Operations | Monitoring | ITSM | DevOps | Cloud

How to Trace Microservices WITHOUT OpenTelemetry

Learn how to trace complex multi-hop transactions across microservices when OpenTelemetry isn't available or trace parents get lost. This quick tutorial demonstrates how to use full-text search in proxymock (a free CLI and UI tool) to isolate user journeys (like looking up a specific username) and instantly generate waterfall tracing views. Whether you are working locally or in a Kubernetes cluster, you can record API traffic, visualize multi-hop requests, and easily transition those captures into load or regression tests.

The API tests passed. The database didn't.

We shipped v2 of a small products API on a Thursday. Green CI. Green replay. The new search endpoint worked. I went home feeling competent. Friday morning I ran the same traffic against both builds with proxymock and compared the SQL. v2 had added 80 queries on the same HTTP script. A per-product audit COUNT was firing inside the list handler. A startup migration had run ALTER TABLE and CREATE TABLE audit_log. Total DB time was up 70 ms on a demo that should have been boring.

Trace without traces

A customer emailed on a Tuesday: checkout hung for ten seconds. I opened our tracing tool, punched in the time window, and got nothing. The trace was sampled out. We keep 1% of traces, like most shops with real traffic do. The one request that actually mattered was in the 99% we threw away. I spent twenty minutes admiring our observability stack before admitting it couldn’t answer a first-grader’s question: what happened to this person? Here’s what I know now.

AI Agents Write Broken Code 49% of the Time #speedscale #AI #Coding #Tech #DevOps

AI agents write broken code nearly 50% of the time. By adding a traffic-based deterministic evaluation, Speedscale boosted unsupervised bug-fixing quality from 51% to 77% in just 5 minutes. This helped slash token costs and eliminate rework without human intervention. Learn more: speedscale.com.

The Three Pillars Were Built for Humans

It was 2am and I was paying for the privilege. Something was on fire in production, and I’d done the modern thing: I pointed an AI agent at it. It ingested the dashboards. It read the logs. It walked the traces. Then it handed me back a beautifully formatted paragraph that said, in effect, “latency is elevated on the checkout path.” I knew that. The page told me that.