The Bandwidth of the Postcard: Why Less Telemetry Can Mean More Insight

We’ve all seen the archeological digs. A production incident occurs, and the first command barked into the chat is “logs!”. A frantic search begins, sifting through terabytes of granular data—every API call timestamped, every database query traced, every container heartbeat logged. Our dashboards are glorious, high-resolution maps of our systems, capable of zooming in to the millisecond. We log everything, we tell ourselves, because we never know what we might need. But in our quest for absolute visibility, we may have engineered a new form of blindness.

The common advice is a relentless pursuit of more: more metrics, more events, more data points. The promise is that with enough instrumentation, we can reconstruct any event, diagnose any failure. The unstated assumption is that data is inherently good and that more data is inherently better. But anyone who has spent three hours staring at a sprawling Kibana dashboard, trying to discern a signal in a cacophony of system noise, knows this isn’t entirely true. The sheer volume becomes a cognitive tax. It’s like trying to understand the plot of a novel by reading every single word in the dictionary.

There is a counterintuitive power in deliberate limitation. Consider the constraint of a postcard: a tiny, physical space. Every word you write must earn its place. This constraint forces clarity, forcing you to distill your message to its absolute essence. You don’t write about the mediocre hotel coffee; you write about the stunning sunset over the sea. The limitation creates the signal.

What if we applied the "postcard" principle to our systems? Instead of logging every conceivable event, what if we were forced to define, in advance, the ten most critical signals of our application’s health? This isn’t about reducing log levels from DEBUG to INFO. It’s a more fundamental exercise. It forces us to ask: What does "working" actually look like? What are the two or three user-facing transactions that, if they fail, constitute a true outage? What single metric best indicates impending resource exhaustion? By ruthlessly limiting our telemetry, we are forced to think deeply about what truly matters.

The result isn’t a data-poor environment; it’s an insight-rich one. When an alert fires from this curated set, it carries immense weight. There is no ambiguity. The signal hasn’t been diluted by ten thousand other insignificant events. Your pager doesn’t cry wolf. Your dashboards cease to be overwhelming mosaics and become instead a series of stark, clear indicators. The cognitive load on the on-call engineer plummets because the system, by design, speaks with clarity rather than verbosity.

This philosophy extends beyond logging to metrics and alerts. It champions the idea that the most reliable system might not be the one with the most data, but the one whose data is so deliberately chosen that its silence is meaningful and its alarms are unequivocal. It’s an argument for building systems that are not just observable, but intelligible. In an age of infinite storage and streams, sometimes the most profound insight comes from choosing to send a postcard instead of shipping the entire library.

Notes & further reading

A few pages I came back to while writing this: