Kubernetes: Twelve Key Features

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Kubernetes: Twelve Key Features

Kubernetes is an abstraction that optimizes the utilization of resources and allows for efficient distributions of applications across a cluster of nodes.

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“Action without orchestration is burn out; orchestration w/o action is management.” 
― Orrin Woodward

Kubernetes “Aye Aye, K-aptain!”

Kubernetes is a Greek word which means “helmsman,”or the pilot of a ship.

It is an open source project that was started by Google and derived from Borg which is used inside Google — for several years now — for container management. Currently, it is hosted by Cloud Native Computing Foundation(CNCF).

Kubernetes (abbreviated as K8S) is an abstraction that optimizes the utilization of resources like CPU and memory through containers, which allow for efficient distributions of applications across a cluster of nodes. K8S can run anywhere on bare metal or in any cloud provider infrastructure. This novel tool is cloud agnostic and focuses on deploying and scheduling containers inside the infrastructure instead of directly utilizing nodes/hosts.

Some of the platform features which K8S offers are:
· Container grouping using pod
· Self-healing
· Auto-scalablility 
· DNS management
· Load balancing
· Rolling update or rollback
· Resource monitoring and logging

Kubernetes Architecture

A Kubernetes cluster is made of a master node and a set of worker/slave nodes.

The Kubernetes master components are:

· API Server: Users use this to interact with the manifest yaml, via Rest operations or kubectl cli. It is employed for every operation related to API Objects, like pod creation, and it is the only component which stores the desired state in etcd.

· Scheduler: Users use this to issue a command to create pod as per manifest yaml to the API Server using kubectl cli. After this action is performed, it is the scheduler’s responsibility to allocate pods to available nodes based on the resource requirement.

· Controller Manager: The Controller Manager performs operations on the resources based on the cluster state and makes changes to bring the current state application to the desired state as per the manifest yaml. In other words, the Controller Manager reconciles the actual state with the desired state. There are multiple specialized controllers inside a Controller Manager in order to simply cluster management. For example, the Node Controller checks to see if any currently running nodes are down and takes the corrective measures, whereas the Replication Controller ensures that the desired number of pods are actually running in the nodes.

· etcd: All configuration information about cluster states is stored in the etcd in the form of key/value pairs, and this component is implemented by CoreOS. These states show the nodes that are included in the cluster and the pods that are needed to be running in it. 

· Addons: In order for a server DNS record to be added to Kubernetes, we need a Cluster DNS addon. Addons help in extending the functionality related to Kubernetes clusters or nodes. There are many other addons available like fluntd for logging, rbac for role based access and so on.

The components that are installed in a Kubernetes node are:

· Docker: A Docker Daemon is running in each node. If the container image is not present, then it will pull an image from docker registryand run it.

· Kubelet: A Kubelet node agent periodically checks the health of the containers in a pod. In addition, it ensures that the volume is mounted as per manifest, and it downloads the sensitive information required to run the container. It also links the node to the API server.

· Kube-proxy: Kube-proxy runs in each node for load distribution among the pods and makes services available to the external host. It uses iptable rules or round robin to forward requests to the correct containers.

For Highly Available and Fault Tolerant Kubernetes production and deployment, multiple master nodes and a separate etcd cluster is required. If three API servers are run, a network load balancer is required to properly distribute the load into the servers. The only remaining problem is needing three actors for the Controller Manager and Scheduler to maintain cluster states and allocating nodes. In order to do it more efficiently yet reliably, only one actor should perform the actual change, but other instances are still needed in case a machine is down. In order to fix this, we can use a lease-lock in API to perform a master election and the flag used for it is –leader-elect

Kubernetes achieves networking from Pod to Pod through either: 
 1) layer 2 (switching solution)
 2) layer 3 (bridging solution)
 3) overlay solutions (weave and flannel)

These allow pod-to-pod communication throughout the cluster and provide unique IP addresses for each Pod.

Kubernetes Key Features

Pod: Collection of Containers

A pod is a deployment unit in the K8S with a single IP address. Inside it, the Pause container handles networking by holding a network’s namespace, port and ip address, which in turn is used by all containers within the pod.

                                 Replication Controller

A replication controller ensures that the desired number of containers are up and running at any given time. Pod templates are used to define the container image identifiers, ports, and labels. Using liveness probes, it auto-heals pods and maintains the number of pods as per desired state. It can also be manually controlled by manipulating the replica count using kubectl.

Storage Management

Pods are ephemeral in nature — any information stored in a pod or container will be lost. In order to store data even after a pod is killed or rescheduled, a persistent system like Amazon Elastic Block Storage (EBS), Google Compute Engine’s Persistent Disks (GCE PD), or a distributed file system such as Network File System (NFS) or Gluster File System (GFS) is needed.

Resource Monitoring

Monitoring is one of the key aspects to run infrastructure successfully. It is the base of hierarchy of reliability. Heapster is an addon used to collect metrics from kubelet, which is integrated with a cAdvisor. cAdvisor is used to collect metrics related to CPU, memory, I/O, and network stats of the running containers. Data collected by Heapster is stored in an influx DB and is displayed in the UI using Grafana. There are also other sinks available like Kafka or Elastic Search, which can be use for storing data and displaying it in the UI.

Health Checking

Health checking in kubernetes is done by a kubelet agent. It is divided into two liveness and readiness probes.

There are mainly three types of handlers:

ExecAction: Shell command is executed, and if the resulting exit code is 0, it means that the instance is healthy. Under any other circumstances, the instance is not healthy. 

TCPAction: Kubelet will try to connect to a specified port, and if it establishes a connection to the given socket, the diagnostic is successful.

HTTPGetAction: Based on the HTTP endpoint that the application exposes, kubelet performs an HTTP GET request against the container IP address on a specified path, and if it returns with a 200 to 300 response code, the diagnostic is successful.

Each probe usually has three results:

Success: The Container has passed the diagnostic.
Failure: The Container has failed the diagnostic.
Unknown: The diagnostic has failed, so no action should be taken.

Horizontal Auto Scaling

Autoscaling utilizes computational resources based on the load. K8S scale pod automatically uses a HorizontalPodAutoscaler object, which gets metrics data from Heapster, and it decreases or increases the number of pods accordingly. For example, if auto-scaling is based on memory utilization, then the controller starts observing memory usage in the pod and scales the replica count based on it.

Service Discovery

Kubernetes pods are ephemeral, and the Replication Controller creates them dynamically on any node, so it is a challenge to discover services in the cluster. A service needs to discover an IP address and ports dynamically related to each other to communicate within a cluster.

There are two primary ways of finding it — Environment variables and DNS

DNS based service discovery is preferable, and it is available as a cluster add-on. It keeps track of new services in cluster and creates a set of DNS records for each.


To manage a cluster fully, a network has to be setup properly, and there are three distinct networking problems to solve:
1. Container-to-Container communications: pods solve this problem through localhost communications and by using the Pause container network namespace
2. Pod-to-Pod communications: this problem is solved by the software defined networking as shown in the Architecture diagram above
 3. External-to-Pod communications: this is covered by services.

Kubernetes provides a wide range of networking options. Furthermore, there is now support for the Container Networking Interface (CNI) plugins, which is common plugin architecture for containers. It’s currently supported by several orchestration tools such as Kubernetes, Mesos, and CloudFoundry.

There are various overlay plugins, some of which are discussed below:

· Flannel is a very simple etcd backed overlay network that comes from CoreOS. It creates another virtual, routable IP Per Pod network, which runs above the underlay network; ergo, it is called an overlay network. Each Pod will be assigned one IP address in this overlay network, and they communicate with each other using their IP directly.

· Weave provides an overlay network that is compatible with Kubernetes through a CNI plugin.


Kubernetes services are abstractions which route traffic to a set of pods to provide a microservice. Kube-proxy runs on each node and manages services by setting up a bunch of iptable rules.

There are three modes of setting up services:
1. ClusterIP (only provides access internally)
2. NodePort (needed to open firewall on a port; not recommended for public access)
3. LoadBalancer (owned by public cloud providers like AWS or GKE)

ConfigMap and Secret

12factor app suggests that only the configuration changes in a container.

ConfigMap makes it possible to inject a configuration based on an environment while keeping the container image identical across multiple environments. These can be injected by mounting volumes or environment variables, and it stores these values in the key/value format.

Secrets are used to store sensitive data such as passwords, OAuth tokens, etc.

Rolling Deployment and Rollback

A deployment object holds one or more replica sets to support the rollback mechanism. In other words, it creates a new replica set every time the deployment configuration is changed and keeps the previous version in order to have the option of rollback. Only one replica set will be in active state at a certain time.

For rolling deployment, the strategy type required is RollingUpdate and minReadySecs which specifies the time that the application takes to serve traffic. It will be unavailable if we leave it on default in the case that the application pods are not ready. This action can be done by running the command below:

$kubectl set image deployment 
    <image> — record


By replacing content in deployment yaml file and running the command below:

$ kubectl replace -f 
<yaml> — record

If the new version is not behaving as expected, then it is possible to rollback to the previous version by running the below command:

$ kubectl rollout undo deployment 

If the desired version is any revision other than the previous one, then run:

$ kubectl rollout undo deployment 
<deployment> — to-revision=


To oversee application behavior, one has to check logs — multiple are generated in each pod. To start searching logs in the Dashboard UI, there has to be some mechanism that collects and aggregates them into one log viewer. To illustrate, Fluentd, an open source tool and part of Cloud Native Computing Foundation (CNCF), combines perfectly with ElasticSearch and Kibana.

kubernates ,kubernetes cluster ,google container engine ,cloud ,aws ,cloud native ,azure ,docker ,google cloud

Published at DZone with permission of Abhay Diwan . See the original article here.

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