Metrics, logs, tracing, error budgets, and reliability engineering culture.
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A user schedules a payment for 9:00 AM. At 9:00, the scheduler finds the job and hands it to a worker. The worker calls the payment provider, the charge succeeds, and then the worker crashes before recording success. What should happen next?
The difficult part isn't sending an email. It's making sure a slow provider, a viral campaign, or a retry storm cannot take down the services that need to send one. Imagine an e-commerce platform just completed an order. The order…
In September a developer asked for a copy of the orders database from the previous Friday to... Tagged with sergeyshinder, observability, prometheus, backups. In September a developer asked for a copy of the orders database from the previous Friday to…
When an agent answers wrong, the first thing most of us open is the retrieval log. It returns a list of memory IDs that came back from the store. What it does not tell you is which of those survived…
If you create alarms manually in the console, you will eventually end up with these issues. You added servers but forgot to attach alarms You don't know who changed the thresholds, when, or why If you delete an alarm, you…
NestJS 12 dropped last week with ESM packages, Standard Schema validation, a rebuilt CLI, and a brand-new observability SDK. That last one is the most interesting part for anyone running NestJS in production with an APM tool. At Scout Monitoring, we…
Open Source Radar · 2026-10-19 · By Renchao Wu In one line: A local agent workspace that writes every model call, tool call and permission decision to an append-only log, with the desktop app, the terminal and the evaluator all reading that log.
Running Node.js applications inside Docker or Kubernetes introduces an important operational challenge: understanding memory pressure before a container runs out of memory. A Node.js application can appear healthy while its container is approaching its configured memory limit. And…
Most developers find out their closed test went wrong on day 15, when the production application asks questions they cannot answer, or the tester count turns out to have dipped below 12 somewhere in the middle. A daily log fixes both problems.
Add up the chairs in your Monday status meeting. Eight people, one hour, every week. That is a full working day, every week, spent reading out loud. The instinct is to blame the meeting. The meeting is not the problem.