Find out before
your customers do.

Monitoring answers questions you predicted: is the server up, is latency under 300ms. Observability lets you answer questions you never predicted, why is checkout slow for Dutch users on mobile since Tuesday, because structured logs, metrics and traces let you interrogate the system after the fact. You need both: monitoring to page you, observability to make the incident short.

By deleting alerts, not adding them. We rebuild the pager around symptoms customers feel, SLO burn-rate alerts and synthetic-check failures, and demote cause-level alerts (CPU, disk, restarts) to dashboards and review queues. Every page that survives gets a runbook and an owner, and a monthly noise review deletes anything that fired without causing action. Clients typically see alert volume drop by around 90% while catching more real incidents.

Start with two or three, on the flows that make money: availability and latency of checkout or login, and freshness of your most important data sync. Pick targets from what the system actually did over the last month rather than aspirational nines, you can tighten later. We define them with you in a working session, then wire burn-rate alerts against the error budget so the SLO is enforced, not decorative.

Self-hosted Grafana, Prometheus and Elasticsearch on AWS typically runs a few hundred dollars a month in infrastructure for a mid-sized stack, versus SaaS platforms like Datadog, where per-host and per-GB pricing routinely surprises teams with five-figure monthly bills as they grow. We default to the open-source stack because you own it and the cost curve stays flat, but if a SaaS tool genuinely fits your team better, we will say so, we sell engineering, not licenses.

Two mechanisms. Synthetic probes run your real flows, checkout, login, CRM sync, end to end from outside your network every few minutes, so a broken payment key or expired OAuth token is caught even when every server is green. Business counters watch metrics like orders per hour against a learned baseline, so revenue dropping to zero is a page in its own right. Both alert on what customers and the P&L actually feel.

Your choice. Most clients keep on-call in-house, we design the rotation, escalation paths and runbooks so a page is answerable by whoever holds the pager. If you don't have the coverage, our managed monitoring under a written SLA takes first response and escalates to your team only when a decision needs an owner. Many start managed and take it in-house once the runbooks have proven themselves.

The observability audit takes about a week. First signals, golden-signal dashboards and synthetic checks on your top two flows, typically ship within two weeks of kickoff. A full build: instrumentation across services, SLOs, alert redesign, game day and on-call wiring, usually runs five to eight weeks depending on service count. You get a real timeline after the audit, not a guess.

Not measurably, done right. Prometheus scrapes are pull-based and cheap, structured logging costs microseconds per request, and traces are sampled, you keep every error trace but only a slice of healthy traffic. We benchmark before and after instrumentation on your own stack and show you the overhead numbers, which are usually lost in normal variance.