When you’re heads-down in your own area of expertise, it’s easy to forget that what’s obvious to you might not be to others. As you might have seen in previous posts, I learned that for me using pen and paper from time to time helps uncover unknown knowns in my head. Last time, it was why the three pillars need to go. This time, it’s context propagation, and its surprising relationship to metrics. ...
I just read another post introducing traces, metrics, and logs using that analogy, which reminded me to re-share that excellent piece by Ted Young on The New Stack from a few years ago: Modern Observability Is a Single Braid of Data Ted argued the pillars are no longer load‑bearing and suggests a better framing: the “Single Braid of Data”. So let’s wheel the pillars into the museum, rope off the exhibit, and hang a small plaque: “Historic framing.” As we do with once‑cherished pillars that are no longer load‑bearing. ...
Most developers use automatic instrumentation without knowing how it actually works. This post breaks down the key techniques behind it—not to build your own, but to understand what’s really happening when things “just work.” Read the full articles on: Causely Blog, OpenTelemetry Blog
I have a confession to make: I struggled for a long time with the statement: “Observability helps you uncover unknown unknowns.” It never quite sat right with me. If you can uncover an “unknown unknown” using Observability, wasn’t it always, in some sense, a known unknown? Or perhaps even an unknown known you just hadn’t noticed? That logical loop kept bothering me. Recently, I realized where my understanding failed, and thought this might be worth sharing: ...