Kubernetes (K8S), Microservices

DevopsHub has implemented Kubernetes for multiple companies in the UK; furthermore, we employ original developer of Kubernetes who has worked for Google for 12 years, and we would be happy to automate your infrastructure with Kubernetes.

Kubernetes (K8S) and Microservices

Introduction

In the rapidly evolving landscape of software development, Kubernetes (K8S) and microservices have emerged as critical technologies. They enable businesses to build, deploy, and manage applications more efficiently and effectively. This article explores the necessity, usefulness, and challenges associated with Kubernetes and microservices, highlighting their roles in modern software architecture.

The Necessity of Kubernetes and Microservices

1. Scalability and Flexibility:

   • Dynamic Scaling: As applications grow, the need for scalable solutions becomes paramount. Kubernetes, with its robust orchestration capabilities, allows for dynamic scaling of applications to meet varying demand levels.
   • Service Independence: Microservices architecture enables the development of applications as a suite of small, independent services. This modularity allows for individual components to be scaled independently, providing flexibility and improving resource utilisation.

2. Agility and Speed:

   • Continuous Deployment: In today's fast-paced digital environment, rapid deployment cycles are essential. Kubernetes supports continuous integration and continuous deployment (CI/CD) pipelines, facilitating faster release cycles.
   • Reduced Time-to-Market: Microservices, by enabling parallel development and deployment of services, significantly reduce the time-to-market for new features and updates.

3. Resilience and Reliability:

   • Fault Isolation: With microservices, faults in one service do not necessarily impact others, enhancing the overall resilience of applications.
   • Self-Healing Capabilities: Kubernetes provides self-healing features, such as automatic restarts, replacements, and scaling of failed containers, ensuring high availability and reliability.

Usefulness of Kubernetes and Microservices

1. Enhanced Developer Productivity:

   • Simplified Management: Kubernetes automates many aspects of application deployment and management, reducing the operational burden on developers and allowing them to focus on writing code.
   • Modular Development: Microservices enable teams to work on different components simultaneously, enhancing collaboration and productivity.

2. Resource Optimisation:

   • Efficient Utilisation: Kubernetes optimises the use of underlying infrastructure resources through effective container orchestration, leading to cost savings.
   • Right-Sizing Services: Microservices architecture allows for fine-tuned allocation of resources to individual services based on their specific needs, avoiding over-provisioning.

3. Improved Maintenance and Updates:

   • Incremental Updates: With microservices, updates can be made incrementally to individual services without affecting the entire application, simplifying maintenance and reducing downtime.
   • Rolling Updates and Rollbacks: Kubernetes supports rolling updates and rollbacks, enabling smooth and controlled deployment of new versions while maintaining system stability.

Challenges of Kubernetes and Microservices

1. Complexity:

   • Steep Learning Curve: Both Kubernetes and microservices introduce a level of complexity that requires significant learning and adaptation. Kubernetes, in particular, has a steep learning curve due to its extensive features and configurations.
   • Service Management: Managing numerous microservices can be challenging, necessitating robust service discovery, monitoring, and communication mechanisms.

2. Security:

   • Increased Attack Surface: The distributed nature of microservices can increase the attack surface, requiring comprehensive security strategies to protect inter-service communication and data.
   • Configuration Management: Kubernetes environments need meticulous configuration management to ensure security policies are consistently applied and maintained.

3. Operational Overhead:

   • Resource Consumption: Running Kubernetes clusters can be resource-intensive, potentially leading to higher operational costs.
   • Monitoring and Logging: Effective monitoring and logging of a microservices architecture demand advanced tools and practices to handle the volume and complexity of data generated.

Kubernetes and microservices are indispensable in modern software development, offering unparalleled scalability, flexibility, and resilience. Their ability to enhance developer productivity, optimise resource usage, and facilitate rapid deployment cycles makes them crucial for businesses aiming to stay competitive. However, the adoption of these technologies is not without its challenges. Complexity, security concerns, and operational overhead must be carefully managed to realise their full potential. By investing in the necessary skills, tools, and strategies, organisations can harness the power of Kubernetes and microservices to drive innovation and achieve operational excellence.

Kubernetes (commonly stylized as k8s) is an open-source container orchestration system for automating application deployment, scaling, and management. It was originally designed by Google, and is now maintained by the Cloud Native Computing Foundation. 

It aims to provide a "platform for automating deployment, scaling, and operations of application containers across clusters of hosts". It works with a range of container tools, including Docker. 

Many cloud services offer a Kubernetes-based platform or infrastructure as a service (PaaS or IaaS) on which Kubernetes can be deployed as a platform-providing service. Many vendors also provide their own branded Kubernetes distributions.

Kubernetes manages containerized applications across a set of containers or hosts and provides mechanisms for deployment, maintenance, and application-scaling. Docker packages, instantiates, and runs containerized applications.

A Kubernetes cluster consists of one or more masters and a set of nodes.

Kubernetes follows the master-slave architecture. The components of Kubernetes can be divided into those that manage an individual node and those that are part of the control plane.

Kubernetes control plane (master)

The Kubernetes Master is the main controlling unit of the cluster, managing its workload and directing communication across the system. The Kubernetes control plane consists of various components, each its own process, that can run both on a single master node or on multiple masters supporting high-availability clusters. The various components of Kubernetes control plane are as follows:

etcd

etcd is a persistent, lightweight, distributed, key-value data store developed by CoreOS that reliably stores the configuration data of the cluster, representing the overall state of the cluster at any given point of time. Just like Apache ZooKeeper, etcd is a system that favors Consistency over Availability in the event of a network partition (see CAP theorem). This consistency is crucial for correctly scheduling and operating services. The Kubernetes API Server uses etcd's watch API to monitor the cluster and roll out critical configuration changes or simply restore any divergences of the state of the cluster, back to what was declared by the deployer. As an example, if the deployer specified that three instances of a particular pod need to be running, this fact is stored in etcd. If it is found that only two instances are running, this delta will be detected by comparison with etcd data, and Kubernetes will use this to schedule the creation of an additional instance of that pod.

API server

The API server is a key component and serves the Kubernetes API using JSON over HTTP, which provides both the internal and external interface to Kubernetes. The API server processes and validates REST requests and updates state of the API objects in etcd, thereby allowing clients to configure workloads and containers across Worker nodes.

Scheduler

The scheduler is the pluggable component that selects which node an unscheduled pod (the basic entity managed by the scheduler) runs on, based on resource availability. Scheduler tracks resource use on each node to ensure that workload is not scheduled in excess of available resources. For this purpose, the scheduler must know the resource requirements, resource availability, and other user-provided constraints and policy directives such as quality-of-service, affinity/anti-affinity requirements, data locality, and so on. In essence, the scheduler's role is to match resource "supply" to workload "demand".

Controller manager

A controller is a reconciliation loop that drives actual cluster state toward the desired cluster state. It does this by managing a set of pods. One kind of controller is a replication controller, which handles replication and scaling by running a specified number of copies of a pod across the cluster. It also handles creating replacement pods if the underlying node fails.[28] Other controllers that are part of the core Kubernetes system include a "DaemonSet Controller" for running exactly one pod on every machine (or some subset of machines), and a "Job Controller" for running pods that run to completion, e.g. as part of a batch job. The set of pods that a controller manages is determined by label selectors that are part of the controller's definition.

The controller manager is a process that runs core Kubernetes controllers like DaemonSet Controller and Replication Controller. The controllers communicate with the API server to create, update, and delete the resources they manage (pods, service endpoints, etc.).

Kubernetes node (slave)

The Node, also known as Worker or Minion, is a machine where containers (workloads) are deployed. Every node in the cluster must run a container runtime such as Docker, as well as the below-mentioned components, for communication with master for network configuration of these containers.

Kubelet

Kubelet is responsible for the running state of each node, ensuring that all containers on the node are healthy. It takes care of starting, stopping, and maintaining application containers organized into pods as directed by the control plane.

Kubelet monitors the state of a pod, and if not in the desired state, the pod re-deploys to the same node. Node status is relayed every few seconds via heartbeat messages to the master. Once the master detects a node failure, the Replication Controller observes this state change and launches pods on other healthy nodes.

Container

A container resides inside a pod. The container is the lowest level of a micro-service that holds the running application, libraries, and their dependencies. Containers can be exposed to the world through an external IP address. Kubernetes supports Docker containers since its first version, and in July 2016 rkt container engine was added.

Kube-proxy

The Kube-proxy is an implementation of a network proxy and a load balancer, and it supports the service abstraction along with other networking operation. It is responsible for routing traffic to the appropriate container based on IP and port number of the incoming request.

cAdvisor

cAdvisor is an agent that monitors and gathers resource usage and performance metrics such as CPU, memory, file and network usage of containers on each node.