Kubernetes is a platform for managing containerized applications. It does this by providing APIs that allow you to control and manage how your containerized applications are deployed, scaled, and organized. Kubernetes can be used on-premises or in the cloud and is currently the most popular platform for managing containerized applications.
One of the valuable benefits of Kubernetes is its ability to scale your applications. Kubernetes can automatically scale your applications based on CPU utilization, memory usage, or other metrics. This ensures that your application is always available and meets the needs of your users.
Kubernetes is a powerful tool that can help manage and orchestrate Docker containers. Using Kubernetes, you can create a self-contained environment for your applications that includes everything needed to run them. This can consist of the application, dependencies, libraries, and configuration files.
Kubernetes can also help you scale your applications up or down as needed, ensuring that they always have the resources needed to run efficiently. Additionally, Kubernetes provides many features to help manage Docker containers easier, such as rolling updates and health checks.
Kubernetes offers a spectrum of resources, services, and tools for application management. Some of the most used options are explored below.
Kubernetes has a resource called Ingress that is used for a variety of functions including as a load balancer. Load balancing via Ingress allows you to distribute traffic among a set of pods, exposing them as a single service. This can improve both the availability and performance of your applications.
The load balancer works by inspecting the headers of each request it receives. It selects a pod based on the request’s destination and the defined rules. It then forwards the request to that pod.
The load balancer also supports health checking, allowing you to specify a set of criteria that must be met for a pod before the load balancer will send requests to it. If a pod fails to meet the requirements, the load balancer will stop sending requests to it.
You can also use the load balancer to route traffic based on the source IP address of the request. This can be useful if you limit access to your applications from specific sources.
Kubernetes networking works by creating pods and services. A pod is a group of one or more containers that are deployed together and share a network namespace and IP address.
Containers within a pod can communicate with each other using a localhost.
Services are used to expose one or more pods to the outside world. Services are implemented as load balancers and can load balance traffic across multiple pods.
The Kubernetes scheduler is a critical part of the Kubernetes system. It is responsible for allocating resources to pods and ensuring that they can run successfully.
The scheduler works by assigning each pod a priority and looking for nodes with enough resources to accommodate the pod. If resources are not available, the scheduler can assign a node with higher-priority pods. This also factors in the different priorities of the pods to make the assignment. In general, when assigning pods to a node, the lowest priority nodes are used to minimize disruption and preemption. If there are no nodes with enough resources, the scheduler will wait until one becomes available.
The scheduler is also responsible for restarting pods that have failed. If a pod fails, the scheduler will continue it on a different node. This ensures that the pod always has access to the resources it needs to run successfully.
Kubernetes autoscaling is a great feature that allows you to scale your pods up or down automatically based on CPU utilization or other metrics. Autoscaling can help you maintain an optimal number of pods in your cluster, improving the performance and stability of your applications.
There are two types of Kubernetes autoscaling: horizontal and vertical.
Horizontal autoscaling scales your pods up or down by adding or removing nodes from your cluster. In contrast, vertical autoscaling scales your pods up or down by changing the CPU or memory limits of individual pods.
Kubernetes autoscaling is based on two concepts: scaling triggers and scaling policies. A scaling motivation is a condition that causes Kubernetes to scale your pods up or down. A scaling policy is an action that Kubernetes takes when a scaling trigger occurs.
DNS stands for domain name system, and it is a system used to translate human-readable domain names into the numerical IP addresses used by computers. Kubernetes uses DNS to manage its services. Each service in Kubernetes has a unique DNS name. When you create a service, Kubernetes creates a DNS record for that service. The DNS record contains the IP address of the service and the port number. Kubernetes uses this information to route traffic to the service.
The DNS name of a service is composed of two parts:
The domain name is the part of the DNS name familiar to all services in the domain. The service name is the part of the DNS name unique to each service.
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