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  2. Kubernetes - Wikipedia

    en.wikipedia.org/wiki/Kubernetes

    Simplified view showing how Services interact with Pod networking in a Kubernetes cluster. A Kubernetes service is a set of pods that work together, such as one tier of a multi-tier application. The set of pods that constitute a service are defined by a label selector. [32] Kubernetes provides two modes of service discovery, using environment ...

  3. Computer cluster - Wikipedia

    en.wikipedia.org/wiki/Computer_cluster

    In either case, the cluster may use a high-availability approach. Note that the attributes described below are not exclusive and a "computer cluster" may also use a high-availability approach, etc. "Load-balancing" clusters are configurations in which cluster-nodes share computational workload to provide better overall performance.

  4. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster.

  5. MySQL Cluster - Wikipedia

    en.wikipedia.org/wiki/MySQL_Cluster

    MySQL Cluster, also known as MySQL Ndb Cluster is a technology providing shared-nothing clustering and auto-sharding for the MySQL database management system.It is designed to provide high availability and high throughput with low latency, while allowing for near linear scalability. [3]

  6. k-medians clustering - Wikipedia

    en.wikipedia.org/wiki/K-medians_clustering

    In statistics, k-medians clustering [1] [2] is a cluster analysis algorithm. It is a generalization of the geometric median or 1-median algorithm, defined for a single cluster. k-medians is a variation of k-means clustering where instead of calculating the mean for each cluster to determine its centroid, one instead calculates the median.

  7. Cluster sampling - Wikipedia

    en.wikipedia.org/wiki/Cluster_sampling

    An example of cluster sampling is area sampling or geographical cluster sampling.Each cluster is a geographical area in an area sampling frame.Because a geographically dispersed population can be expensive to survey, greater economy than simple random sampling can be achieved by grouping several respondents within a local area into a cluster.