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Learn

The Learn section provides comprehensive documentation about the entities Causely discovers, the root causes it identifies, key terminology, and security information.

This reference documentation helps you understand how Causely's causal reasoning engine works, what types of entities it discovers in your environment, the root causes it can identify, and the terminology used throughout the documentation.

How Causely Works​

Causely uses a model-driven reasoning engine to continuously infer root causes for symptoms observed in production. The system works alongside your existing observability stack, interpreting the meaning behind metrics, logs, and traces, rather than replacing them.

Learn more about the core concepts and mechanisms behind Causely's causal reasoning engine, including ontology, topology graphs, causality mapping, and analysis in How Causely Works.

Entity Types​

Causely automatically discovers over 25 different entity types from your cloud native environment through data sources like eBPF, Cloud APIs, and OpenTelemetry. These entities are used to build topologies, identify defects, and infer root causes.

Learn about the different types of entities that Causely automatically discovers, including applications, services, databases, compute resources, messaging systems, and data pipelines in Entity Types.

Root Causes​

With more than 100 types of root causes captured in its Causal Models, Causely can pinpoint hundreds of thousands of potential issues and their effects within your environment. Root causes span applications, infrastructure, data pipelines, release management, and services.

Explore the types of root causes that Causely can identify and how they impact your systems, from application bugs to infrastructure bottlenecks to release-related issues in Root Causes.

Symptoms​

Symptoms are observable anomalies in managed objects that may be caused by root causes. Causely detects a wide variety of symptoms across services, workloads, compute resources, databases, messaging systems, and more.

Browse the complete reference of all symptoms that Causely can detect, organized by category and entity type, in Symptoms.

Terminology​

Understanding the key terms and concepts used throughout Causely documentation helps you get the most out of the system. The terminology covers core concepts like entities, symptoms, root causes, topology, causality graphs, and more.

Understand the key terms and concepts used throughout Causely documentation, grouped by relatedness to help you navigate the system effectively in Terminology.

Security​

Causely is designed to protect sensitive data and ensure privacy. The system processes telemetry data locally and primarily transmits minimal, high-level information to its backend. All data is encrypted in transit and at rest.

Learn about Causely's security model, data handling practices, privacy protections, and the permissions required for deployment components in Security.