Positional Paper: Schema-First Application Telemetry
Yuri Shkuro, Benjamin Renard, Atul Singh

TL;DR
This paper advocates a schema-first approach to application telemetry at Meta, enabling semantic understanding of telemetry data to improve observability, validation, correlation, and privacy enforcement.
Contribution
It introduces a schema-first methodology for telemetry data at Meta, capturing metadata from the start to enhance observability platform capabilities.
Findings
Enables compile-time validation of telemetry data
Supports multi-signal correlation and cross-filtering
Facilitates privacy rules enforcement
Abstract
Application telemetry refers to measurements taken from software systems to assess their performance, availability, correctness, efficiency, and other aspects useful to operators, as well as to troubleshoot them when they behave abnormally. Many modern observability platforms support dimensional models of telemetry signals where the measurements are accompanied by additional dimensions used to identify either the resources described by the telemetry or the business-specific attributes of the activities (e.g., a customer identifier). However, most of these platforms lack any semantic understanding of the data, by not capturing any metadata about telemetry, from simple aspects such as units of measure or data types (treating all dimensions as strings) to more complex concepts such as purpose policies. This limits the ability of the platforms to provide a rich user experience, especially…
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