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AIOps - Artificial Intelligence in the service of DevOps

co.brick observe belongs to the AIOps industry category of software:


AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.1

It uses ML/AI methods to detect, predict, and help to avoid both common and rare issues in operating cloud-native, SaaS systems.

Overview of co.brick observe

co.brick observe is a tool that helps DevOps to be productive in their daily work. Out of the box, it offers:

  • status dashboard presenting the high-level state of the monitored system,
  • insights into services of the system with access to:
    • metrics,
    • logs,
    • events,
    • topology of the whole system (components and connection),
    • runtime information on single components.
  • issue detection features that allow for:
    • early discovery of runtime problems,
    • discovery of configuration mistakes and errors,
    • detection of abnormal patterns (anomalies),
    • graphical display of issue trends.
  • the physical composition of the system:
    • nodes, pods (for Kubernetes).
  • pre-configured and configurable:
    • alerts,
    • SLOs.
  • integrations with 3rd party tools (like Slack).

All of the above features help DevOps by:

  • giving instant information about the state of the system,
  • giving contextual information related to an issue:
    • metrics and logs,
    • similar issues.
  • skilling up the team on:
    • common configuration mistakes,
    • inefficient resource allocation.

By design, the overhead needed to start using the system is reduced to a single command that installs proper collectors (see agent's documentation for more details).


  1. Gartner Glossary: AIOps