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Kubernetes is often abbreviated as K8s, counting the eight letters between the K and the s (a numeronym). [6] Kubernetes assembles one or more computers, either virtual machines or bare metal, into a cluster which can run workloads in containers. It works with various container runtimes, such as containerd and CRI-O. [7]
In recent times, containerization technology has been widely adopted by cloud computing platforms like Amazon Web Services, Microsoft Azure, Google Cloud Platform, and IBM Cloud. [7] Containerization has also been pursued by the U.S. Department of Defense as a way of more rapidly developing and fielding software updates, with first application ...
In that case, the upper layers of the ETSI NFV MANO architecture (i.e. the NFVO and VNFM) cooperate with a container infrastructure service management (CISM) function [5] that is typically implemented using cloud-native orchestration solutions (e.g. Kubernetes). The characteristics of cloud-native network functions are: [6] [7]
In 2017, CNCF also helped the Linux Foundation launch a free Kubernetes course on the EdX platform [104] — which has more than 88,000 enrollments. [105] The self-paced course covers the system architecture, the problems Kubernetes solves, and the model it uses to handle containerized deployments and scaling.
The C10k problem is the problem of optimizing network sockets to handle a large number of clients at the same time. [1] The name C10k is a numeronym for concurrently handling ten thousand connections. [ 2 ]
When the failed network becomes available, those applications may also fail to retry any stalled operations or require a (manual) restart. Ignorance of network latency, and of the packet loss it can cause, induces application- and transport-layer developers to allow unbounded traffic, greatly increasing dropped packets and wasting bandwidth.
“Distributed” or “grid” computing in general is a special type of parallel computing that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a network (private, public or the Internet) by a conventional network interface producing commodity hardware, compared to the lower efficiency of designing and constructing a small ...
Network congestion in data networking and queueing theory is the reduced quality of service that occurs when a network node or link is carrying more data than it can handle. Typical effects include queueing delay , packet loss or the blocking of new connections.