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Use a public standard load balancer in Azure Kubernetes Service (AKS)

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The Azure Load Balancer operates at layer 4 of the Open Systems Interconnection (OSI) model that supports both inbound and outbound scenarios. It distributes inbound flows that arrive at the load balancer's front end to the back end pool instances.

A public load balancer integrated with AKS serves two purposes:

  • To provide outbound connections to the cluster nodes inside the AKS virtual network by translating the private IP address to a public IP address part of its Outbound Pool .
  • To provide access to applications via Kubernetes services of type LoadBalancer , enabling you to easily scale your applications and create highly available services.

An internal (or private) load balancer is used when only private IPs are allowed as frontend. Internal load balancers are used to load balance traffic inside a virtual network. A load balancer frontend can also be accessed from an on-premises network in a hybrid scenario.

This article covers integration with a public load balancer on AKS. For internal load balancer integration, see Use an internal load balancer in AKS .

Before you begin

  • Azure Load Balancer is available in two SKUs: Basic and Standard . The Standard SKU is used by default when you create an AKS cluster. The Standard SKU gives you access to added functionality, such as a larger backend pool, multiple node pools , Availability Zones , and is secure by default . It's the recommended load balancer SKU for AKS. For more information on the Basic and Standard SKUs, see Azure Load Balancer SKU comparison .
  • For a full list of the supported annotations for Kubernetes services with type LoadBalancer , see LoadBalancer annotations .
  • This article assumes you have an AKS cluster with the Standard SKU Azure Load Balancer. If you need an AKS cluster, you can create one using Azure CLI , Azure PowerShell , or the Azure portal .
  • AKS manages the lifecycle and operations of agent nodes. Modifying the IaaS resources associated with the agent nodes isn't supported. An example of an unsupported operation is making manual changes to the load balancer resource group.

If you'd prefer to use your own gateway, firewall, or proxy to provide outbound connection, you can skip the creation of the load balancer outbound pool and respective frontend IP by using outbound type as UserDefinedRouting (UDR) . The outbound type defines the egress method for a cluster and defaults to type LoadBalancer .

Use the public standard load balancer

After you create an AKS cluster with outbound type LoadBalancer (default), your cluster is ready to use the load balancer to expose services.

Create a service manifest named public-svc.yaml , which creates a public service of type LoadBalancer .

Specify the load balancer IP address

If you want to use a specific IP address with the load balancer, there are two ways:

Adding the LoadBalancerIP property to the load balancer YAML manifest is deprecating following upstream Kubernetes . While current usage remains the same and existing services are expected to work without modification, we highly recommend setting service annotations instead.

  • Set service annotations : Use service.beta.kubernetes.io/azure-load-balancer-ipv4 for an IPv4 address and service.beta.kubernetes.io/azure-load-balancer-ipv6 for an IPv6 address.
  • Add the LoadBalancerIP property to the load balancer YAML manifest : Add the Service.Spec.LoadBalancerIP property to the load balancer YAML manifest. This field is deprecating following upstream Kubernetes , and it can't support dual-stack. Current usage remains the same and existing services are expected to work without modification.

Deploy the service manifest

Deploy the public service manifest using kubectl apply and specify the name of your YAML manifest.

The Azure Load Balancer is configured with a new public IP that fronts the new service. Since the Azure Load Balancer can have multiple frontend IPs, each new service that you deploy gets a new dedicated frontend IP to be uniquely accessed.

Confirm your service is created and the load balancer is configured using the following command.

When you view the service details, the public IP address created for this service on the load balancer is shown in the EXTERNAL-IP column. It might take a few minutes for the IP address to change from <pending> to an actual public IP address.

For more detailed information about your service, use the following command.

The following example output is a condensed version of the output after you run kubectl describe service . LoadBalancer Ingress shows the external IP address exposed by your service. IP shows the internal addresses.

Configure the public standard load balancer

You can customize different settings for your standard public load balancer at cluster creation time or by updating the cluster. These customization options allow you to create a load balancer that meets your workload needs. With the standard load balancer, you can:

  • Set or scale the number of managed outbound IPs.
  • Bring your own custom outbound IPs or outbound IP prefix .
  • Customize the number of allocated outbound ports to each node on the cluster.
  • Configure the timeout setting for idle connections.

Only one outbound IP option (managed IPs, bring your own IP, or IP prefix) can be used at a given time.

Change the inbound pool type (PREVIEW)

AKS nodes can be referenced in the load balancer backend pools by either their IP configuration (Azure Virtual Machine Scale Sets based membership) or by their IP address only. Utilizing the IP address based backend pool membership provides higher efficiencies when updating services and provisioning load balancers, especially at high node counts. Provisioning new clusters with IP based backend pools and converting existing clusters is now supported. When combined with NAT Gateway or user-defined routing egress types, provisioning of new nodes and services are more performant.

Two different pool membership types are available:

  • nodeIPConfiguration - legacy Virtual Machine Scale Sets IP configuration based pool membership type
  • nodeIP - IP-based membership type

Requirements

  • The aks-preview extension must be at least version 0.5.103.
  • The AKS cluster must be version 1.23 or newer.
  • The AKS cluster must be using standard load balancers and virtual machine scale sets.

Limitations

  • Clusters using IP based backend pools are limited to 2500 nodes.

AKS preview features are available on a self-service, opt-in basis. Previews are provided "as is" and "as available," and they're excluded from the service-level agreements and limited warranty. AKS previews are partially covered by customer support on a best-effort basis. As such, these features aren't meant for production use. For more information, see the following support articles:

  • AKS support policies
  • Azure support FAQ

Install the aks-preview CLI extension

Register the ipbasedloadbalancerpreview preview feature.

To create an AKS cluster with IP based backend pools, you must enable the IPBasedLoadBalancerPreview feature flag on your subscription.

Register the IPBasedLoadBalancerPreview feature flag by using the az feature register command, as shown in the following example:

It takes a few minutes for the status to show Registered . Verify the registration status by using the az feature list command:

When the feature has been registered, refresh the registration of the Microsoft.ContainerService resource provider by using the az provider register command:

Create a new AKS cluster with IP-based inbound pool membership

Update an existing aks cluster to use ip-based inbound pool membership.

This operation causes a temporary disruption to incoming service traffic in the cluster. The impact time increases with larger clusters that have many nodes.

Scale the number of managed outbound public IPs

Azure Load Balancer provides outbound and inbound connectivity from a virtual network. Outbound rules make it simple to configure network address translation for the public standard load balancer.

Outbound rules follow the same syntax as load balancing and inbound NAT rules:

frontend IPs + parameters + backend pool

An outbound rule configures outbound NAT for all virtual machines identified by the backend pool to be translated to the frontend. Parameters provide more control over the outbound NAT algorithm.

While you can use an outbound rule with a single public IP address, outbound rules are great for scaling outbound NAT because they ease the configuration burden. You can use multiple IP addresses to plan for large-scale scenarios and outbound rules to mitigate SNAT exhaustion prone patterns. Each IP address provided by a frontend provides 64k ephemeral ports for the load balancer to use as SNAT ports.

When using a Standard SKU load balancer with managed outbound public IPs (which are created by default), you can scale the number of managed outbound public IPs using the --load-balancer-managed-outbound-ip-count parameter.

Use the following command to update an existing cluster. You can also set this parameter to have multiple managed outbound public IPs.

We don't recommend using the Azure portal to make any outbound rule changes. When making these changes, you should go through the AKS cluster and not directly on the Load Balancer resource.

Outbound rule changes made directly on the Load Balancer resource are removed whenever the cluster is reconciled, such as when it's stopped, started, upgraded, or scaled.

Use the Azure CLI, as shown in the examples. Outbound rule changes made using az aks CLI commands are permanent across cluster downtime.

For more information, see Azure Load Balancer outbound rules .

The above example sets the number of managed outbound public IPs to 2 for the myAKSCluster cluster in myResourceGroup .

At cluster creation time, you can also set the initial number of managed outbound public IPs by appending the --load-balancer-managed-outbound-ip-count parameter and setting it to your desired value. The default number of managed outbound public IPs is 1 .

Provide your own outbound public IPs or prefixes

When you use a Standard SKU load balancer, the AKS cluster automatically creates a public IP in the AKS-managed infrastructure resource group and assigns it to the load balancer outbound pool by default.

A public IP created by AKS is an AKS-managed resource, meaning AKS manages the lifecycle of that public IP and doesn't require user action directly on the public IP resource. Alternatively, you can assign your own custom public IP or public IP prefix at cluster creation time. Your custom IPs can also be updated on an existing cluster's load balancer properties.

Requirements for using your own public IP or prefix include:

  • Users must create and own custom public IP addresses. Managed public IP addresses created by AKS can't be reused as a "bring your own custom IP" as it can cause management conflicts.
  • You must ensure the AKS cluster identity (Service Principal or Managed Identity) has permissions to access the outbound IP, as per the required public IP permissions list .
  • Make sure you meet the prerequisites and constraints necessary to configure outbound IPs or outbound IP prefixes.

Update the cluster with your own outbound public IP

Use the az network public-ip show command to list the IDs of your public IPs.

The above command shows the ID for the myPublicIP public IP in the myResourceGroup resource group.

Use the az aks update command with the load-balancer-outbound-ips parameter to update your cluster with your public IPs.

The following example uses the load-balancer-outbound-ips parameter with the IDs from the previous command.

Update the cluster with your own outbound public IP prefix

You can also use public IP prefixes for egress with your Standard SKU load balancer. The following example uses the az network public-ip prefix show command to list the IDs of your public IP prefixes.

The above command shows the ID for the myPublicIPPrefix public IP prefix in the myResourceGroup resource group.

The following example uses the load-balancer-outbound-ip-prefixes parameter with the IDs from the previous command.

Create the cluster with your own public IP or prefixes

When you create your cluster, you can bring your own IP addresses or IP prefixes for egress to support scenarios like adding egress endpoints to an allowlist. To define your own public IPs and IP prefixes at cluster creation time, you append the same parameters shown in the previous command.

Use the az aks create command with the load-balancer-outbound-ips parameter to create a new cluster with your own public IPs.

Use the az aks create command with the load-balancer-outbound-ip-prefixes parameter to create a new cluster with your own public IP prefixes.

Configure the allocated outbound ports

If you have applications on your cluster that can establish a large number of connections to small set of destinations, like many instances of a frontend application connecting to a database, you might have a scenario susceptible to encounter SNAT port exhaustion. SNAT port exhaustion happens when an application runs out of outbound ports to use to establish a connection to another application or host. If you have a scenario susceptible to encounter SNAT port exhaustion, we highly recommended you increase the allocated outbound ports and outbound frontend IPs on the load balancer.

For more information on SNAT, see Use SNAT for outbound connections .

By default, AKS sets AllocatedOutboundPorts on its load balancer to 0 , which enables automatic outbound port assignment based on backend pool size when creating a cluster. For example, if a cluster has 50 or fewer nodes, 1024 ports are allocated to each node. As the number of nodes in the cluster increases, fewer ports are available per node.

There is a hard limit of 1024 ports regardless of whether front-end IPs are added when the node size is less than or equal to 50 (1-50).

To show the AllocatedOutboundPorts value for the AKS cluster load balancer, use az network lb outbound-rule list .

The following example output shows that automatic outbound port assignment based on backend pool size is enabled for the cluster.

To configure a specific value for AllocatedOutboundPorts and outbound IP address when creating or updating a cluster, use load-balancer-outbound-ports and either load-balancer-managed-outbound-ip-count , load-balancer-outbound-ips , or load-balancer-outbound-ip-prefixes . Before setting a specific value or increasing an existing value for either outbound ports or outbound IP addresses, you must calculate the appropriate number of outbound ports and IP addresses. Use the following equation for this calculation rounded to the nearest integer: 64,000 ports per IP / <outbound ports per node> * <number of outbound IPs> = <maximum number of nodes in the cluster> .

When calculating the number of outbound ports and IPs and setting the values, keep the following information in mind:

  • The number of outbound ports per node is fixed based on the value you set.
  • The value for outbound ports must be a multiple of 8.
  • Adding more IPs doesn't add more ports to any node, but it provides capacity for more nodes in the cluster.
  • You must account for nodes that might be added as part of upgrades, including the count of nodes specified via maxSurge values .

The following examples show how the values you set affect the number of outbound ports and IP addresses:

  • If the default values are used and the cluster has 48 nodes, each node has 1024 ports available.
  • If the default values are used and the cluster scales from 48 to 52 nodes, each node is updated from 1024 ports available to 512 ports available.
  • If the number of outbound ports is set to 1,000 and the outbound IP count is set to 2, then the cluster can support a maximum of 128 nodes: 64,000 ports per IP / 1,000 ports per node * 2 IPs = 128 nodes .
  • If the number of outbound ports is set to 1,000 and the outbound IP count is set to 7, then the cluster can support a maximum of 448 nodes: 64,000 ports per IP / 1,000 ports per node * 7 IPs = 448 nodes .
  • If the number of outbound ports is set to 4,000 and the outbound IP count is set to 2, then the cluster can support a maximum of 32 nodes: 64,000 ports per IP / 4,000 ports per node * 2 IPs = 32 nodes .
  • If the number of outbound ports is set to 4,000 and the outbound IP count is set to 7, then the cluster can support a maximum of 112 nodes: 64,000 ports per IP / 4,000 ports per node * 7 IPs = 112 nodes .

After calculating the number outbound ports and IPs, verify you have additional outbound port capacity to handle node surge during upgrades. It's critical to allocate sufficient excess ports for additional nodes needed for upgrade and other operations. AKS defaults to one buffer node for upgrade operations. If using maxSurge values , multiply the outbound ports per node by your maxSurge value to determine the number of ports required. For example, if you calculate that you need 4000 ports per node with 7 IP address on a cluster with a maximum of 100 nodes and a max surge of 2:

  • 2 surge nodes * 4000 ports per node = 8000 ports needed for node surge during upgrades.
  • 100 nodes * 4000 ports per node = 400,000 ports required for your cluster.
  • 7 IPs * 64000 ports per IP = 448,000 ports available for your cluster.

The above example shows the cluster has an excess capacity of 48,000 ports, which is sufficient to handle the 8000 ports needed for node surge during upgrades.

Once the values have been calculated and verified, you can apply those values using load-balancer-outbound-ports and either load-balancer-managed-outbound-ip-count , load-balancer-outbound-ips , or load-balancer-outbound-ip-prefixes when creating or updating a cluster.

Configure the load balancer idle timeout

When SNAT port resources are exhausted, outbound flows fail until existing flows release SNAT ports. Load balancer reclaims SNAT ports when the flow closes, and the AKS-configured load balancer uses a 30-minute idle timeout for reclaiming SNAT ports from idle flows.

You can also use transport (for example, TCP keepalives or application-layer keepalives ) to refresh an idle flow and reset this idle timeout if necessary. You can configure this timeout following the below example.

If you expect to have numerous short-lived connections and no long-lived connections that might have long times of idle, like using kubectl proxy or kubectl port-forward , consider using a low timeout value such as 4 minutes . When using TCP keepalives, it's sufficient to enable them on one side of the connection. For example, it's sufficient to enable them on the server side only to reset the idle timer of the flow. It's not necessary for both sides to start TCP keepalives. Similar concepts exist for application layer, including database client-server configurations. Check the server side for what options exist for application-specific keepalives.

AKS enables TCP Reset on idle by default. We recommend you keep this configuration and leverage it for more predictable application behavior on your scenarios.

TCP RST is only sent during TCP connection in ESTABLISHED state. Read more about it here .

When setting IdleTimeoutInMinutes to a different value than the default of 30 minutes, consider how long your workloads need an outbound connection. Also consider that the default timeout value for a Standard SKU load balancer used outside of AKS is 4 minutes. An IdleTimeoutInMinutes value that more accurately reflects your specific AKS workload can help decrease SNAT exhaustion caused by tying up connections no longer being used.

Altering the values for AllocatedOutboundPorts and IdleTimeoutInMinutes might significantly change the behavior of the outbound rule for your load balancer and shouldn't be done lightly. Check the SNAT Troubleshooting section and review the Load Balancer outbound rules and outbound connections in Azure before updating these values to fully understand the impact of your changes.

Restrict inbound traffic to specific IP ranges

The following manifest uses loadBalancerSourceRanges to specify a new IP range for inbound external traffic.

This example updates the rule to allow inbound external traffic only from the MY_EXTERNAL_IP_RANGE range. If you replace MY_EXTERNAL_IP_RANGE with the internal subnet IP address, traffic is restricted to only cluster internal IPs. If traffic is restricted to cluster internal IPs, clients outside your Kubernetes cluster are unable to access the load balancer.

  • Inbound, external traffic flows from the load balancer to the virtual network for your AKS cluster. The virtual network has a network security group (NSG) which allows all inbound traffic from the load balancer. This NSG uses a service tag of type LoadBalancer to allow traffic from the load balancer.
  • Pod CIDR should be added to loadBalancerSourceRanges if there are Pods needing to access the service's LoadBalancer IP for clusters with version v1.25 or above.

Maintain the client's IP on inbound connections

By default, a service of type LoadBalancer in Kubernetes and in AKS doesn't persist the client's IP address on the connection to the pod. The source IP on the packet that's delivered to the pod becomes the private IP of the node. To maintain the client’s IP address, you must set service.spec.externalTrafficPolicy to local in the service definition. The following manifest shows an example.

Customizations via Kubernetes Annotations

The following annotations are supported for Kubernetes services with type LoadBalancer , and they only apply to INBOUND flows.

Customize the load balancer health probe

As documented here , Tcp, Http and Https are three protocols supported by load balancer service.

Currently, the default protocol of the health probe varies among services with different transport protocols, app protocols, annotations and external traffic policies.

  • for local services, HTTP and /healthz would be used. The health probe will query NodeHealthPort rather than actual backend service
  • for cluster TCP services, TCP would be used.
  • for cluster UDP services, no health probes.

For local services with PLS integration and PLS proxy protocol enabled, the default HTTP+/healthz health probe does not work. Thus health probe can be customized the same way as cluster services to support this scenario.

Since v1.20, service annotation service.beta.kubernetes.io/azure-load-balancer-health-probe-request-path is introduced to determine the health probe behavior.

  • For clusters <=1.23, spec.ports.appProtocol would only be used as probe protocol when service.beta.kubernetes.io/azure-load-balancer-health-probe-request-path is also set.
  • For clusters >1.24, spec.ports.appProtocol would be used as probe protocol and / would be used as default probe request path ( service.beta.kubernetes.io/azure-load-balancer-health-probe-request-path could be used to change to a different request path).

Note that the request path would be ignored when using TCP or the spec.ports.appProtocol is empty. More specifically:

Since v1.21, two service annotations service.beta.kubernetes.io/azure-load-balancer-health-probe-interval and load-balancer-health-probe-num-of-probe are introduced, which customize the configuration of health probe. If service.beta.kubernetes.io/azure-load-balancer-health-probe-interval is not set, Default value of 5 is applied. If load-balancer-health-probe-num-of-probe is not set, Default value of 2 is applied. And total probe should be less than 120 seconds.

Custom Load Balancer health probe for port

Different ports in a service can require different health probe configurations. This could be because of service design (such as a single health endpoint controlling multiple ports), or Kubernetes features like the MixedProtocolLBService .

The following annotations can be used to customize probe configuration per service port.

For following manifest, probe rule for port httpsserver is different from the one for httpserver because annotations for port httpsserver are specified.

In this manifest, the https ports use a different node port, an HTTP readiness check at port 10256 on /healthz(healthz endpoint of kube-proxy).

In this manifest, the https ports use a different health probe endpoint, an HTTP readiness check at port 30000 on /healthz/ready.

Troubleshooting SNAT

If you know that you're starting many outbound TCP or UDP connections to the same destination IP address and port, and you observe failing outbound connections or support notifies you that you're exhausting SNAT ports (preallocated ephemeral ports used by PAT), you have several general mitigation options. Review these options and decide what's best for your scenario. It's possible that one or more can help manage your scenario. For detailed information, review the outbound connections troubleshooting guide .

The root cause of SNAT exhaustion is frequently an anti-pattern for how outbound connectivity is established, managed, or configurable timers changed from their default values. Review this section carefully.

  • Check if your connections remain idle for a long time and rely on the default idle timeout for releasing that port. If so, the default timeout of 30 minutes might need to be reduced for your scenario.
  • Investigate how your application creates outbound connectivity (for example, code review or packet capture).
  • Determine if this activity is expected behavior or whether the application is misbehaving. Use metrics and logs in Azure Monitor to substantiate your findings. For example, use the "Failed" category for SNAT connections metric.
  • Evaluate if appropriate patterns are followed.
  • Evaluate if SNAT port exhaustion should be mitigated with more outbound IP addresses + more allocated outbound ports .

Design patterns

Take advantage of connection reuse and connection pooling whenever possible. These patterns help you avoid resource exhaustion problems and result in predictable behavior. Primitives for these patterns can be found in many development libraries and frameworks.

  • Atomic requests (one request per connection) generally aren't a good design choice. Such anti-patterns limit scale, reduce performance, and decrease reliability. Instead, reuse HTTP/S connections to reduce the numbers of connections and associated SNAT ports. The application scale increases and performance improves because of reduced handshakes, overhead, and cryptographic operation cost when using TLS.
  • If you're using out of cluster/custom DNS, or custom upstream servers on coreDNS, keep in mind that DNS can introduce many individual flows at volume when the client isn't caching the DNS resolvers result. Make sure to customize coreDNS first instead of using custom DNS servers and to define a good caching value.
  • UDP flows (for example, DNS lookups) allocate SNAT ports during the idle timeout. The longer the idle timeout, the higher the pressure on SNAT ports. Use short idle timeout (for example, 4 minutes).
  • Use connection pools to shape your connection volume.
  • Never silently abandon a TCP flow and rely on TCP timers to clean up flow. If you don't let TCP explicitly close the connection, state remains allocated at intermediate systems and endpoints, and it makes SNAT ports unavailable for other connections. This pattern can trigger application failures and SNAT exhaustion.
  • Don't change OS-level TCP close related timer values without expert knowledge of impact. While the TCP stack recovers, your application performance can be negatively affected when the endpoints of a connection have mismatched expectations. Wishing to change timers is usually a sign of an underlying design problem. Review following recommendations.

Moving from a Basic SKU load balancer to Standard SKU

If you have an existing cluster with the Basic SKU load balancer, there are important behavioral differences to note when migrating to the Standard SKU load balancer.

For example, making blue/green deployments to migrate clusters is a common practice given the load-balancer-sku type of a cluster and can only be defined at cluster create time. However, Basic SKU load balancers use Basic SKU IP addresses, which aren't compatible with Standard SKU load balancers. Standard SKU load balancers require Standard SKU IP addresses. When migrating clusters to upgrade load balancer SKUs, a new IP address with a compatible IP address SKU is required.

For more considerations on how to migrate clusters, visit our documentation on migration considerations .

The following limitations apply when you create and manage AKS clusters that support a load balancer with the Standard SKU:

  • Provide your own public IPs.
  • Provide your own public IP prefixes.
  • Specify a number up to 100 to allow the AKS cluster to create that many Standard SKU public IPs in the same resource group as the AKS cluster. This resource group is usually named with MC_ at the beginning. AKS assigns the public IP to the Standard SKU load balancer. By default, one public IP is automatically created in the same resource group as the AKS cluster if no public IP, public IP prefix, or number of IPs is specified. You also must allow public addresses and avoid creating any Azure policies that ban IP creation.
  • A public IP created by AKS can't be reused as a custom bring your own public IP address. Users must create and manage all custom IP addresses.
  • Defining the load balancer SKU can only be done when you create an AKS cluster. You can't change the load balancer SKU after an AKS cluster has been created.
  • You can only use one type of load balancer SKU ( Basic or Standard ) in a single cluster.
  • Standard SKU load balancers only support Standard SKU IP addresses.

To learn more about Kubernetes services, see the Kubernetes services documentation .

To learn more about using internal load balancer for inbound traffic, see the AKS internal load balancer documentation .

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How to choose the external IP address of a Kubernetes load balancer in Google Kubernetes Engine

I'm deploying a web app using Google Kubernetes Engine and I want to make it accessible via a load balancer on an existing static IP address that I control as part of the same project in Google Cloud Platform, because the domain name I want to use already points to this IP.

The yaml file I used for the pod is:

I can set up a load balancer using:

This provides an external IP on which the app is accessible, but I can't find any way to configure it to use the IP I want. The services documentation mentions a spec.clusterIP setting, but this doesn't seem to relate to the external IP. Likewise, once the load balancer is set up, the service's status.loadBalancer.ingress.ip field is set to its external IP address, but this doesn't seem to be a configurable setting.

As an alternative, I tried manually creating a forwarding rule in the Google Compute Engine console to direct traffic from my static IP address to the target pool set up by Kubernetes, but when I try to connect the connection is refused.

Is there any way to do what I want - to expose a Kubernetes pod (or replication controller) on Google Kubernetes engine on a chosen static IP address?

how to set a static ip for kubernetes load balancer

  • google-kubernetes-engine

Ben's user avatar

3 Answers 3

TL;DR Google Container Engine running Kubernetes v1.1 supports loadBalancerIP just mark the auto-assigned IP as static first.

Kubernetes v1.1 supports externalIPs :

So far there isn't a really good consistent documentation on how to use it on GCE. What is sure is that this IP must first be one of your pre-allocated static IPs.

The cross-region load balancing documentation is mostly for Compute Engine and not Kubernetes/Container Engine, but it's still useful especially the part "Configure the load balancing service".

If you just create a Kubernetes LoadBalancer on GCE, it will create a network Compute Engine > Network > Network load balancing > Forwarding Rule pointing to a target pool made of your machines on your cluster (normally only those running the Pods matching the service selector). It looks like deleting a namespace doesn't nicely clean-up the those created rules.

It is actually now supported (even though under documented):

  • Check that you're running Kubernetes 1.1 or later (under GKE edit your cluster and check "Node version")
  • Under Networking > External IP addresses you should have already some Ephemeral marked as pointing to your cluster's VM instance (if not or unsure, deploy once without loadBalancerIP , wait until you've an external IP allocated when you run kubectl get svc , and look up that IP in the list on that page). Mark one of them as static , let's say it External Address is 10.10.10.10 .
  • Edit your LoadBalancer to have loadBalancerIP=10.10.10.10 as above (adapt to the IP that was given to you by Google).

Now if you delete your LoadBalancer or even your namespace, it should preserve that IP address upon re-reploying on that cluster. If you need to change the cluster, some manual fiddling should be possible:

  • Name: cluster-pool (or any other name)
  • Region: Select the region of one of your clusters
  • Health Check: Optional, if you wish
  • Select existing instance groups: Your Kubernetes cluster
  • Name: http-cross-region-gfr (or any other name)
  • External IP: Select loadbalancer-ip-crossregion you just reserved
  • Target pool: Select cluster-pool you just created

Wernight's user avatar

  • Are those still relevant ? –  Ben Oct 19, 2016 at 16:13

Good news. This will be fixed in Kubernetes v1.1. You can set the service.spec.loadBalancerIP field to an IP you know you own.

This is a feature that fell through the cracks. It was supposed to work (and may even have worked at some point), but wasn't well tested and got broken along the way and then sort of accidentally designed out (temporarily).

It's on my short-list for things to fix after 1.0.

https://github.com/GoogleCloudPlatform/kubernetes/issues/10323

Mason Stewart's user avatar

  • This should probably be a comment, not an answer. –  Ward - Trying Codidact ♦ Sep 18, 2015 at 18:41
  • 5 @Ward: "It's not possible" from the dev is an answer, IMHO, and it was accepted as such. –  Sven Sep 18, 2015 at 19:03

If you're trying to use Helm to install ingress-nginx with a static external IP, here is the command that worked for me:

  • ingress-nginx docs
  • ingress-nginx values that can be overridden with --set
  • the Stack Overflow post where I found how to do this

Nathan Karasch's user avatar

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how to set a static ip for kubernetes load balancer

Load Balancing in Kubernetes: A Step-by-Step Guide

Tamerlan Gudabayev

Tamerlan Gudabayev

Load balancing is the process of distributing network traffic equally over a set of resources that support an application.

Modern applications must process millions of users simultaneously and return the correct data in a fast and reliable way.

To do that we distribute the network traffic equally which will result in better availability, scalability, security, and performance for the application.

But how do we implement load balancing?  

In non-container environments, load balancing is pretty straightforward.

But, nowadays, many applications are run on containers using technologies such as Docker and are orchestrated using Kubernetes.

Kubernetes offers several options for load balancing, depending on the type of application and the requirements of the workload.

Knowing the difference between each and its implementation will help you better decide what to use.

Today we will cover:

  • Overview of load balancing in Kubernetes.
  • Overview of ClusterIP service.
  • Overview of NodePort service.
  • Overview of Load Balancer service.
  • Overview of Ingress service.

Load Balancing in Kubernetes

In general, there are two types of load balancing that Kubernetes provide.

  • Internal – Internal load balancing refers to load-balancing traffic within a Kubernetes cluster. Internal load balancing is fairly simple and is handled by the ClusterIP service.
  • External – External load balancing is used to expose our services outside our cluster. Kubernetes provides three types of external load balancing: NodePort, LoadBalancer, and Ingress.

PS. To run all the examples below, make sure to have Kubernetes running locally using either Docker Desktop or MiniKube. Just make sure you can run commands using kubectl .  

how to set a static ip for kubernetes load balancer

ClusterIP service is the default Kubernetes service.

It provides a stable IP address that maps to one or more pods.

This allows other services within the cluster to access those pods using a consistent IP address.

Normally you can't access the ClusterIP service from the internet, but you can bypass that rule by exposing a proxy service using Kubernetes proxy.

Now that we know the theory, let's implement it.

Create a file named cluster-ip-demo.yaml with the following:

This will be our service. Currently, it's not bound to anything so let's create a sample pod.

Create a file named pod-demo.yaml with the following:

Now we can update our cluster-demo.yaml file to map our pods by their labels to the ClusterIP service.

Now that we have configured the YAML files, we have to:

  • Create and run our pods.
  • Create and run our ClusterIP service.

To run the pod, use the following command:

Next, let's create our service. Run the following command:

Now that the pods are running inside our cluster, we will expose it to external traffic using Kubernetes proxy.

Start the Kubernetes proxy using the following command:

When should you use this?

ClusterIP provides us with simple load balancing out of the box but it's only limited to internal traffic.

Which is good if that's what you're looking for.

Because it's only internal means it's secure .

But you would only want to expose this using Kubernetes proxy in two scenarios:

  • Debugging purposes.
  • Allowing internal organization traffic for monitoring, internal dashboard, etc...

how to set a static ip for kubernetes load balancer

We will now start talking about handling external traffic.

The first service we will talk about is NodePort.

NodePort is an extension of ClusterIP and provides the same functionality, but also exposes the service on a static port (ranges from 30000 to 32767) on each node in the cluster. This allows the service to be accessed externally from outside the cluster, as well as from within the cluster.

Let's create a sample NodePort service.

Create a file named node-port-demo.yaml with the following:

Huh, it seems pretty similar to our ClusterIP service.

The difference is that we specify the kind of service as NodePort and add a field named nodePort .

This field specifies which port to open on the nodes. If you don't specify this port, Kubernetes will choose the port for you. It is usually better to let Kubernetes choose the port for you because there are many caveats as to what ports are available to use.

Where would you use this?

NodePort is useful in simple projects for anything more complex or more production-ready it's not the best option. A good example of such an application is a demo app or something temporary.

The reason why it's not the recommended method:

  • You can only have one service per port.
  • You can only use ports 30000–32767.
  • If your Node/VM IP address change, you need to deal with that.

Load Balancer

how to set a static ip for kubernetes load balancer

The next service we will talk about is the Load Balancer.

It is built on top of the NodePort service but provisions and configures external load balancers from third-party providers (such as AWS, GCP, or Azure).

The load balancer then routes the traffic to the corresponding NodePort service.

Implementation of load balancer service differs between cloud providers and things change fast in the cloud world so it would be best if you use the official documentation of the provider of your choice.

Using a load balancer is the default way of exposing external traffic to a service. There is no filtering, routing, or anything else which means you can send any kind of traffic into it such as HTTP, gRPC, WebSockets, etc...  

The downsides of this approach include:

  • Complexity – Configuring and managing the Load Balancer service may require additional knowledge and skills beyond basic Kubernetes usage.
  • Cost – Depending on the cloud provider and type of Load Balancer used, there may be additional costs associated with using the Load Balancer service.
  • Latency – The Load Balancer service may introduce additional latency to your application if traffic needs to be routed through multiple layers of infrastructure.
  • Limited Features – The Load Balancer service may not provide all the features and capabilities of a dedicated load balancing solution, such as advanced traffic routing or health checks.

how to set a static ip for kubernetes load balancer

Before we begin talking about Ingress and Ingress Controllers, we have to talk about the limitation of Load Balancers in Kubernetes.

  • Lack of Flexibility – Load balancers work in layer 4 (transport layer) of the OSI model, meaning that the only thing they do is only distribute traffic based on IP addresses and ports. This makes it difficult to implement more advanced traffic routing and management rules.
  • Limited scalability – Load balancers rely on network address translation (NAT) to distribute traffic, which can limit scalability and performance in high-traffic scenarios.
  • Cost – Load balancers provided by cloud providers often come with a cost, which can add up quickly if you have multiple applications running.

This is why Ingress was created to tackle these issues.

Don't get me wrong, Ingress is NOT a Kubernetes service, it acts as a smart router behind your cluster or services.

If you want the technicalities, it's just a layer 7 (application layer) load balancer.

For example, let's define an ingress object using an NGINX as a layer 7 load balancer.

Ingress is the most powerful way to expose your services but albeit the most complicated.

There are many types of Ingress controllers from AWS ELB to Nginx and others. There are also many plugins for Ingress controllers. For example, cert-manager is a popular plugin that manages TLS certificates.

Ingress is best used when you want to:

  • Ingress provides a single entry point to your cluster which means you can expose multiple services on the same IP address and port.
  • Routing traffic based on domain name and URL path. So for example if you have a route for your backend named /api and a route for your frontend named /web .Ingress will allow you to route using one layer 7 load balancer to multiple different services.
  • Handling SSL/TLS connections. Ingress can terminate SSL/TLS connections and forward decrypted traffic to the appropriate service, allowing you to provide secure communication between your clients and services.
  • Load balance multiple services using one router. This also makes it cost-effective because you're only paying for one load balancer.
  • Implement advanced traffic routing. Ingress can implement advanced traffic routing strategies, such as canary releases, A/B testing, and blue-green deployments, allowing you to safely roll out new versions of your services without disrupting your users.

In conclusion, load balancing is a critical aspect of modern containerized applications that can help ensure optimal performance, scalability, and reliability.

With Kubernetes, load balancing is made easy through services such as ClusterIP, NodePort, LoadBalancer and Ingress (not a service but should be included).

But the best way to learn something is to not just read an article about it. I encourage everyone to experiment with the different methods mentioned in this article.

I hope this article has been informative and has provided you with valuable insights. I invite you to peruse my collection and discover more about the exciting world of [topic]. Thank you for reading, and I look forward to sharing more with you in the future!

I hope you learned something today. If you enjoyed reading it, you may want to explore some of my other articles, which cover related topics in greater depth.

Thanks for reading.

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A Guide to Kubernetes Load Balancer - Types, Examples, & Best Practices

RAJESH TILWANI

 · Tutorials

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What is Kubernetes Load Balancer?

Types of load balancers in kubernetes & when should you use them, configuring load balancer in kubernetes, traffic distribution strategies - load balancer in kubernetes, best practices for kubernetes load balancer, summary of kubernetes load balancer.

In this guide, we will talk about Kubernetes Load Balancer, its types, examples, best practices, and more.

kubernetes load balancer, load balancer in kubernetes banner

A Kubernetes LoadBalancer is a service that provides external network access to a set of pods running within a Kubernetes cluster . Kubernetes allows you to manage and scale containerized applications efficiently. 

Still, when you have multiple instances of your application (pods) running within a cluster, you often need a way to distribute incoming network traffic across these pods to ensure high availability, load distribution, and reliability. 

This is where a LoadBalancer service comes into play.

A LoadBalancer service exposes your application to the external world, allowing traffic from the internet or other networks to reach your application's pods.  It evenly distributes incoming network traffic to the pods that make up the service, ensuring that no single pod becomes overwhelmed with requests.

LoadBalancers provide redundancy and failover support. If one node in the cluster fails, traffic is redirected to healthy nodes, ensuring that your application remains available.

They are typically dynamic and can adapt to changes in your cluster. When you scale the number of pods up or down , the LoadBalancer updates its routing accordingly.

Also Read: How to Setup Multiple Apps on One Load Balancer?

In Kubernetes, there are two primary types of Load Balancers: 

External Load Balancers

Internal Load Balancers. 

Each of them is used for different purposes and is used in various scenarios based on your application's architecture and requirements.

External Load Balancers are used when you want to expose your Kubernetes services to external, public network traffic, typically from the Internet. 

They distribute incoming traffic from external clients to the pods running within your cluster.

Use Cases of External Load Balancers

Public-Facing Applications : When you have web applications, APIs, or services that must be accessible to users or clients over the internet.

High Availability : To ensure high availability and fault tolerance by distributing traffic among multiple pods.

E-commerce Websites : For applications where reliability and scalability are crucial, such as e-commerce platforms.

Content Delivery : To distribute content like media files, images, or videos across multiple pods.

For instance, an e-commerce website uses an External Load Balancer to distribute incoming web traffic to multiple web server pods for scalability and reliability.

Use an External Load Balancer when you have services that need to be accessible from the public internet. This is appropriate for applications where external users or clients need to reach your services.

Examples include web applications, APIs, public-facing services, and any system that needs to handle external traffic.

Also Read: AWS ALB vs NLB

Internal Load Balancers

Internal Load Balancers are used to route network traffic within a Kubernetes cluster or between different parts of a microservices application. 

They do not expose services to external clients but are designed for communication within the cluster.

Use Cases of Internal Load Balancers

Microservices Communication : When different microservices or components of your application need to communicate with each other, and you want to ensure load balancing among them.

Internal APIs : For managing and routing traffic between various parts of a complex application, like databases, message queues, and microservices.

Security : To isolate and secure communication between internal components of your application.

For example, consider a multi-tiered application where an Internal Load Balancer is used to distribute traffic between the frontend and backend components or to balance traffic between database replicas.

Use an Internal Load Balancer when you need to balance traffic within your cluster, but do not want to expose your services to external clients. 

This is suitable for applications with complex microservices architectures.

Examples include microservices-based applications, internal APIs, and communication between different parts of a multi-tiered application.

Also Read: How to Use Kubernetes for Microservices?

Installing Load Balancer typically involves setting up the necessary components and services to ensure that network traffic is efficiently distributed to your application's pods. 

Here's a detailed guide on how to configure it on Kubernetes.

Create a Kubernetes Deployment

Before you configure a Load Balancer, you need to have some of your applications running as pods. 

You can create pods using a Kubernetes Deployment YAML manifest, which manages the desired number of replicas of your application.

Deploy this configuration using 

Also Read: How to Use Terraform Apply?

Create a Kubernetes Service

Next, we can create a Kubernetes Service to manage the network traffic to your pods. This is necessary for load balancing as the Load Balancer is a networking component. 

Depending on your needs, you can use either the LoadBalancer or NodePort type. 

For an external Load Balancer, use the LoadBalancer type.

The type LoadBalancer tells Kubernetes to request a Load Balancer from your cloud provider.

Deploy this service configuration using

Wait for Load Balancer Provisioning

Once you deploy the LoadBalancer service, Kubernetes communicates with your cloud provider to provision the actual Load Balancer. 

This process might take some time, depending on your provider. You can check them in the Kubernetes master components section.

Also Read: The Complete Guide to Kubernetes Replicasets

Check Load Balancer Status

To check the status of your Load Balancer and get the external IP or hostname assigned to it, you can use kubectl get services . 

Wait until the EXTERNAL-IP field is populated, indicating that the Load Balancer is ready to route traffic.

Access Your Application

Now that your Load Balancer is provisioned and traffic is being distributed to your pods, you can access your application using the external IP or hostname assigned to the Load Balancer.

Scaling and Maintenance

You can scale your application by adjusting the number of replicas in your Deployment. 

Use kubectl scale deployment my-app-deployment --replicas=5 to scale to five replicas, for example.

Maintenance and updates to your application can be done by updating the Deployment to use a new container image. 

After the update, Kubernetes can perform rolling updates to ensure zero-downtime deployments.

Also Read: Top Kubernetes Monitoring Tools

Monitoring and Autoscaling

You can set up monitoring and autoscaling based on traffic or resource utilization to ensure that your application can handle varying loads efficiently. 

Kubernetes supports Horizontal Pod Autoscaling (HPA) for this purpose.

Follow the above steps properly as it is essential to accurately configure and manage your Load Balancer to ensure that your application remains highly available and scalable.

humalect developer platform, load balancer kubernetes

Load balancers use traffic distribution strategies to evenly distribute network traffic to application pods. These strategies ensure high availability and reliability within your application. 

Here is a list of methods that you can go through to understand how the traffic is distributed within a Load Balancer with a complex infrastructure.

Round Robin

In a round-robin strategy, the load balancer distributes incoming requests sequentially to each backend pod in the rotation. Once a pod receives a request, it goes to the end of the queue, and the next request is sent to the next pod in the list.

This strategy is straightforward but may not be ideal for all scenarios, especially if your pods have varying capacities or resource utilization.

Least Connections

The Least Connections strategy routes traffic to the pod with the fewest active connections. It aims to distribute traffic based on the current load on the pods. 

Pods with lower connection counts receive more traffic until they become more heavily loaded.

This strategy can be more efficient than Round Robin, especially when pods have different loads.

In an IP Hash strategy, the load balancer computes a hash based on the source IP address of the incoming request. It then maps this hash to a specific pod.

This approach can be useful when you want to maintain session persistence, ensuring that requests from the same client always go to the same pod. It's commonly used for stateful applications.

Weighted Traffic

Weighted traffic distribution allows you to assign different weights to different pods. The load balancer then uses these weights to determine how traffic should be distributed. Pods with higher weights receive more traffic.

Weighted traffic distribution is valuable when you have pods with varying capacities or resources. You can allocate more traffic to pods with more resources.

Session Affinity (Sticky Sessions)

Also known as sticky sessions, ensures that all requests from a specific client are directed to the same pod. This is achieved by associating a session identifier or cookie with a particular pod.

It is useful for applications that require stateful communication, such as those using web sessions or user logins. Session affinity can help maintain the user's session state across multiple requests.

Path-Based Routing (Ingress Controllers)

Path-based routing is a strategy used with Ingress controllers in Kubernetes. It routes traffic based on the path of the URL in the HTTP request. Different paths can be mapped to specific services or pods.

This is helpful when you want to create microservices-based applications with different services handling different parts of your application based on the URL path.

The choice of a traffic distribution strategy in Kubernetes depends on your application's needs, such as its architecture, scalability requirements, and the nature of the traffic it receives.

Understanding these strategies and selecting the most appropriate one is essential for optimizing the performance, reliability, and scalability of your Kubernetes-based applications.

Implement health checks

Implement health checks to ensure that the Load Balancer directs traffic only to healthy pods. Health checks regularly monitor the status of your pods and exclude unhealthy ones from receiving traffic. 

Example: Define a health check probe in your Kubernetes Service configuration.

Use Session Affinity

Use session affinity (sticky sessions) when your application requires maintaining a user session state across multiple requests. This ensures that a user's requests go to the same pod. 

Example: Enable session affinity in your Kubernetes Service configuration.

Also Read: How to Fix OOMKilled Error in Kubernetes?

Set Resource Limits

Set resource limits and requests for your pods to ensure they don't consume all available resources. This prevents overloading pods and degrades performance. 

Example: Define resource limits and requests in your Deployment configuration.

Security & RBAC

Configure proper security and access control for your Load Balancer, services, and pods using Kubernetes RBAC and network policies .

humalect developer platform, load balancer kubernetes

In conclusion, load balancers play a pivotal role in modern application deployment and scalability. They act as traffic guardians, efficiently distributing requests to ensure high availability, fault tolerance, and optimal resource utilization. 

Implementing the best practices outlined here, such as health checks, session persistence, resource management, scaling, monitoring, and security measures, can help you harness the full potential of load balancers within your Kubernetes environment . 

By adhering to these practices, you can build and maintain resilient, high-performing applications that meet the demands of today's dynamic and ever-evolving digital landscape.

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Kubernetes Blog

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Kubernetes 1.24: Avoid Collisions Assigning IP Addresses to Services

Author: Antonio Ojea (Red Hat)

In Kubernetes, Services are an abstract way to expose an application running on a set of Pods. Services can have a cluster-scoped virtual IP address (using a Service of type: ClusterIP ). Clients can connect using that virtual IP address, and Kubernetes then load-balances traffic to that Service across the different backing Pods.

How Service ClusterIPs are allocated?

A Service ClusterIP can be assigned:

Across your whole cluster, every Service ClusterIP must be unique. Trying to create a Service with a specific ClusterIP that has already been allocated will return an error.

Why do you need to reserve Service Cluster IPs?

Sometimes you may want to have Services running in well-known IP addresses, so other components and users in the cluster can use them.

The best example is the DNS Service for the cluster. Some Kubernetes installers assign the 10th address from the Service IP range to the DNS service. Assuming you configured your cluster with Service IP range 10.96.0.0/16 and you want your DNS Service IP to be 10.96.0.10, you'd have to create a Service like this:

but as I explained before, the IP address 10.96.0.10 has not been reserved; if other Services are created before or in parallel with dynamic allocation, there is a chance they can allocate this IP, hence, you will not be able to create the DNS Service because it will fail with a conflict error.

How can you avoid Service ClusterIP conflicts?

In Kubernetes 1.24, you can enable a new feature gate ServiceIPStaticSubrange . Turning this on allows you to use a different IP allocation strategy for Services, reducing the risk of collision.

The ClusterIP range will be divided, based on the formula min(max(16, cidrSize / 16), 256) , described as never less than 16 or more than 256 with a graduated step between them .

Dynamic IP assignment will use the upper band by default, once this has been exhausted it will use the lower range. This will allow users to use static allocations on the lower band with a low risk of collision.

Service IP CIDR block: 10.96.0.0/24

Range Size: 2 8 - 2 = 254 Band Offset: min(max(16, 256/16), 256) = min(16, 256) = 16 Static band start: 10.96.0.1 Static band end: 10.96.0.16 Range end: 10.96.0.254

Service IP CIDR block: 10.96.0.0/20

Range Size: 2 12 - 2 = 4094 Band Offset: min(max(16, 4096/16), 256) = min(256, 256) = 256 Static band start: 10.96.0.1 Static band end: 10.96.1.0 Range end: 10.96.15.254

Service IP CIDR block: 10.96.0.0/16

Range Size: 2 16 - 2 = 65534 Band Offset: min(max(16, 65536/16), 256) = min(4096, 256) = 256 Static band start: 10.96.0.1 Static band ends: 10.96.1.0 Range end: 10.96.255.254

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  • Google Kubernetes Engine (GKE)
  • Documentation

Set up an external Application Load Balancer with Ingress

This tutorial shows how to run a web application behind an external Application Load Balancer by configuring the Ingress resource.

Google Kubernetes Engine (GKE) offers integrated support for two types of Cloud Load Balancing for a publicly accessible application:

External passthrough Network Load Balancer

In this tutorial, you use Ingresses .

When you specify kind: Ingress in a resource manifest, you instruct GKE to create an Ingress resource. By including annotations and supporting workloads and Services, you can create a custom Ingress controller. Otherwise, GKE makes appropriate Google Cloud API calls to create an external Application Load Balancer . The load balancer's URL map's host rules and path matchers reference one or more backend services, where each backend service corresponds to a GKE Service of type NodePort , as referenced in the Ingress . The backends for each backend service are either instance groups or network endpoint groups (NEGs). NEGs are created when you configure container-native load balancing as part of the configuration for your Ingress. For each backend service, GKE creates a Google Cloud health check, based on the readiness probe settings of the workload referenced by the corresponding GKE Service .

If you are exposing an HTTP(S) service hosted on GKE, HTTP(S) load balancing is the recommended method for load balancing.

  • Create a GKE cluster.
  • Deploy the sample web application to the cluster.
  • Expose the sample app to the internet behind an external Application Load Balancer.

In this document, you use the following billable components of Google Cloud:

To generate a cost estimate based on your projected usage, use the pricing calculator . New Google Cloud users might be eligible for a free trial .

When you finish the tasks that are described in this document, you can avoid continued billing by deleting the resources that you created. For more information, see Clean up .

Before you begin

  • Visit the Kubernetes Engine page in the Google Cloud console.
  • Create or select a project.
  • Wait for the API and related services to be enabled. This can take several minutes.

Make sure that billing is enabled for your Google Cloud project .

Install the following command-line tools used in this tutorial:

  • gcloud is used to create and delete Kubernetes Engine clusters. gcloud is included in the gcloud CLI .
  • kubectl is used to manage Kubernetes, the cluster orchestration system used by Kubernetes Engine. You can install kubectl using gcloud : gcloud components install kubectl

Clone the sample code from GitHub:

Set defaults for the gcloud command-line tool

Create a gke cluster.

Create a GKE Autopilot cluster:

Deploying a web application

The following manifest describes a Deployment that runs the sample web application container image on an HTTP server on port 8080:

Apply the resource to the cluster:

Exposing your Deployment inside your cluster

The following manifest describes a Service that makes the web deployment accessible within your container cluster:

When you create a Service of type NodePort with this command, GKE makes your Service available on a randomly selected high port number (e.g. 32640) on all the nodes in your cluster.

Verify that the Service is created and a node port is allocated:

In the sample output, the node port for the web Service is 32640 . Also, note that there is no external IP allocated for this Service. Since the GKE nodes are not externally accessible by default, creating this Service does not make your application accessible from the internet.

To make your HTTP(S) web server application publicly accessible, you must create an Ingress resource.

Creating an Ingress resource

Ingress is a Kubernetes resource that encapsulates a collection of rules and configuration for routing external HTTP(S) traffic to internal services.

On GKE, Ingress is implemented using Cloud Load Balancing . When you create an Ingress in your cluster, GKE creates an HTTP(S) load balancer and configures it to route traffic to your application.

The following manifest describes an Ingress resource that directs traffic to your web Service:

After you deploy this manifest, Kubernetes creates an Ingress resource on your cluster. The GKE Ingress controller creates and configures an HTTP(S) Load Balancer according to the information in the Ingress, routing all external HTTP traffic (on port 80) to the web NodePort Service you exposed.

Visiting your application

Find out the external IP address of the load balancer serving your application by running:

Open the external IP address of your application in a browser and see a plain text HTTP response like the following:

You can visit Load Balancing on the Google Cloud console and inspect the networking resources created by the GKE Ingress controller.

(Optional) Configuring a static IP address

When you expose a web server on a domain name, you need the external IP address of an application to be a static IP that does not change.

By default, GKE allocates ephemeral external IP addresses for HTTP applications exposed through an Ingress. Ephemeral addresses are subject to change. If you are planning to run your application for a long time, you must use a static external IP address .

Note that after you configure a static IP for the Ingress resource, deleting the Ingress does not delete the static IP address associated with it. Make sure to clean up the static IP addresses you configured when you no longer plan to use them again.

To configure a static IP address, complete the following steps:

Reserve a static external IP address named web-static-ip :

Config Connector

Note: This step requires Config Connector . Follow the installation instructions to install Config Connector on your cluster.

The basic-ingress-static.yaml manifest adds an annotation on Ingress to use the static IP resource named web-static-ip :

View the manifest:

Check the external IP address:

Wait until the IP address of your application changes to use the reserved IP address of the web-static-ip resource.

It might take a few minutes to update the existing Ingress resource, re-configure the load balancer, and propagate the load balancing rules across the globe. After this operation completes, GKE releases the ephemeral IP address previously allocated to your application.

(Optional) Serving multiple applications on a load balancer

You can run multiple services on a single load balancer and public IP by configuring routing rules on the Ingress. By hosting multiple services on the same Ingress, you can avoid creating additional load balancers (which are billable resources) for every Service that you expose to the internet.

The following manifest describes a Deployment with version 2.0 of the same web application:

The following manifest describes a Service that exposes web2 internally to the cluster on a NodePort Service called web2 :

The following manifest describes an Ingress resource that:

  • routes the requests with path starting with /v2/ to the web2 Service
  • routes all other requests to the web Service

After the Ingress is deployed, run kubectl get ingress fanout-ingress to find out the public IP address of the cluster.

Then visit the IP address to see that both applications are reachable on the same load balancer:

  • Visit http://<IP_ADDRESS>/ and note that the response contains Version: 1.0.0 (as the request is routed to the web Service)
  • Visit http://<IP_ADDRESS>/v2/ and note that the response contains Version: 2.0.0 (as the request is routed to the web2 Service)

The only supported wildcard character for the path field of an Ingress is the * character. The * character must follow a forward slash ( / ) and must be the last character in the pattern. For example, /* , /foo/* , and /foo/bar/* are valid patterns, but * , /foo/bar* , and /foo/*/bar are not.

A more specific pattern takes precedence over a less specific pattern. If you have both /foo/* and /foo/bar/* , then /foo/bar/bat is taken to match /foo/bar/* .

For more information about path limitations and pattern matching, see the URL Maps documentation .

(Optional) Monitoring the availability and latency of your service

Google Cloud Uptime checks perform blackbox monitoring of applications from the viewpoint of the user, determining latency and availability from multiple external IPs to the IP address of the load balancer. In comparison, Google Cloud health checks perform an internal check against the Pod IPs, determining availability at the instance level. The checks are complementary and provide a holistic picture of application health.

You can create an uptime check by using the Google Cloud console, the Cloud Monitoring API, or by using the Cloud Monitoring client libraries. For information, see Managing uptime checks . If you want to create an uptime check by using the Google Cloud console, do the following:

Go to the Services & Ingress page in the Google Cloud console.

Go to Services & Ingress

Click the name of the Service you want to create an uptime check for.

Click Create Uptime Check .

In the Create Uptime Check pane, enter a title for the uptime check and then click Next to advance to the Target settings.

The Target fields of the uptime check are automatically filled in using the information from the Service load balancer.

For complete documentation on all the fields in an uptime check, see Creating an uptime check .

Click Next to advance to the Response Validation settings.

Click Next to advance to the Alert and Notification section.

To monitor an uptime check, you can create an alerting policy or view the uptime check dashboard. An alerting policy can notify you by email or through a different channel if your uptime check fails. For general information about alerting policies, see Introduction to alerting .

Click Create .

By default, Ingress performs a periodic health check by making a GET request on the / path to determine the health of the application, and expects a HTTP 200 response. If you want to check a different path or to expect a different response code, you can use a custom health check path .

Ingress supports more advanced use cases, such as:

Name-based virtual hosting: You can use Ingress to reuse the load balancer for multiple domain names, subdomains, and to expose multiple Services on a single IP address and load balancer. Check out the simple fanout and name-based virtual hosting examples to learn how to configure Ingress for these tasks.

HTTPS termination : You can configure the Ingress to terminate the HTTPS traffic using the Cloud Load Balancer.

When an Ingress is deleted, the GKE Ingress controller cleans up the associated resources (except reserved static IP addresses) automatically.

To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources.

Delete any manually created forwarding rules and target proxies that reference the Ingress:

A dangling target proxy that is referencing a GKE Ingress controller managed URL map will cause the deletion of the Ingress to fail in GKE versions 1.15.4-gke.22+. Inspect the Ingress resource to find an event with an error message similar to the following: Error during GC: error running load balancer garbage collection routine: googleapi: Error 400: The url_map resource 'projects/ project-id /global/urlMaps/k8s2-um-tlw9rhgp-default-my-ingress-9ifnni82' is already being used by 'projects/ project-id /global/targetHttpsProxies/k8s2-um-tlw9rhgp-default-my82-target-proxy', resourceInUseByAnotherResource

In the preceding error message, k8s2-um-tlw9rhgp-default-my82-target-proxy is a manually created target https proxy that is still referencing the URL map k8s2-um-tlw9rhgp-default-my-ingress-9ifnni82 which was created and managed by an Ingress controller.

These manually created frontend resources (both forwarding rule and target proxy) must be deleted before proceeding with the deletion of the Ingress.

Delete the Ingress: This step deallocates the ephemeral external IP address and the load balancing resources associated with your application:

kubectl delete ingress basic-ingress

If you followed the optional step to create an Ingress to route requests by path, then delete the Ingress:

kubectl delete ingress fanout-ingress

Delete the static IP address: Complete this step only if you followed the optional step to create a static IP address.

If you followed "Option 1" to convert an existing ephemeral IP address to static IP, then visit the Google Cloud console to delete the static IP address.

If you followed "Option 2" to create a new static IP address, then run the following command to delete the static IP address:

Delete the cluster: This step deletes the compute nodes of your container cluster and other resources such as the Deployments in the cluster:

gcloud container clusters delete loadbalancedcluster

What's next

  • Check out the Ingress user guide for details about Ingress features.
  • Configure static IP and a domain name for your Ingress application using Ingress.
  • Configure SSL certificates for your Ingress load balancer.
  • Learn about using Google-managed SSL certificates with Ingress .

If you have an application running on multiple Kubernetes Engine clusters in different regions, set up a multi-cluster Ingress to route traffic to a cluster in the region closest to the user.

Explore other Kubernetes Engine tutorials .

Explore reference architectures, diagrams, and best practices about Google Cloud. Take a look at our Cloud Architecture Center .

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2024-02-23 UTC.

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Kubernetes Ingress Controllers: Routing And Load Balancing For Services

In the dynamic landscape of containerized applications, efficiently orchestrating and managing services is critical. As an effective platform for container orchestration, Kubernetes offers a stable foundation for launching, growing, and overseeing containerized applications. The Ingress controller is a crucial part of Kubernetes that helps with efficient service administration.

We’ll examine the nuances of Kubernetes Ingress controllers in this extensive post, including how they function in service load balancing and routing. To assist you in understanding the principles and implementation specifics, we’ll go over the essentials, explore their functioning mechanisms, and offer practical examples.

Understanding Kubernetes Ingress Controllers

What is an ingress controller.

In the Kubernetes ecosystem, an Ingress is an API object that provides HTTP and HTTPS routing to services based on rules defined by the user. It acts as a way to expose services to the external world and enables traffic management for different applications within a Kubernetes cluster.

An Ingress Controller, on the other hand, is a component that implements the rules specified in the Ingress resource. It acts as a traffic manager, handling incoming requests, and directing them to the appropriate services within the cluster. In essence, the Ingress Controller is responsible for managing the external access and load balancing of services.

Key Components of Ingress Controllers

  • Ingress Resource : This is a Kubernetes API object that defines how external HTTP/S traffic should be processed, including rules for routing to different services.
  • Ingress Controller : The actual implementation of the Ingress resource. It can be implemented using various technologies like Nginx, Traefik, or HAProxy, each offering unique features and capabilities.
  • Load Balancer : Often, cloud providers offer load balancing services that work in tandem with Ingress Controllers to distribute incoming traffic across multiple pods of a service.
  • Rules and Paths : In the Ingress resource, rules and paths are defined to specify how different requests should be directed to different services. This includes setting up routing based on paths, domains, or header values.

How Ingress Controllers Work

Request flow in kubernetes ingress.

Understanding the flow of an incoming request through the Ingress system is crucial for grasping the role of Ingress Controllers. Here’s a simplified overview:

  • Ingress Resource Creation : A user defines an Ingress resource, specifying rules for routing traffic to different services.
  • Ingress Controller Watches for Changes : The Ingress Controller continuously monitors the Kubernetes API for changes in Ingress resources.
  • Configuration Update : When a new Ingress resource is created or an existing one is modified, the Ingress Controller updates its configuration accordingly.
  • Load Balancer Configuration (if applicable): In a cloud environment, the Ingress Controller may interact with the cloud provider’s load balancer service to update the routing rules.
  • Routing to Services : Incoming requests are directed to the appropriate service based on the rules defined in the Ingress resource.

Example: Nginx Ingress Controller

Let’s explore a practical example using the Nginx Ingress Controller, one of the popular implementations.

Installation

Ensure you have kubectl configured to connect to your cluster.

Kubectl apply

This command deploys the Nginx Ingress Controller to your cluster.

Creating an Ingress Resource

Now, let’s create a simple Ingress resource to route traffic to a specific service.

In this example, any request to `example.com/app` will be directed to the `app-service` on port 80.

Apply this configuration to your cluster:

Expected/Similar Ouput: ingress.networking.k8s.io/example-ingress created

Testing the Ingress

You can now test the Ingress by sending a request to the specified host and path. Ensure you have the necessary DNS configurations or modify your local hosts file to map `example.com` to the cluster’s IP address.

Testing ingress

If your output looks like this then, the Ingress configuration is working, and you successfully received a response from the `app-service` . The HTML content you see is a placeholder from the “ Example Domain ” and is indicative that the request was correctly routed to the specified service.

This confirms that the Ingress Controller is functioning as expected, and the path-based routing, as defined in the Ingress resource, is directing traffic to the appropriate backend service.

Advanced Features of Ingress Controllers

Ssl/tls termination.

Ingress Controllers often provide the ability to terminate SSL/TLS encryption at the controller level, offloading the decryption process from individual services. This is achieved by specifying TLS settings in the Ingress resource.

Path-based Routing and Rewrites

Ingress Controllers support path-based routing, allowing you to direct requests to different services based on the specified paths. Additionally, URL rewrites can be configured to modify the requested path before forwarding it to the backend service.

In conclusion, Kubernetes Ingress Controllers play a vital role in managing external access and load balancing for services within a Kubernetes cluster. Understanding their fundamentals, components, and working mechanisms is essential for efficiently managing and routing traffic to various services.

In this guide, we’ve covered the basics of Ingress Controllers, their key components, and provided a hands-on example using the Nginx Ingress Controller. Additionally, we explored advanced features such as SSL/TLS termination, path-based routing, and host-based routing to give you a comprehensive understanding of their capabilities.

As you continue to explore Kubernetes and container orchestration, mastering Ingress Controllers will empower you to design scalable and efficient architectures for your applications. Experiment with different Ingress Controllers, explore their unique features, and tailor your configurations to meet the specific requirements of your containerized workloads.

ubernetes Ingress Controllers – FAQ’s

How do I check if the Ingress Controller is running in my Kubernetes cluster?

A. Use the `kubectl get pods` command to list all pods in the specified namespace. Look for the pod running the Ingress Controller (e.g., Nginx Ingress Controller). kubectl get pods -n <namespace>

What is the difference between an Ingress and an Ingress Controller?

A. An Ingress is a Kubernetes API object that defines how external HTTP/S traffic should be processed, while an Ingress Controller is the actual implementation of the Ingress resource. It manages external access, routing, and load balancing based on the rules defined in the Ingress.

How can I troubleshoot issues with my Ingress configuration?

A. Use `kubectl describe ingress` to get detailed information about the Ingress resource, including any errors or misconfigurations. Check for events and conditions that might help identify and resolve issues. kubectl describe ingress <ingress-name>

Can I use wildcard domains with Ingress for routing?

A. Yes, Ingress resources support wildcard domains. You can define rules with wildcards in the host field, such as `*.example.com` , to route traffic to different services based on subdomains.

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Kubernetes Load Balancer: What Are the Options?

Guy Menachem

How Does Load Balancing Work in Kubernetes? 

Kubernetes, an open-source platform for automating deployment, scaling, and operations of application containers, has become increasingly popular in managing containerized applications across various environments. In such a dynamic environment, load balancing is a critical component. Load balancing in Kubernetes refers to the method of distributing network traffic across multiple servers or pods to ensure that no single pod gets overwhelmed, thereby enhancing the overall efficiency and reliability of applications.

Kubernetes facilitates load balancing in two primary ways: internally within the cluster, and externally for accessing applications from outside the cluster. Internally, you can use a ClusterIP service to direct traffic to pods, ensuring smooth operation even if pods are replaced in a Deployment. Externally, you would typically use services of type NodePort or LoadBalancer, or the more powerful Ingress controllers, to manage inbound traffic from outside the cluster.

Keep in mind that Kubernetes does not provide a built-in load balancer. It can provide basic traffic routing functionality, but for full load balancing, you will need to use an external load balancer. On most cloud providers, this is done automatically when you set up a Service of type LoadBalancer. An Ingress object provides more control and lets you integrate with the load balancer of your choice.

This is part of a series of articles about Kubernetes management

Types of Load Balancers in Kubernetes 

Internal traffic routing with clusterip service.

ClusterIP is the default type of Service in Kubernetes. A Service is a way to provide a stable network address for applications running in one or more pods within the cluster. ClusterIP services allow you to expose an application internally, making it accessible only within the cluster and not from the outside world. This can be particularly useful for multi-tier applications where some parts of the application need to communicate with others but should not be exposed externally.

External Traffic Routing with NodePort

NodePort is another type of Kubernetes Service that allows you to expose your application externally. It does this by opening a specific port on each node in the cluster, and any traffic that is sent to this port is forwarded to the Service. This makes your application accessible from outside the cluster, which can be particularly useful for applications that need to be accessed by external users or systems.

External Load Balancing with a LoadBalancer Service

LoadBalancer is another type of Service that provides an external IP address. Kubernetes does not provide built-in load balancer functionality—on most cloud providers, creating a LoadBalancer of Service automatically provisions a load balancer for the Service. This load balancer can then distribute incoming traffic to multiple pods, ensuring that the workload is evenly distributed.

how to set a static ip for kubernetes load balancer

Using an Ingress with an External Load Balancer

An Ingress is a Kubernetes resource that manages external access to the services in a cluster. It can provide load balancing, SSL termination, and name-based virtual hosting, among other things. When combined with an external load balancer, it can provide a flexible solution for managing traffic to your applications.

how to set a static ip for kubernetes load balancer

Should You Use a LoadBalancer Service or Ingress? 

The question of whether to use a LoadBalancer service or Ingress often arises when dealing with Kubernetes systems. 

A LoadBalancer Service is a viable option when you only have a handful of services you need to reveal. As the number of Services grows, you might run into a few difficulties. For example, restricted ability to specify URLs, dependence on cloud providers, lack of SSL termination, and no support for URL rewriting or rate limiting

An Ingress is more suitable when you need to evenly distribute loads across a large number of services. Ingress sets rules for incoming traffic, managing routing based on the URL path and hostname. This allows you to use a LoadBalancer to expose multiple services while controlling the inbound network flow to your cluster.

In addition to the basic functionality of the Kubernetes LoadBalancer service, Ingress controllers typically provide enhanced URL routing, URL path-oriented routing, routing based on hostname, SSL termination, URL rewriting, and rate limiting. It’s important to note that there are multiple Ingress controllers you can use according to your use case—there are ingress controllers available from NGINX, Envoy, Traefik, and other providers.

How to Define a LoadBalancer Service 

Let’s assume you need to establish an NGINX server network cluster with three instances, and you want to load balance between them. Let’s see how to create the pods and a LoadBalancer Service that sets up an external cloud load balancer.

Note: This will only work if your cluster is deployed in a cloud provider that supports load balancing for Kubernetes, for example AWS, Azure, or Google Cloud.

To accomplish this, create a ReplicaSet composed of three pods, each running the NGINX server. Here is an example Deployment manifest that can set this up:

When you apply both the Deployment and the Service in your cluster, the Service will use a selector to associate itself with the corresponding three pods that share the same labels. 

You can run the following command to see the running pods:

The output looks something like this:

Kubernetes uses Endpoints as objects to keep the IPs of each pod updated. Each service creates its own Endpoint object, which allows the cluster to keep track of each matching pod’s IPs automatically.

You can describe your service to see how Kubernetes Endpoints enumerate the matching pods:

Kubernetes Endpoints keep the IPs updated, making traffic forwarding smoother via the Service. If pods are added, modified, or removed from the service selector, the Endpoints will update automatically. This functionality enables the Service to direct network traffic accurately to the right pods, because the Endpoints register the application’s necessary routing destination.

Each endpoint has the pod’s network IP and port and carries the same name as the Service. You can see this by describing the endpoints:

Endpoints establish a stable network identity for the pods. They dynamically adjust as pod state changes, ensuring balanced distribution of network traffic among a dynamic set of pods.

Kubernetes Troubleshooting & Reliability with Komodor

Kubernetes load balancing is complex and involves multiple components; you might experience errors that are difficult to diagnose and fix. Without the right tools and expertise in place, the troubleshooting process can become stressful, ineffective and time-consuming. Some best practices can help minimize the chances of things breaking down, but eventually something will go wrong – simply because it can.

This is where Komodor comes in – Komodor is the Continuous Kubernetes Reliability Platform, designed to democratize K8s expertise across the organization and enable engineering teams to leverage its full value.

Komodor’s platform empowers developers to confidently monitor and troubleshoot their workloads while allowing cluster operators to enforce standardization and optimize performance.

By leveraging Komodor, companies of all sizes significantly improve reliability, productivity, and velocity. Or, to put it simply – Komodor helps you spend less time and resources on managing Kubernetes, and more time on innovating at scale.

If you are interested in checking out Komodor, use this link to sign up for a Free Trial . 

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NSX Advanced Load Balancer as L7 Ingress Controller

To use NSX Advanced Load Balancer as ingress controller in Kubernetes cluster, you must have the NSX ALB Enterprise version. Alternatively, you can use Contour as your ingress controller in your Tanzu Kubernetes Grid clusters.

When integrated though AKO in Tanzu Kubernetes Grid, NSX ALB supports three ingress modes: NodePort, ClusterIP, and NodePortLocal. Choose a type based on your requirement.

When choosing to use the NodePort mode for NSX ALB ingress, the ingress backend service must be NodePort mode. In this type, the network traffic is routed from the client to the NSX ALB SE, and then to the cluster nodes, before it reaches the pods. The NSX ALB SE routes the traffic to the nodes, and kube-proxy helps route the traffic from the nodes to the target pods.

The following diagram describes how the network traffic is routed in the NodePort mode:

Network Traffic in the NodePort mode

The NodePort mode supports sharing an NSX ALB SE between different clusters. However, this type of service can expose a port in the cluster as it requires to use the NodePort mode backend service. It also requires an extra hop for kube-proxy to route traffic from node to pod.

To configure the NodePort ingress mode on the management cluster:

Create a AKODeploymentConfig CR object as follows:

Apply the changes on the management cluster:

To enable the NodePort ingress mode on the workload clusters, create a workload cluster configuration YAML file, and add the following field:

Deploy the workload cluster by using the tanzu cluster create command.

For more information on deploying workload clusters to vSphere, see Create Workload Clusters .

NSX ALB ingress service provider is now configured to use the NodePort mode on the workload clusters that have the AVI_LABELS that match with the cluster selector in the install-ako-l7-node-port AKODeploymentConfig object.

In the ClusterIP mode, the network traffic is routed from the client to the NSX ALB SE, and then to the pods. This mode requires ClusterIP as the ingress backend service type. The NSX ALB SE routes the traffic to the pods by leveraging the static routes.

The following diagram describes how the network traffic is routed in the ClusterIP mode:

Network Traffic in the ClusterIP mode

The ClusterIP mode simplifies the network traffic by routing it directly from the SE to the pods. This mode also prevents the exposure of the ports in a cluster. However, in this mode, SEs cannot be shared between clusters because an SE must be attached to a cluster.

To enable this feature:

To enable the ClusterIP ingress mode on the workload clusters, create a workload cluster configuration YAML file, and add the following field:

NSX ALB ingress service provider is now configured to use the ClusterIP mode on the workload clusters that have the AVI_LABELS that match with the cluster selector in the install-ako-l7-cluster-ip AKODeploymentConfig object.

To enable the ClusterIP ingress mode on other workload clusters, you must create a new SE in Avi Controller, and then create a new AKODeploymentConfig object specifying the name of the new SE before applying the file on the management cluster.

NodePortLocal (For Antrea CNI)

If you use Antrea as the CNI, you can enable the NodePortLocal ingress mode on NSX ALB. It leverages the NodePortLocal feature of Antrea to directly route the traffic from the SE to the pod. In this mode, the network traffic is routed from the client to the NSX ALB SE, and then to the pods. This mode requires ClusterIP as the ingress backend type. Additionally, the ANTREA_NODEPORTLOCAL configuration variable must be set to true in Tanzu Kubernetes Grid. For more information on the NodePortLocal feature in Antrea, see NodePortLocal (NPL) in the Antrea Documentation.

Note NSX ALB NodePortLocal ingress mode is not supported for management clusters. You cannot run NSX ALB as a service type with ingress mode NodePortLocal for traffic to the management cluster. You can only configure NodePortLocal ingress to workload clusters. Configure management clusters with AVI_INGRESS_SERVICE_TYPE set to either NodePort or ClusterIP . Default is NodePort .

The following diagram describes how the network traffic is routed in the NodePortLocal mode:

Network Traffic in the NodePortLocal mode

The NodePortLocal mode simplifies the network traffic by routing it directly from the SE to the pods. This mode supports shared SEs for the clusters and prevents the exposure of the ports in a cluster.

To enable the NodePortLocal ingress mode on the workload clusters, create a workload cluster configuration YAML file, and add the following field:

NSX ALB ingress service provider is now configured to use the NodePortLocal mode on the workload clusters that have the AVI_LABELS that match with the cluster selector in the install-ako-l7-node-port-local AKODeploymentConfig object.

IPv4/IPv6 Dual-Stack Support

For information about how to create dual-stack clusters, see Create Dual-Stack Clusters with NSX Advanced Load Balancer as L7 Ingress Controller .

NSX ALB L7 Ingress Support in Management Cluster

Only the NodePort ingress mode is supported in the management cluster if you use NSX ALB as the cluster endpoint VIP provider. If you do not use NSX ALB as cluster endpoint VIP provider, all the three ingress modes are supported.

To enable L7 ingress in management cluster:

Edit the AKODeploymentConfig file in the management cluster:

In the file that opens, modify the spec.extraConfigs.ingress field as shown in the following example:

how to set a static ip for kubernetes load balancer

Kubernetes (K8s) containers and environments are the leading approach to packaging, deploying and managing containerized applications at scale. The dynamic, open-source , microservices-based configuration of Kubernetes can be a great fit for businesses that are looking to maximize infrastructure agility. However, the distributed flexibility that makes Kubernetes appealing can also make implementing Kubernetes monitoring and observability practices challenging.

Observability comprises a range of processes and metrics that help teams gain actionable insights into a system’s internal state by examining system outputs. It’s an essential part of maintaining any IT infrastructure. But managing the sheer volume of data, nodes, pods, services and endpoints that comprise Kubernetes environments requires observability practices that are appropriate for the job.

In this blog, we discuss how Kubernetes observability works, and how organizations can use it to optimize cloud-native IT architectures.

How does observability work?

Broadly speaking, observability describes how well internal system states can be inferred from external outputs. It’s the ability to diagnose and understand why a system is behaving in a particular way, which is vital to troubleshooting, deciphering performance issues and improving system design.

In DevOps , the concept of observability has evolved to refer to the end-to-end visibility of a system state as dictated by telemetry data. The primary data classes used—known as the three pillars of observability—are logs, metrics and traces.

Logs include discrete events recorded every time something occurs in the system, such as status or error messages, or transaction details. Kubernetes logs can be written in both structured and unstructured text.

CPU usage, memory consumption, network I/O, request latency or any business-specific indicators. Kubernetes metrics are often aggregated to create time-series observability data that can help teams spot trends and identify patterns.

Traces help teams follow a request or transaction through the various services and components of a distributed system. They also help teams visualize the dependencies between different components of an infrastructure so that delays and errors can be located quickly.

Achieving successful observability requires the deployment of appropriate Kubernetes monitoring tools and the implementation of effective processes for collecting, storing and analyzing the three primary outputs. This might include setting up and maintaining monitoring systems, application log aggregators, application performance management (APM) tools or other observability platforms.

However, Kubernetes environments also necessitate a more thorough examination of standard metrics. Kubernetes systems comprise a vast environment of interconnected containers, microservices and other components, all of which generate large amounts of data. Kubernetes schedules and automates container-related tasks throughout the application lifecycle, including:

Kubernetes can deploy a specific number of containers to a specific host and keep them running in their desired state.

A rollout is a Kubernetes deployment modification. Kubernetes enables teams to initiate, pause, resume and roll back rollouts.

Service discovery

Kubernetes can automatically expose a container to the internet or other containers using a  DNS  name or IP address.

Autoscaling

When traffic spikes, Kubernetes can automatically spin up new clusters to handle the additional workload .

Storage provisioning

Teams can set up Kubernetes to mount persistent local or cloud storage for containers.

Load balancing

Based on CPU utilization or custom metrics, Kubernetes  load balancing  features can distribute workloads across the network to maintain performance and stability.

Self-healing for high availability

Kubernetes can automatically debug , restart or replace a failed container to prevent downtime. It can also decommission containers that don’t meet health check requirements.

With so many shifting, interacting and layered components comes as many potential issues and failure points, therefore lots of areas where real-time monitoring becomes a necessity. It also means that a conventional approach to monitoring logs, metrics and traces might prove insufficient for observability in a Kubernetes environment.

Kubernetes observability principles

Because every component in a Kubernetes architecture is interdependent on other components, observability requires a more holistic approach.

Kubernetes observability requires organizations to go beyond collecting and analyzing cluster-level data from logs, traces and metrics; connecting data points to better understand relationships and events within Kubernetes clusters is central to the process. This means that organizations must rely on a tailored, cloud-native observability strategy and scrutinize every available data source within the system.

Observability in a K8s environment involves:

1. Moving beyond metrics, logs and apps . Much like virtual machine (VM) monitoring, Kubernetes observability must account for all log data (from containers, master and worker nodes, and the underlying infrastructure) and app-level metrics. However, unlike VMs, Kubernetes orchestrates container interactions that transcend apps and clusters. As such, Kubernetes environments house enormous amounts of valuable data both outside and within network clusters and apps. This includes data in CI/CD pipelines (which feed into K8s clusters) and GitOps workflows (which power K8s clusters).

Kubernetes also doesn’t expose metrics, logs and trace data in the same way traditional apps and VMs do. Kubernetes tends to capture data “snapshots,” or information captured at a specific point in the lifecycle. In a system where each component within every cluster records different types of data in different formats at different speeds, it can be difficult—or impossible—to establish observability by simply analyzing discrete data points.

What’s more, Kubernetes doesn’t create master log files at either the app or cluster level. Every app and cluster records data in its respective environment, so users must aggregate and export data manually to see it all in one place. And since containers can spin up, spin down or altogether disappear within seconds, even manually aggregated data can provide an incomplete picture without proper context.

2. Prioritizing context and data correlation . Both monitoring and observability are key parts of maintaining an efficient Kubernetes infrastructure. What differentiates them is a matter of objective. Whereas monitoring helps clarify what’s going on in a system, observability aims to clarify why the system is behaving the way that it is. To that end, effective Kubernetes observability prioritizes connecting the dots between data points to get to the root cause of performance bottlenecks and functionality issues.

To understand Kubernetes cluster behavior, you must understand each individual event in a cluster within the context of all other cluster events, the general behavior of the cluster, and any events that led up to the event in question.

For instance, if a pod starts in one worker node and terminates in another, you need to understand all the events that are happening simultaneously in the other Kubernetes nodes, and all the events that are happening across your other Kubernetes services, API servers and namespaces to get a clear understanding of the change, its root cause, and its potential consequences.

In other words, merely monitoring tasks is often inadequate in a Kubernetes environment. To achieve Kubernetes observability, get relevant system insights or conduct accurate accurate root cause analyses , IT teams must be able to aggregate data from across the network and contextualize it.

3. Using Kubernetes observability tools . Implementing and maintaining Kubernetes observability is a large, complex undertaking. However, using the right frameworks and tools can simplify the process and improve overall data visualization and transparency.

Businesses can choose from a range of observability solutions, including programs that automate metrics aggregation and analysis (like Prometheus and Grafana), programs that automate logging (like ELK, Fluentd and Elasticsearch) and programs that facilitate tracing visibility (like Jaeger). Integrated solutions, like OpenTelemetry, can manage all three major observability practices. And customized, cloud-native solutions, like Google Cloud Operations, AWS X-Ray, Azure Monitor and and IBM Instana Observability , offer observability tools and Kubernetes dashboards optimized for clusters that are running on their infrastructure.

Best practices for optimizing Kubernetes observability

• Define your KPIs . Figure out which key performance indicators, like app performance, system health and resource usage, give you the most useful insights into your infrastructure’s behavior. Revise them as needed. • Centralize logging . K8s environments generate massive amounts of data. Aggregating and storing it using a centralized logging solution is integral to data management. • Monitor resource usage . Collect real-time data on memory, CPU and network usage so you can proactively scale resources when necessary. • Set up alerts and alarms . Use established KPI thresholds to configure alerts and alarms. This practice allows teams to receive timely notifications when issues arise.

Establish Kubernetes observability with IBM® Instana® Observability

Kubernetes is the industry-standard container orchestration platform, managing containerized workloads with remarkable efficiency. However, the distributed, multi-layered microservices architecture of Kubernetes demands robust observability mechanisms and advanced solutions, like IBM Instana Observability.

Instana Observability provides automated Kubernetes observability and APM capabilities that are designed to monitor your entire Kubernetes application stack—from nodes and pods to containers and applications—for all Kubernetes distributions.

Observability in Kubernetes is not just a technical implementation; it’s a strategic approach that requires attentive planning and an organizational culture that values data transparency.

Instana Observability helps teams gain a comprehensive understanding of their Kubernetes environments and deliver robust, high-performing applications in an increasingly cloud-based world.

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  • This tutorial requires access to Oracle Cloud. To sign up for a free account, see Get started with Oracle Cloud Infrastructure Free Tier .
  • It uses example values for Oracle Cloud Infrastructure credentials, tenancy, and compartments. When completing your lab, substitute these values with ones specific to your cloud environment.

Configure HTTP Virtual Service on NSX Advanced Load Balancer in Oracle Cloud VMware Solution SDDC for Internet-Based Access

In this series, we have successfully deployed and configured NSX Advanced Load Balancer (formerly known as Avi Networks) controllers, established a DNS virtual service, deployed a HTTP virtual service, and enabled seamless connectivity for internal users to access web servers.

This is the fifth tutorial which extends our scope - It will guide you through the deployment of a HTTP virtual service on the NSX Advanced Load Balancer (NSX ALB) within the Oracle Cloud VMware Solution Software-Defined Data Center (SDDC), with a specific focus on making it accessible over the internet.

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  • Administrators will be able to deploy and access a HTTP virtual service on NSX Advanced Load Balancer in Oracle Cloud VMware Solution SDDC via domain name for external users or internet-based access.

Prerequisites

  • NSX ALB (Avi) controller has been deployed on the Oracle Cloud VMware Solution SDDC, see Tutorial 1: Deploy VMware NSX Advanced Load Balancer on Oracle Cloud VMware Solution SDDC .

Task 1: Set up Inbound External Connectivity for Oracle Cloud VMware Solution Overlay Segment

In the previous tutorials we have deployed, configured and set up access to the web servers only for internal users.

Now the Nginx virtual service IP needs to be mapped to public IP on Oracle Cloud Infrastructure (OCI) which will be then associated with our public domain name. This will set up external access for web servers.

To set up a demilitarized zone (DMZ) environment on Oracle Cloud VMware Solution SDDC, see A Detailed Guide to Deploy a DMZ on NSX-T for Oracle Cloud VMware Solution . Once the setup is deployed, we will have another set of NSX edges with dedicated Tier-0 and Tier-1.

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Task 2: Configure NSX ALB (Avi) Controllers

We have configured DMZ on Oracle Cloud VMware Solution and have deployed NSX ALB (Avi) controllers. We now need to set up the configuration.

Follow [ Tutorial 2: Configure VMware NSX Advanced Load Balancer on Oracle Cloud VMware Solution of this series and complete the following tasks.

Task 1: Add vCenter and NSX-T credentials

Task 2: Create Content Library on Oracle Cloud VMware Solution vCenter.

Task 3: Create DNS and IPAM profile on the NSX ALB (Avi) controller.

Note: We need to create additional NSX overlay segment.

Log in to the Oracle Cloud VMWare Solution NSX-T portal, navigate to Networking and Segments . Under NSX tab, click Add Segment .

Enter the following information and click Save .

  • Name: Enter the name.
  • Connected Gateway: Select the appropriate Tier-1 (in this tutorial, it is backed by DMZ uplink 2).
  • Transport Zone: Select Overlay-TZ transport zone.
  • Subnets: Enter the CIDR.
  • We will not enable DHCP as the web servers will have static IP.

We also need to create additional overlay network to host management networks and web servers.

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  • Continue to follow Tutorial 2: Configure VMware NSX Advanced Load Balancer on Oracle Cloud VMware Solution from Task 5, the next imperative step involves seamlessly incorporating NSX-T as a Cloud connector.

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Note: Most of the steps remain the same as per Tutorial 2: Configure VMware NSX Advanced Load Balancer on Oracle Cloud VMware Solution , the only difference is the Data Network Segment is aligned to DMZ Tier-01 as the users will be connecting over the internet.

Task 3: Configure and deploy DNS Virtual Service

To deploy DNS virtual service, see Tutorial 3: Configure DNS Virtual Service on NSX Advanced Load Balancer in Oracle Cloud VMware Solution SDDC and complete the following tasks.

  • Task 1: Define IP range on the NSX-T Cloud connector network profile.

To deploy virtual service network that is avi-vs-external on DMZ for public access, we need to refer the avi-vs-external overlay segment to Tier-1-uplink-2 DMZ uplink.

Once the set up done, now we need to deploy DNS virtual service. We will follow Task 3 of Tutorial 3: Configure DNS Virtual Service on NSX Advanced Load Balancer in Oracle Cloud VMware Solution SDDC and select the avi-vs-external for VIP that we configured earlier and other steps will be the same.

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Task 4: Configure and Deploy HTTP Virtual Service

To deploy the HTTP virtual service, see Tutorial 4: Configure HTTP Virtual Service on NSX Advanced Load Balancer in Oracle Cloud VMware Solution SDDC for Internal Users and complete Task 2, during the VIP creation we need to select VRF backed overlay segment that is avi-vs-external and other steps will remain the same.

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Task 5: Map public IP with HTTP Virtual Service private IP

We are able to access the HTTP virtual service over IP and name internally. However, to access the URL over internet we need to map the HTTP virtual service private IP with public IP.

To attach a public IP to a guest VM in Oracle Cloud VMware Solution, see Learn How to Attach a Public IP to a Guest VM in Oracle Cloud VMware Solution .

The domain used in this series demoocvs.xyz is registered with GoDaddy domain registry and we have created an entry for the same.

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To Configure Global Server Load Balancing (GSLB) to access an HTTP virtual service on Oracle Cloud VMware Solution through NSX Advanced Load Balancer over the internet, see Tutorial 6: Configure GSLB to access an HTTP virtual service on Oracle Cloud VMware Solution through NSX Advanced Load Balancer over the internet .

Acknowledgments

  • Author - Vaibhav Tiwari (Cloud VMware Solutions Specialist)

More Learning Resources

Explore other labs on docs.oracle.com/learn or access more free learning content on the Oracle Learning YouTube channel . Additionally, visit education.oracle.com/learning-explorer to become an Oracle Learning Explorer.

For product documentation, visit Oracle Help Center .

February 2024

Copyright © 2024, Oracle and/or its affiliates.

IMAGES

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    how to set a static ip for kubernetes load balancer

  2. Guide to the Kubernetes Load Balancer Service

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COMMENTS

  1. How to specify static IP address for Kubernetes load balancer?

    1 Use the loadBalancerIP field in your service declaration, as described in the current documentation: kubernetes.io/docs/user-guide/services/#type-loadbalancer - Marco Lamina Nov 4, 2016 at 21:09

  2. Use a static IP with a load balancer in Azure Kubernetes Service (AKS

    Open Cloudshell az group create --name myNetworkResourceGroup --location eastus Create an AKS cluster using the az aks create command. Azure CLI Copy Open Cloudshell az aks create --name myAKSCluster --resource-group myNetworkResourceGroup --generate-ssh-keys Create a static IP address

  3. Create an External Load Balancer

    To create an external load balancer, add the following line to your Service manifest: type: LoadBalancer Your manifest might then look like: apiVersion: v1 kind: Service metadata: name: example-service spec: selector: app: example ports: - port: 8765 targetPort: 9376 type: LoadBalancer Create a Service using kubectl

  4. How to Configure Advanced Load Balancer Settings in Kubernetes Clusters

    Because of an existing limitation in upstream Kubernetes, pods cannot talk to other pods via the IP address of an external load balancer set up through a LoadBalancer-typed service. As a workaround, you can set up a DNS record for a custom hostname (at a provider of your choice) and have it point to the external IP address of the load balancer.

  5. Configure domain names with static IP addresses

    To learn how to use Ingress to expose your applications to the internet, see Setting up an external Application Load Balancer with Ingress. Note: Static IP addresses have no cost when they are used by a load balancer. If you reserve a static IP address and don't use it, you are charged per unused IP address pricing.

  6. Create an internal load balancer

    An internal load balancer doesn't have a public IP and makes a Kubernetes service accessible only to applications that can reach the private IP. These applications can be within the same VNET or in another VNET through VNET peering. This article shows you how to create and use an internal load balancer with AKS. Note

  7. Tanzu Kubernetes Service Load Balancer with Static IP Address Example

    For the NSX-T load balancer, you have two options. The default mechanism is the same as the NSX Advanced load balancer: use an IP address taken from the IP pool configured for the load balancer when it was installed. When the static IP address is assigned, the load balancer automatically marks it as allocated and manages its lifecycle.

  8. linux

    1. The use case you described is one that is covered by ingress-controller. Ingress controller will listen to an static IP which is mapped to kubernetes service of type LoadBalancer and will then forward the traffic to the pods as required. LoadBalancer Services are used to create services that listen to traffic from outside the cluster.

  9. Use a public load balancer in Azure Kubernetes Service (AKS)

    If you'd prefer to use your own gateway, firewall, or proxy to provide outbound connection, you can skip the creation of the load balancer outbound pool and respective frontend IP by using outbound type as UserDefinedRouting (UDR). The outbound type defines the egress method for a cluster and defaults to type LoadBalancer.

  10. How to choose the external IP address of a Kubernetes load balancer in

    Likewise, once the load balancer is set up, the service's status.loadBalancer.ingress.ip field is set to its external IP address, but this doesn't seem to be a configurable setting. As an alternative, I tried manually creating a forwarding rule in the Google Compute Engine console to direct traffic from my static IP address to the target pool ...

  11. Load Balancing in Kubernetes: A Step-by-Step Guide

    Create a file named cluster-ip-demo.yaml with the following: apiVersion: v1 kind: Service metadata: name: backend spec: type: ClusterIP ports: - protocol: TCP targetPort: 80 port: 80 This will be our service. Currently, it's not bound to anything so let's create a sample pod. Create a file named pod-demo.yaml with the following:

  12. Services, Load Balancing, and Networking

    This creates a clean, backwards-compatible model where Pods can be treated much like VMs or physical hosts from the perspectives of port allocation, naming, service discovery, load balancing , application configuration, and migration. Kubernetes imposes the following fundamental requirements on any networking implementation (barring any ...

  13. Service ClusterIP allocation

    In Kubernetes, Services are an abstract way to expose an application running on a set of Pods. Services can have a cluster-scoped virtual IP address (using a Service of type: ClusterIP). Clients can connect using that virtual IP address, and Kubernetes then load-balances traffic to that Service across the different backing Pods. How Service ClusterIPs are allocated? When Kubernetes needs to ...

  14. The Only Guide to Kubernetes Load Balancer You'll Ever Need

    Next, we can create a Kubernetes Service to manage the network traffic to your pods. This is necessary for load balancing as the Load Balancer is a networking component. Depending on your needs, you can use either the LoadBalancer or NodePort type. For an external Load Balancer, use the LoadBalancer type. apiVersion: v1 kind: Service metadata:

  15. Kubernetes Load Balancer: Expert Guide With Examples

    Best practices for handling a Kubernetes load balancer. When implementing Kubernetes load balancers, take a few configuration steps to make sure your K8s deployment uses the load balancers you pick to the fullest. Here are a few best practices for working with load balancers in Kubernetes. Check whether the load balancer is enabled

  16. Kubernetes 1.24: Avoid Collisions Assigning IP Addresses to Services

    In Kubernetes 1.24, you can enable a new feature gate ServiceIPStaticSubrange . Turning this on allows you to use a different IP allocation strategy for Services, reducing the risk of collision.

  17. Set up an external Application Load Balancer with Ingress

    The load balancer's URL map's host rules and path matchers reference one or more backend services, where each backend service corresponds to a GKE Service of type NodePort, as referenced in the...

  18. Obtaining a static IP address in an unmanaged kubernetes

    ports: - containerPort: 80. Now we are going to create this deployment by executing kubectl: kubectl create -f nginx-server.yaml. On a managed cluster you would expect the load balancer to obtain an external IP address from the cloud provider. This will not happen in an unmanaged cluster in your local network. It remains pending:

  19. NSX Advanced Load Balancer as Cluster Load Balancer Service Provider

    NSX ALB is now configured as the load balancer only for the workload clusters that have the corresponding AVI_LABELS value. Configure External Static IP Address for NSX ALB. This feature leverages the Avi Kubernetes Operator (AKO) application that is deployed in the clusters. For information, see Service of Type Load Balancer with Preferred IP.

  20. Azure Kubernetes Service: Setup an Internal load balancer with static

    1 Answer Sorted by: 3 The load balancer that gets created with the AKS cluster (usually called kubernetes) is used for egress (not ingress) traffic and is a public LB, and it cannot be private. This is part of the outbound type configuration.

  21. Kube-VIP Load Balancer (Technical Preview)

    Kube-VIP provides Kubernetes clusters with a virtual IP and load balancer for both the control plane and Kubernetes services of ServiceType LoadBalancer without relying on external hardware or software. ... To configure Kube-VIP as a class-based workload cluster's load balancer service, set the following in the cluster configuration file:

  22. Manage NSX ALB Advanced Load Balancer

    Manage NSX ALB Advanced Load Balancer. Tanzu Kubernetes Grid lets you perform various management operations on your NSX Advanced Load Balancer (ALB) deployment. ... In the Controller Cluster IP field, update the IP Address or the ... If the AVI_ENABLE field is set to true when deploying a management cluster, the Tanzu CLI performs a validation ...

  23. Kubernetes Ingress Controllers: Routing And Load Balancing For Services

    Load Balancer: Often, cloud providers offer load balancing services that work in tandem with Ingress Controllers to distribute incoming traffic across multiple pods of a service. Rules and Paths: In the Ingress resource, rules and paths are defined to specify how different requests should be directed to different services. This includes setting ...

  24. Kubernetes Load Balancer: What Are the Options?

    External Load Balancing with a LoadBalancer Service. LoadBalancer is another type of Service that provides an external IP address. Kubernetes does not provide built-in load balancer functionality—on most cloud providers, creating a LoadBalancer of Service automatically provisions a load balancer for the Service.

  25. Lionel Tchami on LinkedIn: Mastering Kubernetes Services: ClusterIP

    LoadBalancer exposes your service externally using a cloud provider's load balancer, automatically setting up an external IP address for your app. ️NodePort: This is your service's public face.

  26. Set static external IP for my load balancer on GKE

    In addition to what Dirk said, if you happen to reserve a global static IP address as oppose to a regional one; you need to use Ingres as describe here in documentation: Configuring Domain Names with Static IP Addresses specifically step 2b. So basically you reserve the static ip gcloud compute addresses create helloweb-ip --global

  27. NSX Advanced Load Balancer as L7 Ingress Controller

    NSX Advanced Load Balancer as L7 Ingress Controller To use NSX Advanced Load Balancer as ingress ... The NSX ALB SE routes the traffic to the pods by leveraging the static routes. ... the ANTREA_NODEPORTLOCAL configuration variable must be set to true in Tanzu Kubernetes Grid. For more information on the NodePortLocal feature in Antrea, see ...

  28. Simplifying Azure Kubernetes Service Authentication Part 2

    Welcome to the second installment of our multipart series on simplifying Azure Kubernetes Service (AKS) authentication. In this article, we delve deeper into the intricacies of AKS setup, focusing on critical aspects such as deploying demo applications, configuring Cert Manager for TLS certificates (enabling HTTPS), establishing a static IP address, creating a DNS label, and initiating the ...

  29. How to achieve Kubernetes observability: Principles and best ...

    Kubernetes can automatically expose a container to the internet or other containers using a DNS name or IP address. Autoscaling. When traffic spikes, Kubernetes can automatically spin up new clusters to handle the additional workload. Storage provisioning. Teams can set up Kubernetes to mount persistent local or cloud storage for containers.

  30. Configure HTTP Virtual Service on NSX Advanced Load Balancer in Oracle

    We will not enable DHCP as the web servers will have static IP. We also need to create additional overlay network to host management networks and web servers. Continue to follow Tutorial 2: Configure VMware NSX Advanced Load Balancer on Oracle Cloud VMware Solution from Task 5, the next imperative step involves seamlessly incorporating NSX-T as ...