Trace without traces
The trace was sampled out. I found the bug anyway — by filtering recorded traffic on the customer's email instead of a trace ID. Here's how to follow one request across four services with no trace IDs and no OpenTelemetry.
Posts about observability
Browse 24 posts in this category
The Three Pillars Were Built for Humans
Metrics, logs, and traces were built for humans and cheap storage. AI inverts both assumptions, and the next maturity level is a deterministic replay sandbox.
Five things your logs will never tell you
Logs, metrics, and traces are a lossy compression of production. Five things you can do with a traffic data lake that observability can't.
Logs told me something broke. Traffic showed me what.
Capture production traffic and store it in your own Elasticsearch with Speedscale BYOC. Pull it locally with es-gather.py and reproduce bugs with proxymock.
The Kubeshark Workflow That Doesn't Stop at the Dashboard
A Kubeshark alternative that goes beyond observability. Stream live cluster traffic into proxymock, then replay or mock it locally from your laptop.
Replay Real Customer API Sessions as Datadog Synthetics Tests
Export recorded proxymock traffic to Datadog Synthetics in one command. Auth headers redacted, global variables created. No scripting, no flaky journeys.
Replace API Synthetics with Traffic Replay
UI synthetics only tell you something is broken. Traffic replay per microservice isolates failures before any human walks up. Zero scripts required.
OpenTelemetry Trace Testing for CI Release Gates
Trace-based testing uses OpenTelemetry traces as replayable test input so CI catches production regressions before deploy, not after incident review.
When Your Observability Literally Stops Traffic
Observability tells you what failed—but not how to recreate it. Why reproducibility is the missing fourth pillar, and what that means for incident response.