Measuring the time spent between two points in a request’s lifecycle in a distributed system sounds simple enough, right? You just log the start and

Understanding Timings in Distributed Systems

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2024-11-18 18:00:05

Measuring the time spent between two points in a request’s lifecycle in a distributed system sounds simple enough, right? You just log the start and end times, look at a chart, and voilà, problem solved. But when a customer raises an issue about a specific delay, and you dive into your logs, charts, and metrics to diagnose it, you quickly realize that connecting the dots across disparate systems is anything but easy. Despite advanced tooling, observability graphs, dashboards, and well-structured logging, achieving a full picture of system behavior can still be challenging.

This problem recently became apparent for my team when a high-MRR customer reported delays in receiving specific SMS messages on their test numbers. Investigating these specific messages meant diving into our various observability tools to see if we could pinpoint the timing.

Each one of these tools are useful but have inherent limitations when it comes to providing a coherent picture of holistic execution.

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