How Observe Uses...Observe! [Part II]

O2, a next-in-class observability product, has enabled the discovery and resolution of unforeseen issues by ingesting and analyzing a wide range of data types, including usage data, UI event data, and backend traces. Datasets, created from raw event data, allow users to ask questions about specific entities like Pods or Servers, while Worksheets provide a platform for data transformation and visualization. Monitors alert users to specific conditions within Datasets, enhancing proactive troubleshooting. The platform's robust telemetry capabilities are leveraged by various roles, particularly product managers and the pricing team, to extract insights, plot trends, and refine usage-based pricing models. Detailed UI event data, collected via a custom JavaScript library, aids in diagnosing issues like the WSOD by sending alerts with stack traces to internal channels. The backend, built on a microservice architecture, uses custom tracing tools to model data for easier troubleshooting, especially for third-party services such as Snowflake and GraphQL. This comprehensive approach, including the integration of Snowflake usage data, allows for deep, statement-level analysis and problem-solving, offering extensive visibility from user interactions to backend processes. The forthcoming part III will explore linking multiple data sources for enhanced observability and share best practices for utilizing Observe effectively.

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