protocol that it uses.

This document details some special cases, all of them typically using TCP as a transport protocol:

Supported protocols

There are 3 valid values for the protocol of a port for a Service:

SCTP

FEATURE STATE: Kubernetes v1.20 [stable]

When using a network plugin that supports SCTP traffic, you can use SCTP for most Services. For type: LoadBalancer Services, SCTP support depends on the cloud provider offering this facility. (Most do not).

SCTP is not supported on nodes that run Windows.

Support for multihomed SCTP associations

The support of multihomed SCTP associations requires that the CNI plugin can support the assignment of multiple interfaces and IP addresses to a Pod.

NAT for multihomed SCTP associations requires special logic in the corresponding kernel modules.

TCP

You can use TCP for any kind of Service, and it's the default network protocol.

UDP

You can use UDP for most Services. For type: LoadBalancer Services, UDP support depends on the cloud provider offering this facility.

Special cases

HTTP

If your cloud provider supports it, you can use a Service in LoadBalancer mode to configure a load balancer outside of your Kubernetes cluster, in a special mode where your cloud provider's load balancer implements HTTP / HTTPS reverse proxying, with traffic forwarded to the backend endpoints for that Service.

Typically, you set the protocol for the Service to TCP and add an annotation (usually specific to your cloud provider) that configures the load balancer to handle traffic at the HTTP level. This configuration might also include serving HTTPS (HTTP over TLS) and reverse-proxying plain HTTP to your workload.

You might additionally want to specify that the application protocol of the connection is http or https. Use http if the session from the load balancer to your workload is HTTP without TLS, and use https if the session from the load balancer to your workload uses TLS encryption.

PROXY protocol

If your cloud provider supports it, you can use a Service set to type: LoadBalancer to configure a load balancer outside of Kubernetes itself, that will forward connections wrapped with the PROXY protocol.

The load balancer then sends an initial series of octets describing the incoming connection, similar to this example (PROXY protocol v1):

PROXY TCP4 192.0.2.202 10.0.42.7 12345 7\r\n

The data after the proxy protocol preamble are the original data from the client. When either side closes the connection, the load balancer also triggers a connection close and sends any remaining data where feasible.

Typically, you define a Service with the protocol to TCP. You also set an annotation, specific to your cloud provider, that configures the load balancer to wrap each incoming connection in the PROXY protocol.

TLS

If your cloud provider supports it, you can use a Service set to type: LoadBalancer as a way to set up external reverse proxying, where the connection from client to load balancer is TLS encrypted and the load balancer is the TLS server peer. The connection from the load balancer to your workload can also be TLS, or might be plain text. The exact options available to you depend on your cloud provider or custom Service implementation.

Typically, you set the protocol to TCP and set an annotation (usually specific to your cloud provider) that configures the load balancer to act as a TLS server. You would configure the TLS identity (as server, and possibly also as a client that connects to your workload) using mechanisms that are specific to your cloud provider.

2 - Ports and Protocols

When running Kubernetes in an environment with strict network boundaries, such as on-premises datacenter with physical network firewalls or Virtual Networks in Public Cloud, it is useful to be aware of the ports and protocols used by Kubernetes components.

Control plane

ProtocolDirectionPort RangePurposeUsed By
TCPInbound6443Kubernetes API serverAll
TCPInbound2379-2380etcd server client APIkube-apiserver, etcd
TCPInbound10250Kubelet APISelf, Control plane
TCPInbound10259kube-schedulerSelf
TCPInbound10257kube-controller-managerSelf

Although etcd ports are included in control plane section, you can also host your own etcd cluster externally or on custom ports.

Worker node(s)

ProtocolDirectionPort RangePurposeUsed By
TCPInbound10250Kubelet APISelf, Control plane
TCPInbound30000-32767NodePort Services†All

† Default port range for NodePort Services.

All default port numbers can be overridden. When custom ports are used those ports need to be open instead of defaults mentioned here.

One common example is API server port that is sometimes switched to 443. Alternatively, the default port is kept as is and API server is put behind a load balancer that listens on 443 and routes the requests to API server on the default port.

3 - Virtual IPs and Service Proxies

Every node in a Kubernetes cluster runs a kube-proxy (unless you have deployed your own alternative component in place of kube-proxy).

The kube-proxy component is responsible for implementing a virtual IP mechanism for Services of type other than ExternalName.

A question that pops up every now and then is why Kubernetes relies on proxying to forward inbound traffic to backends. What about other approaches? For example, would it be possible to configure DNS records that have multiple A values (or AAAA for IPv6), and rely on round-robin name resolution?

There are a few reasons for using proxying for Services:

  • There is a long history of DNS implementations not respecting record TTLs, and caching the results of name lookups after they should have expired.
  • Some apps do DNS lookups only once and cache the results indefinitely.
  • Even if apps and libraries did proper re-resolution, the low or zero TTLs on the DNS records could impose a high load on DNS that then becomes difficult to manage.

Later in this page you can read about how various kube-proxy implementations work. Overall, you should note that, when running kube-proxy, kernel level rules may be modified (for example, iptables rules might get created), which won't get cleaned up, in some cases until you reboot. Thus, running kube-proxy is something that should only be done by an administrator which understands the consequences of having a low level, privileged network proxying service on a computer. Although the kube-proxy executable supports a cleanup function, this function is not an official feature and thus is only available to use as-is.

Some of the details in this reference refer to an example: the backend Pods for a stateless image-processing workloads, running with three replicas. Those replicas are fungible—frontends do not care which backend they use. While the actual Pods that compose the backend set may change, the frontend clients should not need to be aware of that, nor should they need to keep track of the set of backends themselves.

Proxy modes

Note that the kube-proxy starts up in different modes, which are determined by its configuration.

  • The kube-proxy's configuration is done via a ConfigMap, and the ConfigMap for kube-proxy effectively deprecates the behavior for almost all of the flags for the kube-proxy.
  • The ConfigMap for the kube-proxy does not support live reloading of configuration.
  • The ConfigMap parameters for the kube-proxy cannot all be validated and verified on startup. For example, if your operating system doesn't allow you to run iptables commands, the standard kernel kube-proxy implementation will not work.

iptables proxy mode

In this mode, kube-proxy watches the Kubernetes control plane for the addition and removal of Service and EndpointSlice objects. For each Service, it installs iptables rules, which capture traffic to the Service's clusterIP and port, and redirect that traffic to one of the Service's backend sets. For each endpoint, it installs iptables rules which select a backend Pod.

By default, kube-proxy in iptables mode chooses a backend at random.

Using iptables to handle traffic has a lower system overhead, because traffic is handled by Linux netfilter without the need to switch between userspace and the kernel space. This approach is also likely to be more reliable.

If kube-proxy is running in iptables mode and the first Pod that's selected does not respond, the connection fails. This is different from the old userspace mode: in that scenario, kube-proxy would detect that the connection to the first Pod had failed and would automatically retry with a different backend Pod.

You can use Pod readiness probes to verify that backend Pods are working OK, so that kube-proxy in iptables mode only sees backends that test out as healthy. Doing this means you avoid having traffic sent via kube-proxy to a Pod that's known to have failed.

Virtual IP mechanism for Services, using iptables mode

Example

As an example, consider the image processing application described earlier in the page. When the backend Service is created, the Kubernetes control plane assigns a virtual IP address, for example 10.0.0.1. For this example, assume that the Service port is 1234. All of the kube-proxy instances in the cluster observe the creation of the new Service.

When kube-proxy on a node sees a new Service, it installs a series of iptables rules which redirect from the virtual IP address to more iptables rules, defined per Service. The per-Service rules link to further rules for each backend endpoint, and the per- endpoint rules redirect traffic (using destination NAT) to the backends.

When a client connects to the Service's virtual IP address the iptables rule kicks in. A backend is chosen (either based on session affinity or randomly) and packets are redirected to the backend without rewriting the client IP address.

This same basic flow executes when traffic comes in through a node-port or through a load-balancer, though in those cases the client IP address does get altered.

Optimizing iptables mode performance

In large clusters (with tens of thousands of Pods and Services), the iptables mode of kube-proxy may take a long time to update the rules in the kernel when Services (or their EndpointSlices) change. You can adjust the syncing behavior of kube-proxy via options in the iptables section of the kube-proxy configuration file (which you specify via kube-proxy --config <path>):

...
iptables:
  minSyncPeriod: 1s
  syncPeriod: 30s
...
minSyncPeriod

The minSyncPeriod parameter sets the minimum duration between attempts to resynchronize iptables rules with the kernel. If it is 0s, then kube-proxy will always immediately synchronize the rules every time any Service or Endpoint changes. This works fine in very small clusters, but it results in a lot of redundant work when lots of things change in a small time period. For example, if you have a Service backed by a Deployment with 100 pods, and you delete the Deployment, then with minSyncPeriod: 0s, kube-proxy would end up removing the Service's Endpoints from the iptables rules one by one, for a total of 100 updates. With a larger minSyncPeriod, multiple Pod deletion events would get aggregated together, so kube-proxy might instead end up making, say, 5 updates, each removing 20 endpoints, which will be much more efficient in terms of CPU, and result in the full set of changes being synchronized faster.

The larger the value of minSyncPeriod, the more work that can be aggregated, but the downside is that each individual change may end up waiting up to the full minSyncPeriod before being processed, meaning that the iptables rules spend more time being out-of-sync with the current apiserver state.

The default value of 1s is a good compromise for small and medium clusters. In large clusters, it may be necessary to set it to a larger value. (Especially, if kube-proxy's sync_proxy_rules_duration_seconds metric indicates an average time much larger than 1 second, then bumping up minSyncPeriod may make updates more efficient.)

syncPeriod

The syncPeriod parameter controls a handful of synchronization operations that are not directly related to changes in individual Services and Endpoints. In particular, it controls how quickly kube-proxy notices if an external component has interfered with kube-proxy's iptables rules. In large clusters, kube-proxy also only performs certain cleanup operations once every syncPeriod to avoid unnecessary work.

For the most part, increasing syncPeriod is not expected to have much impact on performance, but in the past, it was sometimes useful to set it to a very large value (eg, 1h). This is no longer recommended, and is likely to hurt functionality more than it improves performance.

Experimental performance improvements
FEATURE STATE: Kubernetes v1.26 [alpha]

In Kubernetes 1.26, some new performance improvements were made to the iptables proxy mode, but they are not enabled by default (and should probably not be enabled in production clusters yet). To try them out, enable the MinimizeIPTablesRestore feature gate for kube-proxy with --feature-gates=MinimizeIPTablesRestore=true,….

If you enable that feature gate and you were previously overriding minSyncPeriod, you should try removing that override and letting kube-proxy use the default value (1s) or at least a smaller value than you were using before.

If you notice kube-proxy's sync_proxy_rules_iptables_restore_failures_total or sync_proxy_rules_iptables_partial_restore_failures_total metrics increasing after enabling this feature, that likely indicates you are encountering bugs in the feature and you should file a bug report.

IPVS proxy mode

In ipvs mode, kube-proxy watches Kubernetes Services and EndpointSlices, calls netlink interface to create IPVS rules accordingly and synchronizes IPVS rules with Kubernetes Services and EndpointSlices periodically. This control loop ensures that IPVS status matches the desired state. When accessing a Service, IPVS directs traffic to one of the backend Pods.

The IPVS proxy mode is based on netfilter hook function that is similar to iptables mode, but uses a hash table as the underlying data structure and works in the kernel space. That means kube-proxy in IPVS mode redirects traffic with lower latency than kube-proxy in iptables mode, with much better performance when synchronizing proxy rules. Compared to the other proxy modes, IPVS mode also supports a higher throughput of network traffic.

IPVS provides more options for balancing traffic to backend Pods; these are:

  • rr: round-robin
  • lc: least connection (smallest number of open connections)
  • dh: destination hashing
  • sh: source hashing
  • sed: shortest expected delay
  • nq: never queue

Virtual IP address mechanism for Services, using IPVS mode

Session affinity

In these proxy models, the traffic bound for the Service's IP:Port is proxied to an appropriate backend without the clients knowing anything about Kubernetes or Services or Pods.

If you want to make sure that connections from a particular client are passed to the same Pod each time, you can select the session affinity based on the client's IP addresses by setting .spec.sessionAffinity to ClientIP for a Service (the default is None).

Session stickiness timeout

You can also set the maximum session sticky time by setting .spec.sessionAffinityConfig.clientIP.timeoutSeconds appropriately for a Service. (the default value is 10800, which works out to be 3 hours).

IP address assignment to Services

Unlike Pod IP addresses, which actually route to a fixed destination, Service IPs are not actually answered by a single host. Instead, kube-proxy uses packet processing logic (such as Linux iptables) to define virtual IP addresses which are transparently redirected as needed.

When clients connect to the VIP, their traffic is automatically transported to an appropriate endpoint. The environment variables and DNS for Services are actually populated in terms of the Service's virtual IP address (and port).

Avoiding collisions

One of the primary philosophies of Kubernetes is that you should not be exposed to situations that could cause your actions to fail through no fault of your own. For the design of the Service resource, this means not making you choose your own port number if that choice might collide with someone else's choice. That is an isolation failure.

In order to allow you to choose a port number for your Services, we must ensure that no two Services can collide. Kubernetes does that by allocating each Service its own IP address from within the service-cluster-ip-range CIDR range that is configured for the API Server.

To ensure each Service receives a unique IP, an internal allocator atomically updates a global allocation map in etcd prior to creating each Service. The map object must exist in the registry for Services to get IP address assignments, otherwise creations will fail with a message indicating an IP address could not be allocated.

In the control plane, a background controller is responsible for creating that map (needed to support migrating from older versions of Kubernetes that used in-memory locking). Kubernetes also uses controllers to check for invalid assignments (e.g. due to administrator intervention) and for cleaning up allocated IP addresses that are no longer used by any Services.

IP address ranges for Service virtual IP addresses

FEATURE STATE: Kubernetes v1.25 [beta]

Kubernetes divides the ClusterIP range into two bands, based on the size of the configured service-cluster-ip-range by using the following formula min(max(16, cidrSize / 16), 256). That formula paraphrases as never less than 16 or more than 256, with a graduated step function between them.

Kubernetes prefers to allocate dynamic IP addresses to Services by choosing from the upper band, which means that if you want to assign a specific IP address to a type: ClusterIP Service, you should manually assign an IP address from the lower band. That approach reduces the risk of a conflict over allocation.

If you disable the ServiceIPStaticSubrange feature gate then Kubernetes uses a single shared pool for both manually and dynamically assigned IP addresses, that are used for type: ClusterIP Services.

Traffic policies

You can set the .spec.internalTrafficPolicy and .spec.externalTrafficPolicy fields to control how Kubernetes routes traffic to healthy (“ready”) backends.

Internal traffic policy

FEATURE STATE: Kubernetes v1.22 [beta]

You can set the .spec.internalTrafficPolicy field to control how traffic from internal sources is routed. Valid values are Cluster and Local. Set the field to Cluster to route internal traffic to all ready endpoints and Local to only route to ready node-local endpoints. If the traffic policy is Local and there are no node-local endpoints, traffic is dropped by kube-proxy.

External traffic policy

You can set the .spec.externalTrafficPolicy field to control how traffic from external sources is routed. Valid values are Cluster and Local. Set the field to Cluster to route external traffic to all ready endpoints and Local to only route to ready node-local endpoints. If the traffic policy is Local and there are are no node-local endpoints, the kube-proxy does not forward any traffic for the relevant Service.

Traffic to terminating endpoints

FEATURE STATE: Kubernetes v1.26 [beta]

If the ProxyTerminatingEndpoints feature gate is enabled in kube-proxy and the traffic policy is Local, that node's kube-proxy uses a more complicated algorithm to select endpoints for a Service. With the feature enabled, kube-proxy checks if the node has local endpoints and whether or not all the local endpoints are marked as terminating. If there are local endpoints and all of them are terminating, then kube-proxy will forward traffic to those terminating endpoints. Otherwise, kube-proxy will always prefer forwarding traffic to endpoints that are not terminating.

This forwarding behavior for terminating endpoints exist to allow NodePort and LoadBalancer Services to gracefully drain connections when using externalTrafficPolicy: Local.

As a deployment goes through a rolling update, nodes backing a load balancer may transition from N to 0 replicas of that deployment. In some cases, external load balancers can send traffic to a node with 0 replicas in between health check probes. Routing traffic to terminating endpoints ensures that Node's that are scaling down Pods can gracefully receive and drain traffic to those terminating Pods. By the time the Pod completes termination, the external load balancer should have seen the node's health check failing and fully removed the node from the backend pool.

What's next

To learn more about Services, read Connecting Applications with Services.

You can also: