instruction: Explain overview | kubernetes
output: Overview
  Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
  This page is an overview of Kubernetes.
  The name Kubernetes originates from Greek, meaning helmsman or pilot. K8s as an abbreviation
  results from counting the eight letters between the "K" and the "s". Google open-sourced the
  Kubernetes project in 2014. Kubernetes combines
  over 15 years of Google's experience
  running
  production workloads at scale with best-of-breed ideas and practices from the community.
  Why you need Kubernetes and what it can do
  Containers are a good way to bundle and run your applications. In a production
  environment, you need to manage the containers that run the applications and
  ensure that there is no downtime. For example, if a container goes down, another
  container needs to start. Wouldn't it be easier if this behavior was handled by a system?
  That's how Kubernetes comes to the rescue! Kubernetes provides you with a framework
  to run distributed systems resiliently. It takes care of scaling and failover for
  your application, provides deployment patterns, and more. For example: Kubernetes
  can easily manage a canary deployment for your system.
  Kubernetes provides you with:
  Service discovery and load balancing
  Kubernetes can expose a container using the DNS name or using their own IP address.
  If traffic to a container is high, Kubernetes is able to load balance and distribute
  the network traffic so that the deployment is stable.
  Storage orchestration
  Kubernetes allows you to automatically mount a storage system of your choice, such as
  local storages, public cloud providers, and more.
  Automated rollouts and rollbacks
  You can describe the desired state for your deployed containers using Kubernetes,
  and it can change the actual state to the desired state at a controlled rate.
  For example, you can automate Kubernetes to create new containers for your
  deployment, remove existing containers and adopt all their resources to the new container.
  Automatic bin packing
  You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks.
  You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit
  containers onto your nodes to make the best use of your resources.
  Self-healing
  Kubernetes restarts containers that fail, replaces containers, kills containers that don't
  respond to your user-defined health check, and doesn't advertise them to clients until they
  are ready to serve.
  Secret and configuration management
  Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens,
  and SSH keys. You can deploy and update secrets and application configuration without
  rebuilding your container images, and without exposing secrets in your stack configuration.
  Batch execution
  In addition to services, Kubernetes can manage your batch and CI workloads, replacing containers that fail, if desired.
  Horizontal scaling
  Scale your application up and down with a simple command, with a UI, or automatically based on CPU usage.
  IPv4/IPv6 dual-stack
  Allocation of IPv4 and IPv6 addresses to Pods and Services
  Designed for extensibility
  Add features to your Kubernetes cluster without changing upstream source code.
  What Kubernetes is not
  Kubernetes is not a traditional, all-inclusive PaaS (Platform as a Service) system.
  Since Kubernetes operates at the container level rather than at the hardware level,
  it provides some generally applicable features common to PaaS offerings, such as
  deployment, scaling, load balancing, and lets users integrate their logging, monitoring,
  and alerting solutions. However, Kubernetes is not monolithic, and these default solutions
  are optional and pluggable. Kubernetes provides the building blocks for building developer
  platforms, but preserves user choice and flexibility where it is important.
  Kubernetes:
  Does not limit the types of applications supported. Kubernetes aims to support an
  extremely diverse variety of workloads, including stateless, stateful, and data-processing
  workloads. If an application can run in a container, it should run great on Kubernetes.
  Does not deploy source code and does not build your application. Continuous Integration,
  Delivery, and Deployment (CI/CD) workflows are determined by organization cultures and
  preferences as well as technical requirements.
  Does not provide application-level services, such as middleware (for example, message buses),
  data-processing frameworks (for example, Spark), databases (for example, MySQL), caches, nor
  cluster storage systems (for example, Ceph) as built-in services. Such components can run on
  Kubernetes, and/or can be accessed by applications running on Kubernetes through portable
  mechanisms, such as the
  Open Service Broker
  .
  Does not dictate logging, monitoring, or alerting solutions. It provides some integrations
  as proof of concept, and mechanisms to collect and export metrics.
  Does not provide nor mandate a configuration language/system (for example, Jsonnet). It provides
  a declarative API that may be targeted by arbitrary forms of declarative specifications.
  Does not provide nor adopt any comprehensive machine configuration, maintenance, management,
  or self-healing systems.
  Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need
  for orchestration. The technical definition of orchestration is execution of a defined workflow:
  first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable
  control processes that continuously drive the current state towards the provided desired state.
  It shouldn't matter how you get from A to C. Centralized control is also not required. This
  results in a system that is easier to use and more powerful, robust, resilient, and extensible.
  Historical context for Kubernetes
  Let's take a look at why Kubernetes is so useful by going back in time.
  Traditional deployment era:
  Early on, organizations ran applications on physical servers. There was no way to define
  resource boundaries for applications in a physical server, and this caused resource
  allocation issues. For example, if multiple applications run on a physical server, there
  can be instances where one application would take up most of the resources, and as a result,
  the other applications would underperform. A solution for this would be to run each application
  on a different physical server. But this did not scale as resources were underutilized, and it
  was expensive for organizations to maintain many physical servers.
  Virtualized deployment era:
  As a solution, virtualization was introduced. It allows you
  to run multiple Virtual Machines (VMs) on a single physical server's CPU. Virtualization
  allows applications to be isolated between VMs and provides a level of security as the
  information of one application cannot be freely accessed by another application.
  Virtualization allows better utilization of resources in a physical server and allows
  better scalability because an application can be added or updated easily, reduces
  hardware costs, and much more. With virtualization you can present a set of physical
  resources as a cluster of disposable virtual machines.
  Each VM is a full machine running all the components, including its own operating
  system, on top of the virtualized hardware.
  Container deployment era:
  Containers are similar to VMs, but they have relaxed
  isolation properties to share the Operating System (OS) among the applications.
  Therefore, containers are considered lightweight. Similar to a VM, a container
  has its own filesystem, share of CPU, memory, process space, and more. As they
  are decoupled from the underlying infrastructure, they are portable across clouds
  and OS distributions.
  Containers have become popular because they provide extra benefits, such as:
  Agile application creation and deployment: increased ease and efficiency of
  container image creation compared to VM image use.
  Continuous development, integration, and deployment: provides for reliable
  and frequent container image build and deployment with quick and efficient
  rollbacks (due to image immutability).
  Dev and Ops separation of concerns: create application container images at
  build/release time rather than deployment time, thereby decoupling
  applications from infrastructure.
  Observability: not only surfaces OS-level information and metrics, but also
  application health and other signals.
  Environmental consistency across development, testing, and production: runs
  the same on a laptop as it does in the cloud.
  Cloud and OS distribution portability: runs on Ubuntu, RHEL, CoreOS, on-premises,
  on major public clouds, and anywhere else.
  Application-centric management: raises the level of abstraction from running an
  OS on virtual hardware to running an application on an OS using logical resources.
  Loosely coupled, distributed, elastic, liberated micro-services: applications are
  broken into smaller, independent pieces and can be deployed and managed dynamically –
  not a monolithic stack running on one big single-purpose machine.
  Resource isolation: predictable application performance.
  Resource utilization: high efficiency and density.
  What's next
  Take a look at the
  Kubernetes Components
  Take a look at the
  The Kubernetes API
  Take a look at the
  Cluster Architecture
  Ready to
  Get Started
  ?
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  Last modified September 11, 2024 at 3:17 PM PST:
  Removed duplicated paragraph (7e71096044)