Find out before your customers do.
Logs, metrics, traces, and alerts wired into Datadog, Honeycomb, or Sentry — with the discipline to define SLOs and alert on what your users actually feel, not on noise. The kind of setup where a problem reaches your on-call before it reaches your inbox.
Right now, your best monitoring tool is an angry customer.
When the support inbox is the first place an outage shows up, you don't have monitoring — you have a delay between failure and finding out, paid for in trust. Most teams have the opposite problem at the same time: a wall of alerts that page someone every night for a CPU spike that means nothing, until everyone learns to ignore them. The fix isn't more graphs. It's measuring what your users actually feel, setting a clear bar for "good enough," and only ringing the phone when that bar is crossed for real. Logs, metrics, traces, and alerts, wired with the discipline to make them worth trusting.
You shouldn't hear about downtime from a customer.
Each familiar symptom has the same answer — measure what matters, alert on what hurts.
- 01
You learn about outages from customers
Symptom-based alerts on the signals users feel — so you hear it first, not last.
- 02
Alerts wake people up for non-issues
Pages tied to SLOs, not to CPU spikes — every alert actionable and real.
- 03
There's no SLO conversation happening
Clear targets and error budgets that decide what's worth paging on.
- 04
Nobody can find where the time went
Distributed traces that pinpoint the slow call across every service.
- 05
On-call is dreaded and chaotic
A sane rotation, the right team paged, and a runbook for the first move.
Everything it takes to hear it first.
With Datadog, Honeycomb, or Sentry — chosen for your stack and budget, not for a logo.
Logs, metrics & traces
All three wired in via OpenTelemetry — catch it, locate it, explain it.
SLOs & error budgets
Targets for what users feel, and a budget that decides what's worth a page.
Alert routing & on-call
Symptom-based alerts to the team that owns the service, with sane rotation.
Dashboards by team
A small set of views per service — the numbers each team actually owns.
Incident runbooks
The first moves written down, so 2am responses aren't invented from scratch.
Postmortems that stick
Blameless reviews that make each incident make the next one shorter.
From signal to resolution, the same way every time.
- Collect01
- Trace02
- Alert03
- Triage04
- Resolve05
Every signal follows the same path — telemetry collected from your services, traced across the request, alerted on when it crosses an SLO, triaged by the team that owns it, and resolved with a runbook and a postmortem so the next one is faster.
Logs, metrics, and traces — not one of the three.
Metrics tell you something is wrong and how much. Traces tell you where the time or the failure went, across every service a request touched. Logs explain what actually happened. We wire up all three through OpenTelemetry, so the data isn't locked to one vendor and 'the app is slow' becomes 'this database call in this endpoint is the problem.'
- Metrics to catch it, traces to locate it, logs to explain it
- Instrumented with OpenTelemetry, not vendor lock-in
- High-cardinality tracing for the weird 1%
- Sensible sampling and retention to keep cost sane
A clear bar for "good enough."
Without an SLO, every incident becomes an argument about whether it's bad enough to act on. We define targets from the user's side — say, 99.9% of checkout requests succeed under 800ms — and an error budget for the rest. The budget tells you when to stop shipping features and fix reliability, and when you have room to take risks. It ends the guesswork about what's worth a page.
- Targets measured from the user's experience
- Error budgets that drive real decisions
- The end of 'is this bad enough to page someone?'
- Reliability and feature work, balanced honestly
Alert on symptoms, not on noise.
Alert fatigue comes from paging on causes — CPU at 80%, a pod restarting — none of which mean a user is hurting. We switch to alerting on symptoms tied to your SLOs: is the thing slow, broken, or erroring for real people right now? Everything else becomes a dashboard or a ticket. Every page is actionable and urgent, routed to the team that owns the service.
- Pages tied to user-impacting symptoms
- Causes become dashboards, not 3am calls
- Routed to the owning team, not everyone
- Every alert actionable — or it doesn't ring
On-call that people don't dread.
A sane rotation with primary and backup, hand-offs that don't land mid-incident, and escalation if the first responder doesn't ack — set up in PagerDuty, Opsgenie, or your tool of choice. The real fix for burnout, though, is the quiet: when pages are rare and always real, being on-call stops being something people avoid.
- Primary, backup, and clean hand-offs
- Escalation that has the responder's back
- Runbooks for the common first moves
- Blameless postmortems that shorten the next one
Real monitoring, built deliberately.
Map what hurts
We review your services, the outages you've had, and where you currently find out things broke — usually too late.
Instrument the stack
Logs, metrics, and traces wired in through OpenTelemetry, into Datadog, Honeycomb, or Sentry as fits your stack.
Define SLOs
Targets measured from the user's side, with error budgets that decide what's worth paging on and what isn't.
Wire alerts & on-call
Symptom-based alerts routed to the owning team, with a sane rotation and escalation in your paging tool.
Dashboards & runbooks
Per-team views, incident runbooks, and a postmortem habit your team can own without us on call.
The first sign of trouble shouldn't be an angry email.
You learn about outages from customers
The support inbox is the first place a failure shows up, paid for in the time between breaking and finding out.
Alerts wake people up for non-issues
The phone rings for a CPU spike that means nothing, until everyone has quietly learned to ignore it.
There's no SLO conversation happening
Nobody has agreed what 'good enough' means, so every incident becomes an argument about whether to act.
Proven observability tools, used with restraint.
The things teams ask first.
Hear it from a dashboard, not a customer.
Tell us where outages hurt most and how you find out today. We'll wire in logs, metrics, and traces, define SLOs that matter, and set up alerting and on-call that ring only when a real user is hurting — so failures find you, not your customers.