Observability, taken from zero to one.
Zero-to-one observability for startups — instrumentation, tracing, metrics and logs wired through the stack, with dashboards, SLOs and an on-call setup your team can actually use.
What you get
- Instrumentation through the stack — traces, metrics and structured logs correlated by request
- A small set of dashboards that answer the questions you actually ask
- SLOs and error budgets agreed with the team, not imposed
- Alerts that page a person only when a user is affected
- An incident response runbook and an on-call rota that has been rehearsed
- A cost model for the telemetry pipeline, so observability does not become the next surprise bill
Most startups have some logs, a couple of dashboards someone made once, and alerts that either page constantly or never fire. When something breaks, the investigation is archaeology.
We take observability from zero to one: instrumentation wired through the stack, a handful of dashboards that answer real questions, SLOs the team agrees to, and alerts that only wake someone when a user is affected — plus the incident process and on-call setup to go with it, and a cost model so the telemetry pipeline doesn't become the next surprise.
What we help with.
Instrumentation
OpenTelemetry through the services that matter — traces, metrics and structured logs, correlated so one request tells one story.
Tracing and root-cause
Distributed tracing set up so a slow request or an error can be followed across services instead of guessed at from logs.
Metrics and dashboards
A small, deliberate set of dashboards — the golden signals, the business events that matter — rather than a wall of graphs nobody reads.
SLOs and error budgets
Service level objectives agreed with the team, with error budgets that make the trade-off between shipping and stability explicit.
Alerting and on-call
Alerts tied to user impact, routed to a rota that has been rehearsed, with runbooks linked from the alert itself.
Incident response
A lightweight incident process — roles, comms, a template — and blameless reviews that produce fixes rather than blame.
Telemetry cost control
Sampling, retention and cardinality managed against a budget, so the observability bill stays proportional to the value it returns.
The terms every engagement runs on.
One team, start to finish
One team owns your system from architecture to on-call. There is no handover wall to throw requirements over.
Evidence before launch
AI features get an evaluation set before they get a launch date. If we cannot measure it, we say so.
Built to be handed over
Documentation and knowledge transfer are contract terms, not favours. You should be able to leave us at any point.
Senior engineers, not a bench
The people who scope your engagement are the ones who build and run it, never handed off to someone you haven't met.
Related reading.
Questions about observability.
We already have logs and a few dashboards. What is missing?
Usually correlation and intent. Traces, metrics and logs that tell one story per request, a small set of dashboards built around the questions you actually ask, and alerts tied to user impact rather than raw thresholds.
Do you use a specific vendor, or our own stack?
We instrument with OpenTelemetry so the data is portable, then wire it to whatever backend fits your budget and team — a managed vendor or a self-hosted stack. The instrumentation does not change if you switch later.
How do you stop alerts from becoming noise?
Alerts are tied to SLOs and user impact, not to every metric that moves. Each one links to a runbook, and anything that pages without being actionable gets removed rather than muted.
What are SLOs and do we need them this early?
Service level objectives are the targets you hold yourselves to — availability, latency — with an error budget that makes the trade-off between shipping fast and staying stable explicit. A small startup needs one or two, agreed with the team, not a spreadsheet of them.
Will the observability bill get out of hand?
That is a design constraint from the start: sampling, retention and metric cardinality are managed against a budget, so the telemetry pipeline stays proportional to the value it returns.