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Connect kubectl to private Kubernetes cluster in EKS and AKS

Sat, 10 Jun 2023 19:31:00 -0400

Managed Kubernetes services give user a cluster endpoint and a number of worker nodes, with the choice. For each access, users have the choice of making them publicly available, or keeping them on private networking. In my opinion, any deployment beyond personal hobbies, should use Kubernetes private cluster, with both cluster endpoint and worker nodes on private subnet. There is no reason to expose computing nodes or Kubernetes management traffic publicly.

For worker nodes, it is fairly easy to put VMs on private network, but many companies still have the cluster endpoint exposed publicly. There are usually two reasons. First, their CI/CD agent is hosted somewhere else on the Internet (instead of on private network with private connectivity to Kubernetes cluster) and need to access Kubernetes cluster endpoint. Second, when the cluster needs to connect with third-party identity provider as OIDC provider, a two-way communication is needed.

There is a classic pattern of using a public bastion host (jump box), with a bastion host on the public subnet, routable to the private endpoint of managed Kubernetes service. Clients then connect to the bastion host via port 22 on a public IP address. The authentication is based on SSH key pair, or worse, password. The port forwarding (aka SSH tunnelling) capability enables all the magics.

Exposing a jump box in the public subnet with RSA key authentication is still not favourable. In this post, I’ll examine some secure patterns to connect to private endpoint with improved security posture.

AWS options

There are two problems. First, how to establish connectivity to the Bastion host in a private subnet. Second, how to use the Bastion host to proxy traffic to the cluster endpoint also in private subnet. To the first problem, there are two potential solutions: SSM Session Manager, and EC2 Instance Connect (EIC) with EIC endpoint (EICE).

SSM Session Manager was introduce in 2018. It runs an agent on the EC2, which initiates a connection to the SSM endpoint on the AWS side. This connection enables not only Session Manager, but also other Systems Managers (SSM) services such as Fleet Manager, Patch Manager and State Manager. The problem that session manager originally addresses is server management.

AWS launched EC2 Instance Connect (EIC) in 2019, and EIC Endpoint (EICE) in 2023. EIC addresses the problem with managing SSH key pairs at scale. It dynamically generates an SSH key pair for server access, based on IAM permission. However, it still requires an instance to have its SSH port publicly accessible. With EICE, it is no longer a requirement. In the diagram, EICE is placed in a private subnet, allowing EICE service to reach private instances at their SSH port.

Here is a comparison of the two:

	EC2 Instance Connect (EIC) with EIC Endpoint	SSM Session Manager
Location of Bastion host	Private Subnet.	Private Subnet
Need Ingress Port	Yes. Port 22 must open to the endpoint.	No. SSM agent initiate outbound connection from the instance
Traffic Path	AWS CLI → AWS EIC ES → EICE→EC2 Inst	AWS CLI → AWS SSM ES → SSM ← EC2 Inst
Authentication	AWS IAM and ephemeral SSH key when using AWS CLI directly AWS IAM and long-term SSH key when using SSH proxy command	AWS IAM and long-term SSH key when using AWS CLI directly or SSH proxy command
Work with OpenSSH	Yes	Yes
Cost	There is no additional cost for using EIC.	No additional cost, unless private SSM Endpoint.

Let’s take a look at each option.

EC2 Instance Connect

To use EIC, pick an AMI that has it pre-installed and ensure instance profile has correct policy, as the document states here. AWC CLI will make use of local OpenSSL client. So make sure there connection at port 22 is open. To make it work with EC2 instance on a private subnet, create an EC2 Instance Connect Endpoint on the VPC, and ensure that the security group of EC2 allows port 22 from the Endpoint. Run this command:

$ aws ec2-instance-connect ssh --instance-id i-00ea30a6e02db33fe

The command above simply generates a key pair internally, add the public key to the server side, and connect with SSH from the client side. The command takes you to an SSH session. Checking ps -ef | grep ssh on the client machine, you can see the full parameter of SSH, including the location of the ephemeral private key.

However, if you use AWS CLI open-tunnel as proxy command to ssh, then you’d still have to use the key pair used to create the EC2 instance. As suggested at the bottom of this blog post, the command is:

$ ssh ec2-user@[INSTANCE] -i [SSH-KEY] -o ProxyCommand='aws ec2-instance-connect open-tunnel --instance-id %h'

This is a bummer, because with native SSH tool you do not get the primary benefit of EIC – ephemeral key pair.

SSM Session Manager

Now let’s look at SSM session manager. Similarly, it needs an agent installed and IAM role configured. You can connect to from web console but more importantly, from AWS CLI:

$ aws ssm start-session --target i-0531b19bec8ad022d

This command takes you to an SSH session with user ssm-user, without starting an OpenSSH client process locally. User do not have to manage key pair. There is also a document about using this command as proxy command, which uses an SSM document. I have one of the SSH config entry as:

host i-* mi-*
 ProxyCommand sh -c "aws ssm start-session --target %h --document-name AWS-StartSSHSession --parameters 'portNumber=%p'"
 User ec2-user
 IdentityFile ~/.ssh/id_rsa

This allows me to directly SSH to client using OpenSSL client (e.g. ssh i-0531b19bec8ad022d) by Instance ID. With this, I also need to specify my own OS user and matching private key.

I know I will use the OpenSSH client a lot from pipelines because it is very powerful. In both options, I have to live with managing key pairs myself. With SSM session manager’s proxy command, the instance does not need port 22 to open, which is a great advantage, in terms of security and operation. SSM Session Manager is a winner.

SOCKS5 proxy for kubectl

Either SSM Session Manager or EIC with EICE enables an SSH tunnel with key encryption between client (a local computer or a pipeline agent). On top of the SSH tunnel, we can build a SOCKS5 proxy. Kubernetes document has a good page on how to do this. I managed to get this to work with a few gotchas.

To put this in practice, I first created a VPC stack with a bastion host using terraform template from my vpc-base project. The terraform output will give the next set of commands to run to create a private cluster, using a manifest rendered from the file private-cluster.yaml.tmpl:

# cd aws_vpc
# terraform init
# terraform plan
# terraform apply
# ... run the given command ...
# envsubst < private-cluster.yaml.tmpl | tee | eksctl create cluster -f -

# Run this from a remote host without access to cluster endpoint.
# Run terraform apply and terraform output contains the variables needed for the next steps

# the command below may take 15 minutes to create a private cluster

eksctl create cluster -f private-cluster.yaml 

aws eks update-kubeconfig --name private-cluster

At this point, the kubeconfig file has been updated, but kubectl (from Internet or on-prem) is unable to connect to cluster endpoint (on private network). In order to

BASTION_SECURITY_GROUP_ID=$(terraform output -raw bastion_sg_id)
CLUSTER_SECURITY_GROUP_ID=$(aws eks describe-cluster --name private-cluster --query "cluster.resourcesVpcConfig.clusterSecurityGroupId" --output text)

# In Cluster Endpoint's security group, open up port 443 to Bastion host
aws ec2 authorize-security-group-ingress --group-id $CLUSTER_SECURITY_GROUP_ID --source-group $BASTION_SECURITY_GROUP_ID --protocol tcp --port 443

# Test with connecting to Bastion host with ssh i-0750643179667a5b6, assuming .ssh/config file is configured as above. From the bastion host, you can test:
# curl -k https://EC5405EE1846F19F9F61ED28FB12A6A9.sk1.us-west-2.eks.amazonaws.com/api 
# if you get an HTTP response, even an error code 403, the bastion host has TCP connectivity to cluster endpoint

# then we can start an SSH session as a SOCKS5 proxy on the remote host
ssh -D 1080 -q -N i-0750643179667a5b6

# add > /dev/null 2>&1 & to push it to background, or use ctrl+z after running the command
# to validate that the SOCKS5 proxy is working, you can run the same curl command with a proxy parameter:
# curl -k https://EC5405EE1846F19F9F61ED28FB12A6A9.sk1.us-west-2.eks.amazonaws.com/api --proxy socks5://localhost:1080

# you can instruct kubectl to use the SOCKS5 proxy with the following environment variable
export HTTPS_PROXY=socks5://localhost:1080

kubectl get node

# alternatively, add "proxy-url: socks5://localhost:1080" below server attribute in ~/.kube/config file.

There are some pitfalls to watch for. On the remote host both ssh command and kubectl command implicitly uses AWS CLI. Therefore, make sure the profile and IAM role are correctly configured. For example, if SSM agent requires one IAM role, and kubectl is created with another IAM role, then make sure AWS CLI assumes the correct IAM role using environment variables, and use “aws sts get-caller-identity” to validate the IAM identity being used.

What about AKS in Azure

I touched on this in my Azure notes in 2021 and did a research again. Unfortunately, options are still fairly limited.

The first option is to use a managed service called “Azure Bastion”, which requires public IP and a dedicated subnet with the exact name of AzureBastionSubnet, as well as some additional requirement. I’m not impressed with these requirement because it is meant to be a managed service. The other option, is essentially to DIY a JumpBox. The idea is the same: put the jumpbox in a public subnet, which is routable to private subnets. When you need to connect to private VMs, get to the jumpbox first.

Apart from having to put the bastion VM on a public subnet, the pattern that we discussed above involving SOCKS5 proxy still works. Exposing a bastion host isn’t ideal but it still reduces attack surface significantly, comparing to exposing the cluster endpoints of all Kubernetes API servers.

Summary

Many immature Kubernetes configurations exposes private endpoint publicly. Having cluster endpoint in private subnet greatly improves security posture. In my opinion, there are very few situations where cluster endpoint must exposed publicly. Having private endpoint should be mandatory for all Kubernetes cluster. In the next post, I also cover how to create a ROSA cluster with private endpoint.

Service and Ingress -Traffic Management in Kubernetes

Sun, 04 Jul 2021 01:30:00 -0400

Update 2022-08 – Read my latest article on ingress traffic management.

In this post we discuss the traffic management in Kubernetes, specifically on Service and Ingress objects. Let’s start with a traditional architecture:

In this traditional architecture, we run application as processes on the operating system on each virtual machine. The application process is bound to a certain ports on the operating system, and is wrapped into services (e.g. systemd). On the same virtual machine, there is also a reverse proxy service (e.g. Nginx). There are several main functional areas as listed below, and how they are fulfilled in traditional architecture:

Requirement	Detail	Typically fulfilled by
L4 Load balancing	TCP/UDP traffic routing, operating at L3 and L4	Network Load Balancer
TLS termination	Terminate TLS traffic, operating at L4	TLS termination is available in many products such as Load Balancer (L4/L7), Nginx, or the application itself.
Path-based routing	Route request based on URI path, operating at L7	Nginx, modern L7 Load Balancer.
Authentication	Integrate with external identity store, operating at L7	Nginx, modern L7 Load Balancer.

These requirements are the problems that Kubernetes needs to solve in its own architecture. They are solved by different abstraction objects in Kubernetes. Before getting to traffic management, we first need to expose an application.

Service

During traditional application deployment, we often need to organize a group of homogenous application instances as a single target for batch operation. The Pod object is an abstraction of a single application instance. The Deployment object is an abstraction of a group of homogenous Pods. The purpose of Deployment object is for Pod orchestration only. It is not designed to expose the application. To define how we want to expose an application, we use Service object.

The service object does not carry exactly the same functionalities as an operating system service. It connects to the frontend (client), as well as to the backend (server). There are two ways to connect to a backend:

To connect to Pods as backend, use selector and label; the target port is Pod’s port. This is the most common use case.
To connect to a custom backend (e.g. external database, services in different namespaces, during workload migration), define an Endpoints object (including address and port), and target the port;

On the frontend, there are several ways to expose service to client, as defined in ServiceType property. Each represents a level of exposure:

ClusterIP (default): the service gets an internal IP address in the cluster. This is the lowest level of exposure. The service is only reachable from within the cluster. This is a good choice when the service is for internal assumption, such as database.
NodePort: the service is exposed at a static port on each node. The port must be in a range pre-specified during cluster provisioning (default 30000-32767). Each node proxies traffic to that port to the service. Without a load balancer, each node is a point of entry on its own.
LoadBalancer: this option works with external load balancer in cloud deployments. The actual creation of the load balancer happens asynchronously, and information about the provisioned balancer is published in the Service’s .status.loadBalancer field. Some cloud providers allow you to specify the loadBalancerIP. The benefit Load Balancer over NodePort, is it provides a single point of entry (for each service).
ExternalName: rare use case with custom endpoint object.

Headless service

With service type ClusterIP, if you explicitly specify "None" for the cluster IP (.spec.clusterIP), the service is considered a headless service. With a headless service, a cluster IP is not allocated, kube-proxy does not handle these services, and there is no load balancing or proxying done by the platform for them. Each connection to the service is forwarded to one randomly selected backing pod. Hence the document points out that you can use a headless Service to interface with other service discovery mechanisms, without being tied to Kubernetes implementation. The behaviour differs slightly based on whether selectors are present, but both resembles DNS routing with multiple A record.

Virtual IP

Kubernetes manages service traffic with virtual IP. When clients connect to virtual IP (VIP), the traffic is automatically transported to an appropriate endpoint. Virtual IP is implemented with kube-proxy. Kube-proxy can work in three modes: userspace, iptables and IPVS. I discussed these terms in this post last year. The takeaway is that IPVS is the recommended mode.

Ingress

Ingress in Kubernetes cannot match up with a counterpart in traditional architecture. It is mainly for path-based request routing. Also, do not confuse Ingress object with Ingress rule as a policy type in Network Policy object. Ingress is a high level abstraction and should be considered over Service object when the followings are involved in the routing.

Content-based or path-based L7 routing
Multiple protocols (e.g. gRPC, WebSockets)
Authentication

Ingress usually work with service object (ClusterIP), as illustrated in Kubernetes documentation:

Also note that if you have a service other than HTTP or HTTPS, that you need to expose to the Internet, it is recommended to use a service object of NodePort or LoadBalancer type.

We call Ingress a high-level abstraction. Ingress object (aka ingress resource) itself does not expose application. It simply defines a set of routing rules. The implementation is provided by another object (Ingress Controller), who enforces the routing rules by monitoring and manage traffic using its own Service and Pods. You must have an Ingress controller to satisfy an Ingress. Only creating an Ingress resource has no effect. There are a number of Ingress Controllers to choose from.

Ingress Resource

In an Ingress resource, annotations are used to configure some options, depending on the corresponding Ingress Controller. What annotation can be used depends on the the specific Ingress Controller. The backend can be either a service, or a resource. A common usage for a Resource backend is to ingress data to an object storage backend with static assets. You can define DefaultBackend for an Ingress.

Each Ingress should specify a class, a reference to an IngressClass resource that contains additional configuration including the name of the controller that should implement the class. Before the IngressClass resource and ingressClassname field were added in Kubernetes 1.8, Ingress classes were specified with a kubernetes.io/ingress.class annotation on the Ingress. This annotation was never formally defined, but was widely supported by Ingress controllers. For example, here is the annotations supported by Nginx Controllers.

Below is the yaml output of the ingress from Kubernetes documentation:

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
 name: minimal-ingress
 annotations:
 nginx.ingress.kubernetes.io/rewrite-target: /
spec:
 rules:
 - http:
 paths:
 - path: /testpath
 pathType: Prefix
 backend:
 service:
 name: test
 port:
 number: 80

Ingress Controller

Ingress Controller exists in the form of Pods, usually as daemonSet, sometimes as a deployment. The Pods listens for requests to create or modify Ingress within the cluster, and converts the rules in the manifest into configuration directives for a load balancing components. Below is all the components related to Ingress Controller:

> kubectl -n ingress-nginx get all
NAME READY STATUS RESTARTS AGE
pod/ingress-nginx-admission-create-s7486 0/1 Completed 0 11d
pod/ingress-nginx-admission-patch-sjt2q 0/1 Completed 2 11d
pod/ingress-nginx-controller-5b74bc9868-6vmjc 1/1 Running 18 11d

NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/ingress-nginx-controller LoadBalancer 10.106.25.194 localhost 80:31774/TCP,443:31576/TCP 11d
service/ingress-nginx-controller-admission ClusterIP 10.102.38.191 <none> 443/TCP 11d

NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/ingress-nginx-controller 1/1 1 1 11d

NAME DESIRED CURRENT READY AGE
replicaset.apps/ingress-nginx-controller-5b74bc9868 1 1 1 11d

NAME COMPLETIONS DURATION AGE
job.batch/ingress-nginx-admission-create 1/1 9s 11d
job.batch/ingress-nginx-admission-patch 1/1 25s 11d

Ingress Controller can be implemented by load balancer resource from cloud platform, or Nginx. When you have one ingress resource and one controller, the matching is assumed. When you have multiple controllers, you need to use the mechanism from the ingress controller to ensure correct matching.

Nginx is a popular controller and there are a couple of implementations as illustrated here. Let’s take a look at Nginx Controller as an example. The troubleshooting guide states that, For each Ingress/VirtualServer resource, the Ingress Controller generates a corresponding NGINX configuration file in the /etc/nginx/conf.d folder. Additionally, the Ingress Controller generates the main configuration file /etc/nginx/nginx.conf, which includes all the configurations files from /etc/nginx/conf.d. In the Rancher ingress example above, we can check the nginx configuration with the commands below:

kubectl exec ingress-nginx-controller-5b74bc9868-6vmjc -n ingress-nginx -- cat /etc/nginx/nginx.conf | less

It is important to understand the difference between a load-balancer type service and an ingress. The documentation for ingress states that: An Ingress does not expose arbitrary ports or protocols. Exposing services other than HTTP and HTTPS to the internet typically uses a service of type Service.Type=NodePort or Service.Type=LoadBalancer. This is because ingress operates at layer 7, so routes connections based on http host header or url path. Load balanced services operate at layer 4 so can load balance arbitrary tcp/udp/sctp services. Ingress should be backed by L7 load balancer, whereas load-balancer service should be backed by L4 load balancer.

Nginx Ingress Controller

There are several flavours of Nginx ingress controllers that cause much confusion. It is clarified on a blog post on Nginx website. To recap:

Community version: Found in the kubernetes/ingress-nginx repo, the community Ingress controller is based on Nginx Open Source, with docs on Kuberentes.io. It is maintained by the Kubernetes community with assistance from the F5 Nginx team.
Nginx version: Found in the nginxinc/kubernetes-ingress repo, the NGINX Ingress Controller is developed and maintained directly by F5 NGINX team, with docs on docs.nginx.com. It is available in two editions:
- NGINX Open Source-based
- NGINX Plus-based

There are also a number of other Ingress controller based on NGINX, such as Kong, but their names are easily distinguished. If you’re not sure which version you’re using, check the container image, then compare the image name with the repos listed above.

Load Balancer

Kubernetes by itself does not have an object for Load Balancer. The function of traditional Load Balancer is implemented through Service and Ingress objects in Kubernetes, both of which can be satisfied by a load balancer object from the cloud platform (service-managed load balancer and ingress-managed load balancer). Alternatively, you may stand up a standalone load balancer independent of the Kubernetes cluster, which is not recommended.

If your architecture is complex and you have a lot of services (e.g. using microservice), then the overhead of managing everything with Service and Ingress in Kubernetes can be significant. In that case, consider delegating these tasks to a service mesh.

Troubleshooting

There isn’t a single recipe for troubleshooting service and ingress on Kubernetes. There are some good general guide lines here and here, in addition to the guides (here and here) from official documentation. To run networking command from within the Pod network, you can launch a Pod using nicolaka netshoot image.

Bottom line

We compared service and ingress in Kubernetes. In real life, we use both, and oftentimes along with CRDs of service mesh.

Basic Resource Object in Kubernetes 1 of 2

Sat, 16 Jan 2021 22:13:00 -0400

For someone from a system administration background, it would be amazing to discover that Kubernetes provides a solution to every pain point in the traditional software deployment landscape. On the contrary, it also brings about a lot of complexity due to the types of resource objects introduced.

Pod

A Pod is a shared execution environment for one or more containers. The containers running in a Pod share resources such as memory, volumes, network namespace (e.g. IP address, port range, hostname, routing table), UTS namespace (e.g. hostname) and IPC namespace (Unix domain sockets). Every Pod has its own IP address that is routable on the Pod network. All Pods connect to the same flat network called the Pod network.

A pod most commonly only contains a single container, which is considered a good practice, unless there is good reasons to put two containers in a single pod (sharing resource). One such good reason is to co-schedule tightly-coupled workloads (such as logging, sharing volume, etc). Within the Pod, the containers communicate with each other via localhost interface of the Pod. In service mesh model, there is also a proxy container in each application Pod. The proxy container handles all network traffic entering and leaving the Pod. Also, within the Pod, to avoid competing for resources, individual containers can have their own cgroup limits, which actively police resource usage.

Pods are mortal (composable). They come and go (with dynamic IPs), so application should not store state in Pods. Deploying a Pod is an atomic (all or nothing) operation. When a Pod is scheduled to a node, it enters the pending state while the container runtime on the node downloads images and starts any containers. Once’s everything is ready, the Pod enters the running state.

We typically deploy Pods via higher-level controllers such as Deployments (to offer scalability and rolling updates), DaemonSets (to run one instance of a service on every node in the cluster), StatefulSets (for stateful application components), and CronJobs (for short-lived tasks that need to run at set times just like a Linux cronjob).

Deployments

Deployment manages multiple replicas of the same Pod (via ReplicaSets). To follow best practice, you interact with Deployments instead of ReplicaSets, and use YAML file (declarative model). You can perform rolling update or rollback.

ReplicaSets

ReplicaSets provide self-healing and scaling capabilities to Pods. If a Pod fails, it will be replaced. If load increases, then the ReplicaSets creates new Pod. This is all implemented with a background reconciliation loop that is constantly checking whether the right number of Pod replicas are present on the cluster. If not, Kubernetes declares a red-alert condition, orders the control plan to bring up more replicas. The best practice however, is that you should not manage ReplicaSets directly. Instead, you should perform all actions against the Deployment object and leave the Deployment to manage ReplicaSets.

Service

Pods themselves are mortal (IP churn) so it’s a bad idea to talk directly to individual Pods. Service object provides stable and reliable networking for a set of dynamic Pods. Service gets its own stable IP address, stable port and stable DNS name. It can also load-balance request across the Pods.

Services are loosely coupled with Pods via labels and label selectors. You specify label selector for Service and labels on Pods when creating them. All the labels in label selector are used to select target Pods. Service acts as front-end, consisting of stable IP, DNS name and port, with Pods acting as backend, consisting of constantly changing Pods. Labels are simple yet extremely powerful. During blue-green update, you may use version label as a technique to control what backend pool is used behind Service object. For example, start with version=1, deploy version 2, remove version from label selector, and eventually add version=2 back to label selector, before phasing out the old Deployment.

Services learn Pod status via Endpoint object, more details to follow.

There are several types of Service, the default being ClusterIP. A ClusterIP Service has a stable IP address and port that is only accessible from inside the cluster. The ClusterIP gets registered against the name of the Service on the cluster’s internal DNS service (implemented via coreDNS with Control plane Pods). This means that the ClusterIP only works within the cluster, not outside. The other type of Service is called a NodePort, which is built on top of ClusterIP, but also enables access from outside of the cluster. The Service object has a reliable NodePort mapped to every node in the cluster. The NodePort value is the same on every cluster. Traffic from outside of the cluster can hit any node in the cluster on the NodePort and get through the the Pods.

Other types of Services include LoadBalancer and ExternalName. LoadBalancer Services integrate with load-balancers from cloud provider. They build on top of NodePort Services and allow clients on the internet to reach your Pods via the load balancer of cloud vendor. ExternalName Services route traffic to systems outside of your K8s cluster.

For service discovery within the cluster, Kubelet program every container with the knowledge of the internal DNS (/etc/resolv.conf). The internal DNS service watches constantly the API server for new Services and automatically register them in the DNS. The other means of service discovery is through environment variables. However, in this method the Pods have no way of learning about new Services added to the cluster after the Pod itself is created.

Endpoints

Endpoints object is a dynamic list of all the healthy Pods on the cluster that match the Service’s label selector. Each Service gets its own Endpoints objects for an up-to-date list of matching Pods. Kubernetes is constantly evaluating the Service’s label selector against the currently list of healthy Pods on the cluster. Any new Pods that match the selector get added to the Endpoints object, and any Pods that disappear get removed.

When sending traffic to Pods, via a Service, an application will query the cluster’s internal DNS for the IP address of a Service, then sends the traffic to this stable IP address. Service then forwards it on to a Pod. Kubernetes-native application however, has the ability to query the Endpoints API directly, bypassing the DNS lookup and use of the Service’s IP.

It requires a thorough understanding of Services, Endpoints and the service discovery mechanism to perform effective troubleshooting in Kubernetes.

The aforementioned internal DNS service (we usually call it the “cluster DNS”) is implemented in the kube-system Namespace as a set of Pods managed by a Deployment called coredns. These Pods are fronted by a Service called kube-dns. The cluster DNS is constantly looking for new Services and automatically register their details (metadata.name). We might need to check the logs for each of the coredns Pods during troubleshooting.

The kubelet process on every node is watching the API Server for new Endpoints objects, when it sees them, it creates local networking rules that redirect ClusterIP traffic to Pod IPs, using IPVS technology on Linux to manage these rules.

DaemonSet

A DaemonSet ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the cluster, Pods are added to them. As nodes are removed from the cluster, those Pods are garbage collected. Deleting a DaemonSet will clean up the Pods it created.

Some typical uses of a DaemonSet are: cluster storage daemon on every node, logs collection daemon on every node, a node monitoring daemon on every node.

Horizontal Pod Autoscaler

The Horizontal Pod Autoscaler automatically scales the number of Pods in a replication controller, deployment, replica set or stateful set based on observed CPU utilization (or, with custom metrics support, on some other application-provided metrics). Note that Horizontal Pod Autoscaling does not apply to objects that can’t be scaled, for example, DaemonSets.

The Horizontal Pod Autoscaler is implemented as a Kubernetes API resource and a controller. The resource determines the behaviour of the controller. The controller periodically adjusts the number of replicas in a replication controller or deployment to match the observed average CPU utilization to the target specified by user.

There are more details about HPA here and here.

StatefulSets are designed for stateful application, which creates and saves valuable data. The three properties that form the state of a Pod are:

Pod names (<StatefulSetName>-<Integer>)
DNS hostnames
volume bindings

They are sometimes referred to as the Pods sticky ID. StatefulSets ensures that these are all predictable and persistent. For example, failed Pods managed by a StatefulSet will be replaced by new Pods with the exact same Pod name, the exact same DNS hostname, and the exact same volumes, even if the replacement Pod is started on a different cluster Node.

Note that StatefulSets create one Pod at a time, and always wait for previous Pods to be running and ready before creating the next. Scaling operations are also governed by the same ordered startup rules. This is different from Deployments that use a ReplicaSet controller to start all Pods at the same time, causing potential race conditions. The way StatefulSet controllers do their own self-healing and scaling is architecturally different to Deployments which use a separate ReplicaSet controller for these operations. The reason it is a game changer to know the order in which Pods will be scaled down, as well as that Pods will not be terminated in parallel, is because clustered apps that store data are usually at high risk of losing data if multiple replicas go down at the same time.

Deleting a StatefulSet does not terminate Pods in order. So you may want to scale a StatefulSet to 0 replicas before deleting it. You might also set 10 seconds grace period before terminating to allow applications a chance to flush local buffers and safely commit any writes still in flight.

In Kubernetes, Volumes are decoupled from Pods via PersistentVolumes and PersistentVolumeClaims. So volumes have separate lifecycles to Pods and can survive Pod failures and termination operations. When a StatefulSet Pod is created, any volumes it needs are created at the same time and named in a way to connect them to the right Pod. Any time a StatefulSet Pod fails or is terminated, the associated volumes are unaffected. This allows replacement Pods to attach to the same storage as the Pods they’re replacing, even if the replacement Pod is scheduled to a different cluster Node. Similarly, if a StatefulSet Pod is detected as part of a scale-down operation, subsequent scale-up operations will attach new Pods to the existing volumes that match their names.

Since each StatefulSet Pod needs its own unique storage, hence its own PVC, this can be done by volumeClaimTemplate, which dynamically creates a PVC each time a new Pod replica is dynamically created. This eliminates the hassle to have to pre-create a unique PVC for every potential StatefulSet Pod.

Namespaces

Namespaces allows you to partition resource objects. For example, you may create a Namespace called prod and dev. Object names must be unique within Namespaces but not across Namespaces.

Docker network in different modes

Wed, 01 Jul 2020 20:19:00 -0400

Reading notes of “Docker DeepDive”.

Docker networking is backed by libnetwork, which is an implementation of Container Network Model (CNM), an open-source pluggable architecture designed to provide networking to containers. Libnetwork also provides native service discovery and basic container load balancing solution. Docker networking also involves some drivers that extend the CNM model with specific network topology implementation.

Sandbox – an isolated network stack, including Ethernet interfaces, ports, routing tables, and DNS config, usually implemented through Linux namespace.
Endpoints – behave like regular network adapters, and can only be connected to a single network at a time. It connects sandbox to network. Endpoint is implemented in veth pair in Linux.
Networks – software implementation of an 802.1 bridge (aka switch). They group together, and isolate, a collection of endpoints that need to communicate.

Docker company separates network project out from its container project, as a plugin called libnetwork, which is developed in Golang and compliant to CNM. Libnetwork is the official implementation of CNM.

Libnetwork supports the following network modes:

network mode	mechanism	use case
null	no network is provided to containers	quarantined environment for security
bridge	containers communicate with each other through bridge	containers needs to communicate with each other or with host service
host	process in container has access to host network stack and use host port	container needs to use host network stack (e.g. licence by mac address)
container	place containers in a single net namespace so they can communicate with each other as localhost	proxy, kubernetes

Linux veth comes in pairs to connect virtual network devices. For example, connect two net namespaces to allow intercommunication. Linux bridge is a virtual device, to connect two net namespaces.

Dockers ships with several built-in drivers, known as native drivers or local drivers, such as bridge, overlay and macvlan on Linux. There are also 3rd-party network drivers for docker (aka remote drivers).

Host network

In this mode libnetwork will not create network and net namespace for container. Container process shares the network configuration of the host, and therefore uses the ports on host. Other than network sharing, other aspects (e.g. process, file system, hostname, etc) are separated from host.

Bridge networks

This type of network only exist on a single Docker host and can only connect containers that are on the same host. The word bridge refers to 802.1d bridge (layer 2 switch), which is used to connect multiple network interfaces.

Every Docker host gets a default single-host network, called bridge on Linux. This is the network that all new containers will attach to by default.
Docker networks built with the bridge driver on Linux hosts are based on the linux bridge technology that has existed in the Linux kernel for a while. They’re high performance and extremely stable. Linux brctl tool can inspect the linux bridge.

Bridge networks allows container on the same host to communicate with each other. Port mapping allows network connectivity between container and host. Traffic hitting host port will be redirected to container port.

Multi-host overlays

Cross-host networking usually uses an overlay network, which builds a mesh between host and employs a large block of IP addresses within that mesh. A mesh network is a local network topology in which the infrastructure nodes connect directly, dynamically and non-hierarchically to as many other nodes as possible and cooperate with one another to efficiently route data from/to clients.

You can attach a service to overlay network, which spans across multiple Docker hosts so that containers on different hosts can communicate at layer 2. They are much better alternatives than bridge network for container-to-container communication. Overlay networking is very common due to its scalability.

The trick is basically the layer 2 frame of the overlay network is encapsulated into layer 3 datagram transmitted across underlay network, at layer 3. This is achieved through VXLAN tunnels, which allows you to create a virtual Layer 2 network on top of an existing Layer 3 infrastructure. VXLAN is an encapsulation technology that existing routers and network infrastructure just see as regular IP/UDP packets without issue.

To create the virtual Layer 2 overlay network, a VXLAN tunnel is created through the underlying Layer 3 IP infrastructure (aka underlay network). Each end of the VXLAN tunnel is terminated by a VXLAN Tunnel Endpoint (VTEP). It’s this VTEP that performs the encapsulation/de-encapsulation.

VXLAN networking

To accomplish overlay network across multiple hosts, a new network sandbox was created on each host. A sandbox is like a container, but instead of running an application, it runs an isolated network stack – one that’s sandboxed from the network stack of the host itself.

A virtual switch (aka virtual bridge) called Br0 is created inside the sandbox. A VTEP is also created with one end plumbed into the Br0 virtual switch, and the other end plumbed into the host network stack (VTEP). The end in the host network gets an IP address on the underlay network the host is connected to and is bound to a UDP socket on port 4789. The two VTEPs on each host create the overlay via a VXLAN tunnel.

Each container then gets its own virtual Ethernet (veth) adapter that is also plumbed into the local Br0 virtual switch.

Let’s go over an example in the following diagram, where container C1 with an overlay IP needs to communicate to another container C2, with a different overlay IP, sitting on a different node (Docker host). Each node has its own underlay IP.

IP communication details:

C1 creates the IP datagram with destination IP (C2) and sends it over its veth interface, which is connected to the Br0 virtual switch on the host node.
The virtual switch doesn’t know where to send the datagram, as it doesn’t have an entry in its ARP table that corresponds to the destination IP address. As a result, it floods the packet to all ports. The VTEP interface connected to Br0 knows how to forward the frame, so responds with its own MAC address.
This is a proxy APR reply and results in the Br0 switch learning how to forward the packet. So it updates its ARP mapping the destination IP address to the MAC address of the local VTEP.
The VTEP knows about C2 because all newly started containers have their network details propagated to the other nodes in the Swarm using the network’s built-in gossip protocol. When the packet arrives at node2
The VTEP encapsulates the frame so it can be sent over the underlay transport infrastructure, by adding a VXLAN header to the Ethernet frame. The VXLAN header contains the VXLAN network ID (VNID) which is used to map frames from VLANs to VXLANs and vice versa.
Each VLAN gets mapped to VNID, so that the packet can be de-encapsulated on the receiving end and forwarded to the correct VLAN. This is how network isolation is maintained. The encapsulation also wraps the frame in a UDP packet with the IP address of the remote VTEP on node2 in the destination IP field, and the UDP port 4789 socket information. The underlying network does not know that it is transporting data frames for the overlay network.
When the packet arrives at node2, the kernel sees that it’s addressed to UDP port 4789. The kernel also knows that it has a VTEP interface bound to this socket. As a result, it sends the packet to the VTEP, which reads the VNID, de-encapsulates the packet, and sends it on to its own local Br0 switch on the VLAN that corresponds the VNID. From there it is delivered to container C2

Docker also supports Layer 3 routing within the same overlay network. For example, you can create an overlay network with two subnets, and Docker will take care of routing between them. Two subnets will require two virtual switches, Br0 and Br1, being created inside the sandbox, and routing happens by default.

Plugging into existing vLANs

The built-in MACVLAN driver was created for onnect containerized apps to external physical network. A good example is partially containerized app, in which the containerized parts will need a way to communicate with the non-containerized parts still running on existing physical networks.

To connect the container interface through the host interface to an external network, the host NIC needs to be in promiscuous mode. For public cloud, this is most likely prohibited. For data centers, this depends on the network policy.

Docker MACVLAN driver is built on top of Linux kernel driver with the same name. As such, it supports VLAN trunking. This means we can create multiple MACVLAN networks and connect containers on the same Docker host to them.

For connectivity issues between containers, it’s worth checking both the daemon logs (on host) and container logs.

Service discovery

allows all containers and Swarm services to locate each other by name, as long as they are on the same network. This leverages Docker’s embedded DNS server as well as a DNS resolver in each container.
Each Swarm Service and standalone container started with the –name flag will register its name and IP address with the Docker DNS service.
This name resolution, however, only works within the same network.
It is also possible to configure Swarm services and standalone containers with customized DNS options in case embedded Docker DNS server cannot resolve a query (/etc/resolv.conf)

Ingress load balancing

Services published via ingress mode (by default, as opposed to host mode) can be accessed from any node in the Swarm, even nodes not running a service replica. Ingress mode uses a layer 4 routing mesh called the Service Mesh or the Swarm Mode Service Mesh.

Updates:

The most common network modes that I use are host and bridge. With host network mode, container exposes ports on the interface of the host machine. Containers talk to each other via that interface. With bridge network, containers have their own namespace of networking separate from the one from the interface of the hosts, with a bridge getting the two networks connected.

Reference

Docker Deep dive