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Today, the company is announcing its acquisition by New Relic, the publicly traded monitoring and observability platform. The Pixie Labs brand and product will remain in place and allow New Relic ...
OSM was written in the Go programming language and designed to be a reference implementation of the Service Mesh Interface (SMI) specification, a standard interface for service meshes on Kubernetes. [5] The software was based on the Envoy proxy server and allowed users to uniformly manage, secure, and get out-of-the-box observability features ...
Dynatrace, Inc. is a technology company that provides a software observability platform. Dynatrace technologies are used to monitor, analyze, and optimize application performance, software development and security practices, IT infrastructure, and user experience for businesses and government agencies throughout the world.
Prometheus is a free software application used for event monitoring and alerting. [2] It records metrics in a time series database (allowing for high dimensionality) built using an HTTP pull model, with flexible queries and real-time alerting.
Hubble is the observability, service map, and UI of Cilium which is shipped with the CNI. [59] [60] It can be used to observe individual network packet flows, view network policy decisions to allow or block traffic, and build up service maps showing how Kubernetes services are communicating. [61]
The Kubernetes ingress concept was modeled after this. [11] OpenShift includes other software such as application runtimes as well as infrastructure components from the Kubernetes ecosystem. For example, for observability needs, Prometheus, Fluentd, Vector, Loki, and Istio (and their dependencies) are included. The Red Hat branding of Istio is ...
Kubernetes (/ ˌ k (j) uː b ər ˈ n ɛ t ɪ s,-ˈ n eɪ t ɪ s,-ˈ n eɪ t iː z,-ˈ n ɛ t iː z /, K8s) [3] is an open-source container orchestration system for automating software deployment, scaling, and management.
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google.The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development (Kubeflow Notebooks [4]), model training (Kubeflow Pipelines, [5] Kubeflow Training Operator [6]), model serving (KServe [a] [7]), and ...