What problems are solved by Kubernetes? a.k.a. why Kubernetes was created?

After the intro to the series, let's take a deep dive into why Kubernetes was created.

Kubernetes solves a variety of problems related to deploying, managing, and scaling containerized applications (we will discuss the advantages of containerized applications in a different series). It provides a platform for automating many of the manual tasks required for running applications in a distributed environment. Here's how it addresses key challenges:

Container Orchestration: Kubernetes is a container orchestrator that manages the deployment and scaling of containerized applications. It automates the scheduling of containers to run on servers and ensures that the correct number of application instances are running and available.

• Kubernetes handles restarting containers when they fail, moving containers to new hosts when a host becomes unhealthy, and other management tasks.
• It provides mechanisms for managing the container lifecycle, including starting, stopping, and updating containers.

Kubernetes abstracts the underlying infrastructure, so developers do not need to worry about which specific machine or cloud their application runs on.

Application Deployment and Management: Kubernetes simplifies the process of deploying applications, making it faster and more reliable. It allows for the creation of multiple application instances, which provides high availability and the ability to handle large traffic volumes.

• Kubernetes uses a declarative model, where users define the desired state of the system, and Kubernetes takes the necessary actions to achieve that state. This approach simplifies management and enables self-healing, scaling, and version control.
• It allows for rolling updates and rollbacks, which minimize downtime and disruptions during application updates.

It facilitates continuous deployment practices, such as canary and blue-green deployments. It also provides a consistent approach to application rollout and reliability, which enables a consistent lifecycle across different microservice teams.

Scalability and High Availability: Kubernetes enables applications to scale dynamically based on demand, automatically adding or removing container instances to match the current load.

• It provides load balancing across multiple instances of an application.
• It includes autoscaling features that respond to demand spikes, prevent service disruptions by dynamically adjusting the number of replicas, and can scale down when demand decreases.
• Kubernetes also supports high availability by distributing Pods across multiple nodes and restarting failed containers automatically.

Resource Management: Kubernetes manages resources across nodes using resource requests and limits, which ensure that containers have the resources they need to run efficiently without affecting other containers.

• The scheduler places Pods on nodes based on resource requests and other criteria, aiming for high utilization of cluster resources.
• It supports a variety of node sizes and attempts to distribute workloads fairly across as many nodes as possible.
• The Descheduler tool can be used to rebalance the cluster by moving Pods from one node to another to improve resource utilization.
• Service Discovery and Networking: Kubernetes simplifies service discovery by providing a stable IP and DNS name for applications, which ensures that services can find and communicate with each other even as Pods are moved or restarted.
• It handles network routing and load balancing using a service object that exposes a stable IP address and DNS name to multiple pods.
• It has a network model that allows all containers to communicate with other containers, and all nodes can communicate with all containers without network address translation (NAT).
• Abstraction and Portability: Kubernetes provides an infrastructure-agnostic platform, meaning that applications can run on any cloud provider or on-premises environment, making it easier to avoid vendor lock-in.
• It abstracts the underlying hardware and operating system, allowing developers to focus on application logic instead of infrastructure details.
• It also enables a high degree of portability since developers are consuming a higher-level API that is implemented in terms of specific cloud infrastructure APIs.

Simplified Operations and Automation: Kubernetes automates many of the tasks that system administrators traditionally perform, such as upgrading servers, installing security patches, configuring networks, and running backups.

• This automation enables operations teams to focus on core work and simplifies their workload by allowing them to manage a unified compute substrate rather than a sprawling estate of machines.
• It provides tools that automate the distribution of applications across a cluster of machines.
• It reduces the burden on operators by performing reliable repairs more quickly using its self-healing capabilities.
• Extensibility: Kubernetes is designed to be extensible, allowing users to add custom resources and controllers to meet specific needs.
• Operators are a way of packaging, running, and maintaining Kubernetes applications and extending Kubernetes to automate the management of the entire lifecycle of a particular application.

Microservices Architecture:

• Kubernetes is well-suited for microservices architectures because it allows for independent deployment, scaling, and management of individual services.
• It provides abstractions to make it easier to build decoupled microservice architectures.
• The use of containers and Pods in Kubernetes allows for the grouping of container images developed by different teams into a single deployable unit.

By providing solutions to these problems, Kubernetes allows organizations to build and operate complex distributed systems more efficiently and reliably.