Foundations of Calmo, The AI SRE
What are Knowledge Graphs?
Knowledge graphs store information as entities and their relationships, offering a structured way of representing knowledge compared to traditional databases. This structured representation is particularly useful in Site Reliability Engineering (SRE), as graphs are a natural fit for representing complex systems and their dependencies. Capturing both high-level and low-level relationships between infrastructure components provides a holistic view of system context and health, while also helping to identify potential knowledge hazards and ensure data integrity.
Temporal Data and its Impact
All production systems are dynamic in nature. Relationships between systems and services are evolving and changing over time, through deployments, code changes, and data flow. In dynamic production environments, temporal data is crucial. Temporal data refers to information associated with a specific point in time or time interval. This type of data allows for analyzing changes over time and is essential for monitoring distributed systems effectively.
In the context of knowledge graphs, temporal data is particularly important as it allows Calmo to represent the evolution of entities and their relationships. By using these ever-evolving temporal relationships, Calmo can provide a more complete picture of system behavior, spot trends, patterns, and anomalies that would otherwise go unnoticed. This temporal awareness is key to proactive site reliability engineering, allowing for timely interventions, improved system resilience, and the prevention of cascading failures.
How Calmo Builds and Uses Knowledge Graphs
Calmo's knowledge graph has 3 interconnected layers that improves incident detection and response.