Basic concepts of docker/kubernete/kata-container

Kubereters

An open-source system for automating deployment, scaling, and management of containerized applications;

 

 

 

 

Traditional >> Hypervisor >> Container

Traditional:

  No way to define resource boundaries for applications in a physical server before, run each applications on a different physical server;

Hypervisor: 

  Will run multi VMs on a single physical server's CPU; 

  Allow applications to be isolated between VMs and provides a level of securiy as the infomation of one application cannot be freely accessed by another     application;

  Each VM is a full machine running all the components, including its own operating system;

Container:

  Have relaxed isolation properties to share the operating system among the applications;

  Lightweight;

  A container has its own filesytem/CPU/memory/process space/..

  Are portable across clouds and OS distributions because they are decoupled from the underlying infrastrucure;

  Benifits of containers:

    1. Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use

    2. Continuous development, integrations and deployment:

      provide for reliable and frequent container image build and deployment with quick and easy rollbacks;

    3. Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure;

    4. Obervability not only surfaces OS-level information and metrics, but also application health and other signals;

    5. Environmental consistency across development, testing, and production; Runs the same on a laptop as it does in the cloud;

    6. Cloud and OS distribution portabilty: Runs on Ubuntu, RHEL, CoreOS, on-prem, Google Kubernetes Engine, and anywhrere else;

    7. Application-centric management;

    8. Loosely coupled, distributed;

    9. Resource isolation;

    10. Resource utilization;

 

Benefits of Kubernetes:

  1.  Service discovery and load balancing    

      kubernetes 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;

  2.  Stroage orchestartion

      automatically mount a storage system of local storages/public cloud providers/..

  3.  Automated rollouts and rollbacks

      automake kubernets to create new containers

  4.  Self-healing

      restart fail containers, kill no-respond containers;

  5.  Automatic bin packing

      tell kubernetes how much CPU and RAM each container needs, kubernets can fit containers onto your nodes to make the best use of you resources;

 

Kubernetes Master

When deploying kubernetes, we wil get a cluster, which is a set of machines (nodes),

that run containerzed applications managed by kubernetes.

A cluster has at least one worker node and at least one master node;

 

Kubernetes Master is a collection of three processes that run on a single node in your cluster, which is designed as the master node;

Three processes:

  Kube-apiserver;

  Kube-controller-manager;

  Kube-scheduler;

 

Individual non-master node in cluster run two processes:

  kubelet

    which communicates with the Kubernetes Master;

    The primary node agent that runs on each node; It can register the node with tha apiserver using one of

      the host name;

      a flag to override the hostname;

      specific logic for a cloud provider;

    

  kube-proxy

    a network proxy which reflects Kubernetes networking services on each node;

    Kubernets network proxy runs on each node, this relects services as defined in the Kubernetes API on each node

    and can do simple TCP/UDP and SCTP stream forwarding or round robin TCP/UDP/SCTP forwarding across a set of backends/

    Service cluster IPs and ports are currently found through Docker-links-compatible   

 

Kubernetes Objects

Kubernetes contains serveral abstractions representing the state of system;

Basic Kubernetes objects include:

 

Kata-container

An open-source project and community working to build a standard implement of lightweight VM that feel and perform like containers, but provide the workload isolation and security advantages of VMs;

 

Kata container Components

  • Agent      -- The Kata-agent runs inside the virtual machine and sets up the container environment
  • KSM throttler   -- An optional utility that monitors containers and deduplicates memory to max container density on a host
  • Proxy      -- A process running on the host and co-ordinates access to the agent running inside the VM
  • Runtime     -- Be invoked by a container manager and provides high-level verbs to manage containersd  
  • Shim        -- A process that runs on the host, acts as though it is the workload ( which actually runs inside the VM), required to be compliant with th expecations of the OCI runtime sepc
  • Hypervisor    -- 
  • Kernel      -- HV uses a linux kernel to boot the guest image

 

 

Docker

Following storage drivers:

  • overlay2     is the preferred storage driver, for all currently supported linux distributions, and requires no extra conf
  • aufs       is the preferred stroage driver for Docker 18.06 or older, when running on Ubuntu 14 on Kernel 3.13 which has no support or ovrlay2
  • devicemapper   is supported, but requires direct-lvm for production environments, because loopback-lvm, while zero-conf, has very poor performance.
posted @ 2019-10-12 14:20  coneypo  阅读(153)  评论(0编辑  收藏