Observability & alerting
Know your product is up — and why it isn't — before customers tell you: structured logs, metrics, alerts, uptime checks, crash reporting, and runbooks.
What we build
The difference between finding out from a dashboard and finding out from an angry customer. We instrument your product with structured, correlated logs; wire metrics and alerts to the events that actually matter — failed payments, error spikes, crashes, webhook failures, unusual spend; add uptime checks on the endpoints customers touch; and write runbooks so whoever receives an alert knows exactly what to do. Covers mobile too: crash reporting with readable stack traces. Choose this for a product already running (or about to launch) that currently fails silently; every build we deliver includes a baseline of it by default.
What you get
- Structured logs with a request ID traceable across services
- An alert policy per event on the agreed alert list, each fired once in test
- Uptime checks on the customer-facing endpoints, alerting to the agreed channel
- A runbook per alert that can fire
How the work unfolds
- Instrument structured logging with request correlation
- Build metrics and alert policies on the events that matter
- Add uptime checks on customer-facing endpoints
- Set up crash reporting with symbolicated stack traces
- Track spend including AI token costs
- Write runbooks for every alert that can fire
What shapes the price
Before you see a number, our scoping conversation asks:
- Is a mobile app in scope, as well as the web and backend? Crash reporting with symbolicated traces only applies to native apps.
- Should running costs — including AI token spend — be tracked with alerts from day one? Spend tracking is a day; products with AI usage usually want it.
How an engagement starts
Teams often combine it with: