The demand around scalable and reliable services is increasing every day exponentially. The market is driven by customers demanding their favorite services to have zero downtime and companies that lose millions of dollars for every minute they’re down.
If you have come across the space that is responsible for keeping the systems up, you would have heard buzz words like microservices, containers, and Kubernetes. We have covered the topics in-depth, and you could read them below.
In this post, we would focus on an orchestration tool that facilities the infrastructure support to these always-on applications.
Let’s get started!
What is Kubernetes?
Kubernetes (also called k8s or kubes) is an open-source production-grade orchestration tool that helps you automate the deployment, scaling, and management of your production containers across computer clusters.
Developed by Google and then was donated to CNCF, where companies like Google, Red Hat, IBM, and thousands of contributors carry the project forward.
Kubes manages the infrastructure by grouping many Linux containers that help you efficiently manage these containers and scale when needed from on-premises, public, private, or hybrid cloud.
Advantages of Kubernetes
The main benefit of implementing Kubernetes in your environment, particularly if you’re optimizing app development for the cloud, is that it provides a framework for scheduling and running containers on physical or virtual machine clusters.
Apart from that, you get:
- High Security due to minimal human error
- Capabilities of plugging in different tools
- Recovery of failed containers
- Load balancing between containers
- Automatic bin packing
- Automated deployments and secretes management
If you’re confused about the benefits of orchestration tools or want to go in more depth, we already have an in-depth blog. Check that out here:
Kubernetes is gaining traction among DevOps professionals because it enables them to provide a self-service Platform-as-a-Service (PaaS) that abstracts the development teams’ hardware layer.
The other reason is the big community of around 123k+ members(!) it has, that acts as a savior when stuck.
The colossal community drives the adoption, and also companies have embraced the change it has bought to their infrastructure due to scheduling and scalability it supports natively.
If you’re interested to know how DevRel plays a critical role in community building and how you can launch your products and build a community around that, then read this here.
K8s is also very lightweight and comparatively more manageable than other orchestration tools (like Mesos) without sacrificing anything significant. It can be deployed on Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), or locally. And you can transfer your loads from one provider to another or your servers without worrying about infrastructure.
Let’s take a step back and revisit what does kubes consists of in the first place.
Building blocks of Kubernetes
A cluster is a set of nodes that includes at least one master node and several worker nodes (also known as minions), which may be virtual (VMs) or physical machines.
The master handles the scheduling and deployment of application instances across nodes, and the control plane refers to the entire collection of services provided by the master node. The master uses the Kubernetes API server to communicate with the nodes. Based on the resource and policy constraints you’ve established, the scheduler assigns nodes to pods (one or more containers).
Each Kubernetes node has an agent process called a kubelet in charge of managing the node’s state, such as starting, stopping, and maintaining application containers to control plane commands. The Kubernetes API server provides all of the details for a kubelet.
The simple scheduling unit is made up of one or more containers that are guaranteed to be co-located on the host machine and share resources. Inside the cluster, each pod is given its own IP address, allowing the application to use ports without conflict.
A PodSpec is a YAML or JSON object that describes the containers’ desired state in a pod. Via the API server, these objects are transferred to the kubelet.
A label is a key/value pair associated with a Kubernetes resource, such as a pod. Labels may be applied to resources at the time of creation and later added and updated.
A deployment is a YAML object that specifies the pods and the number of replicas (container instances) for each pod.
3 Storage building blocks in Kubernetes
A container’s file system is ephemeral, meaning that any modifications made to it are lost if the container crashes, aka temporary. A volume is generated at the pod level and is used to keep data safe if a container crash. A volume can be used to share data among the pod containers. A volume inherits the pod’s lifecycle; when a pod is removed, the volume is also deleted. Different volume types are supported by Kubernetes and are implemented as plugins.
A persistent volume in a cluster is a real networked storage device that an administrator has provisioned. The lifecycle of persistent storage is independent of the lifecycle of any individual pod. It supports a variety of access modes, including read-write mounting by a single node, read-only mounting by several nodes, and read-write mounting by several nodes. Different persistent volume types are supported by Kubernetes and are implemented as plugins. AWS EBS, vSphere space, Azure File, GCE Persistent Disk, CephFS, Ceph RBD, GlusterFS, iSCSI, NFS, and Host Path are few examples of persistent volume types.
Persistent Volume Claim
A persistent volume claim specifies the amount of storage and access modes that are needed. Kubernetes looks for a persistent volume that matches the persistent volume claim and attaches it to it. A persistent volume claim can remain unbound forever if a corresponding volume does not exist. As soon as a volume that matches it becomes available, it will be bound.
I hope you are clear about Kubernetes to a considerable extent after this post. Kubes is one of the few complex topics, and things start to go complex if you don’t prefer learning by doing.
If you want to learn and explore, the official tutorial would be an excellent place to start.
Wanna play? Play with it here without any installation 😉
And if you want us to do all these deployments and orchestrations without worrying about the steep learning curve, feel free to reach out to our engineering team.