Kubernetes

Today, it is prevalent for businesses to operate and manage multiple Kubernetes clusters and cloud-native operations across different cloud providers or infrastructures. However, as each Kubernetes cluster is a nearly self-contained unit, the upstream community tries to research and develop Kubernetes multi-cluster management solutions. That said, Kubernetes Cluster may be a possible way, among others. The most frequent use cases of multi-cluster management involve development and production isolation, service traffic load balancing, decoupling of data processing and data storage, cross-cloud backup and disaster recovery, manageable allocation of computing resources, and low latency access cross-region services, and vendor lock-in avoidance. Kubermatic is developed to address multi-cluster and multi-cloud management challenges, including the situations mentioned above. It offers users a centralized control plane to distribute applications and their models to multiple clusters from th...

  Edge computing is a term used to represent decentralized IT infrastructure. In , applications, computation, and data storage are all carried out near the source of the data, as opposed to in the cloud or at an offsite data center. Edge servers deliver enhanced performance by processing data locally and reducing the distance between devices and servers. It requires less bandwidth and decreases latency. How does it work? Traditional IT infrastructure needs data to be conveyed across long distances and multiple network connections. It may require ample bandwidth and hardware. Edge computing leads compute and storage resources closer to where the data is created, decreasing the distance it has to travel. Rather than pushing the data off to the cloud or shoving it to a central data center, it enables for real-time processing of applications within close physical proximity to the end-user. Why is edge computing necessary? Edge computing is crucial to address lapses in cloud-based appli...