Observability & Reliability Engineering | OpenTelemetry, SLOs, Incident Response

How you know you need this

An incident starts with twenty minutes of deciding which service is at fault.
The alert that fires is never the one that matters, so everyone has muted the channel.
A customer reports a problem before your monitoring does.
Logs exist, in four places, in three formats, with no shared request identifier.
You know the system is slow but not which hop is slow.
The same incident happens twice because nobody wrote down what fixed it.

What we build

Tracing across the whole request

OpenTelemetry instrumentation propagating context through services, queues and workers, so a slow request has a waterfall instead of a theory.

Logs, metrics and traces that connect

One correlation identifier across all three, so a log line leads to its trace and a metric spike leads to the requests behind it.

SLOs that reflect the product

Objectives based on what users notice, with error budgets that inform release decisions instead of decorating a dashboard.

Alerts worth waking up for

Alerting on symptoms rather than causes, tuned so that a page means action is required. Fewer, better alerts beat comprehensive noise.

Runbooks and incident practice

Written procedures for the failures you can predict, a post-incident process that produces changes rather than blame, and rehearsals before the real thing.

Typical projects

Instrument a system that has none

Add tracing to the critical paths first, unify log formats, and get to the point where one request can be followed end to end.

Fix alert fatigue

Audit every alert, delete the ones nobody acts on, rewrite the rest around user-visible symptoms, and set escalation that matches severity.

Define the first SLOs

Pick the handful of indicators that reflect the product experience, set achievable targets, and connect them to release decisions.

Diagnose a latency problem nobody can locate

Instrument the suspect paths, profile the hot spots, and produce a ranked list of where the time actually goes.

Build the incident process

On-call rotation, severity levels, communication templates and post-incident reviews that end in tracked work.

What you get

Instrumented services emitting correlated logs, metrics and traces
Dashboards for the questions asked during an incident, not a wall of graphs
An alert set small enough that every alert is trusted
Written SLOs with error budgets and what happens when they are spent
Runbooks and a post-incident template your team will actually use

Questions we get asked

Which observability vendor do you use?

Whatever you already pay for, in most cases. We instrument with OpenTelemetry, which is vendor-neutral, so the data can go to Datadog, Grafana, Prometheus or a replacement later without re-instrumenting everything. Locking telemetry to one vendor's SDK is a decision people regret at renewal time.

Is this worth it before we have scale?

The cheapest time to instrument is before you need it, and the most expensive time is during an outage. That said, this is proportional work: a small system needs tracing on its critical path and a handful of alerts, not an observability programme.

Can you help during an active incident?

We can help stabilise and then fix the underlying cause, but understand that arriving mid-incident with no context is the worst case for everyone. The value of this work is that it exists beforehand.

Stop debugging production by guessing