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Sosivio

Sosivio - Your Kubernetes “Life Jacket”

Cluster Overview

Purpose

Sosivio is a predicitve troubleshooting tool for Kubernetes applications and environments, built from the ground up for cloud native environments. Sosivio applies AI to do the heavy lifting by providing eventless failure prediction and autonomous failure resolution. Sosivio was built to help all stakeholders - DevOps, IT, Management, Security, Data teams, & Developers can solve the organization’s toughest problems using Sosivio while running cloud environments.

Product Features

  • Once installed, Sosivio runs as 'Yet Another Application' running on your cluster. A DaemonSet ensures every Node in the cluster contains exactly one Sosivio data collector microservice, but does not permanently install anything on the Nodes.

  • The Sosivio collector is full-stack aware. Sosivio utilizes information from:

    • Kernel signals
    • OS signals and logs
    • Container logs
    • Application signals
    • Kubernetes API

  • Sosivio is self-sufficient and requires no assistance from an external processing engine. It utilizes the same Worker Nodes that are used by other applications. All data is kept internal to the Kubernetes cluster. There is no data offloading.

  • Sosivio does not break artifacts, does not pose a security threat, or a threat of warranty annulment. Sosivio passively digests the information from the Kubernetes layers, without intervening in data flow. Sosivio does not interact with any other containers. It passively reads signals and logs. Sosivio does not inject code, require instrumentations, or require any custom data offloading requirements.
  • Sosivio utilizes lean AI for analysis, ensuring that the processing is lightweight and is distributed amongst the cluster Nodes. All of the analyzing is done on the fly while data flows through Sosivio's components. There are no additional servers required.
  • Sosivio’s footprint is light and cloud-native oriented, never exceeding 5% of existing resources and seamlessly integrating with the Kubernetes code.

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