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Reliability Metrics

Availability

Availability is the share of time a service was able to fulfill its intended function.

What is availability?

Availability describes the share of time a service was able to fulfill its intended function. In reliability work, the label is useful only when it maps to a measurable check, a clear owner, and a next action when expectations break. Without that operational meaning, the phrase becomes decoration in dashboards and status updates.

Why it matters

Availability matters because teams need a precise shared meaning for the share of time a service was able to fulfill its intended function. Vague language turns incidents into arguments about words instead of fixes.

When everyone uses the same definition, alerts, status updates, and post-incident reviews stay aligned.

How it works

In practice, the share of time a service was able to fulfill its intended function shows up as a concrete signal you can measure or communicate. Operators define what good looks like, watch for deviations, and record what happened when expectations break.

The useful version of availability is operational: it changes who gets notified, what customers see, or which metric a team reviews after an incident.

Practical example

Imagine a team operating around 99.9% availability target for checkout. When observed behavior stops matching the definition of availability, the team treats that change as a reliability event with a clear owner and next step.

Common misconception

Availability always equals uptime percentage from one probe

That reading usually collapses distinct ideas into one slogan. Keep availability tied to observable behavior so the definition stays useful under pressure.

How Fajita handles this

Availability definitions vary. Write yours down before arguing about decimals.

Related documentation

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