Introduction to Kubernetes
Kubernetes, often abbreviated as K8s, is an open source platform for automating the deployment, scaling, and management of containerized applications. Originally developed by Google, Kubernetes has become one of the most widely adopted container orchestration platforms in the world. It provides a powerful set of tools to manage the lifecycle of containerized applications across clusters of machines, whether on-premises or in the cloud.
Why choose Kubernetes?
As applications become more complex and distributed, the need for tools to manage and orchestrate containers grows. Kubernetes solves several key challenges in container management:
- Zoom: Automatically expand the number of container execution individuals according to demand.
- load balancing: Distribute traffic across containers to ensure high availability and performance.
- Self-healing: Automatically replace or reschedule failed or unresponsive containers.
- Declarative configuration: Manage application deployment and configuration using code for easy version control and rollback.
Kubernetes core concepts
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cluster:
A Kubernetes cluster is a group of nodes (virtual or physical machines) that run containerized applications. A cluster has at least one master node and multiple worker nodes. -
node:
A node is a machine in a Kubernetes cluster. It can be a virtual machine or a physical server and contains the services required to run the container. Each node contains:- Cubelet: Agent that ensures containers are running as expected on the node.
- this is an agent: Maintain network rules for Pod communication.
- container runtime: Software that runs containers (for example, Docker, containerd).
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pod:
Pod is the smallest and simplest Kubernetes object. It is a group of one or more containers that share the same network namespace, IP address, and storage volume. Pods are the basic execution unit in Kubernetes, designed to run closely related containers that require shared resources. -
deploy:
Deployment in Kubernetes manages the establishment and expansion of Pods. It defines the desired state of a Pod (such as the number of replicas) and ensures that state is maintained by creating new Pods or terminating old Pods as needed. -
Serve:
A service is an abstraction that defines a set of Pods and provides stable endpoints to access them. It load balances traffic across multiple Pods, ensuring that applications remain available and responsive even if Pods are expanded or replaced. -
Entrance:
An ingress is a collection of rules that allow inbound connections to cluster services. It typically includes load balancing, SSL termination, and routing rules for HTTP and HTTPS traffic. -
namespace:
Namespaces are logical partitions within a Kubernetes cluster. It allows users to group resources together, making them easier to manage and isolate. For example, you can use different namespaces for development, staging, and production environments. -
volume:
Volumes are storage resources in Kubernetes that can be used by containers in pods. It allows data to persist beyond the lifetime of a single container and enables containers to share data. Kubernetes supports multiple types of volumes, such as hostPath, PersistentVolumeClaim (PVC), NFS, etc.
How Kubernetes works
Kubernetes follows a declarative approach, where users define the desired state of the system, and Kubernetes ensures that the actual state matches the desired state. The process involves the following steps:
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Define resources: Users use YAML or JSON configuration files to define the resources required by their applications. These resources can include deployments, services, portals, disks, etc.
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Kubernetes controller: The controller manager continuously monitors the status of the cluster and defined resources. If there is a discrepancy between the current state and the desired state (for example, a pod fails or becomes unhealthy), the controller takes action to restore the system to the desired state.
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scheduler: The Kubernetes scheduler places Pods on nodes in a cluster based on resource availability and other constraints. It optimizes resource allocation within the cluster.
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Kubelet and Kube agent: Once a pod is scheduled to a node, the kubelet on the node ensures that the container operates normally. The kube proxy manages network connections and load balancing for services.
Why use Kubernetes?
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Auto scaling: Kubernetes can automatically scale applications up or down based on resource usage or custom metrics. This enables efficient use of resources and improves application performance.
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High availability: Kubernetes ensures application high availability by automatically restarting failed containers, redistributing workloads among healthy nodes, and managing redundant resources.
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Self-healing: If a container fails or becomes unresponsive, Kubernetes can automatically replace it with a new container, ensuring minimal downtime and impact on the entire application.
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portability: Kubernetes abstracts the underlying infrastructure, allowing applications to run in any environment, whether on-premises, in the cloud, or in a hybrid environment.
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Simplify management: Kubernetes provides powerful tools for application deployment, version control, monitoring, logging, and troubleshooting, making it easier for teams to manage complex applications.
Kubernetes use cases
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microservices: Kubernetes is well suited for microservices-based architectures, where each service can run in its own container, allowing for scalability, isolation, and ease of management.
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CI/CD pipeline: Kubernetes integrates well with continuous integration and continuous deployment (CI/CD) tools to enable automated testing, deployment, and scaling of applications.
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Hybrid and multi-cloud environments: Kubernetes allows enterprises to manage applications across different cloud providers or on-premises systems, providing the flexibility to choose the best infrastructure for each workload.
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Big data and machine learning: Kubernetes can be used to manage and scale big data applications, including distributed systems such as Hadoop, Spark, and machine learning frameworks.
Kubernetes ecosystem
Kubernetes has a vast ecosystem of tools and integrations that extend its capabilities. Some popular tools and projects include:
- rudder: A package manager for Kubernetes that simplifies application installation and management.
- Prometheus: Monitoring system and time series repository, often used with Kubernetes to collect metrics.
- In this regard: A service mesh that provides advanced traffic management, security, and observability for microservices running on Kubernetes.
- Kubernetes Operator: Custom controller designed to manage complex, stateful applications on Kubernetes.
- to Bechtel: Command-line tool for interacting with Kubernetes clusters, managing resources, and troubleshooting issues.
in conclusion
Kubernetes revolutionizes the way organizations deploy and manage containerized applications. It provides powerful tools to automate container management, scale applications and ensure high availability, making it an essential tool for modern DevOps practices. Whether you’re running microservices, large applications, or distributed systems, Kubernetes provides a reliable and efficient platform for orchestrating containerized workloads.