Introduction
AIOps - Artificial Intelligence in the service of DevOps
co.brick observe belongs to the AIOps industry category of software:
info
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).