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Reliability · Version 1.2.0 · Reviewed 2026-08-02

SLO & Error Budget Designer

Reduce production risk in SLI definition and target selection with evidence, explicit trade-offs, and a verification plan.

4 method steps 6 documented failure modes 5 diagnostic checks 7 quality gates

Defines SLIs that reflect user experience, sets defensible targets, and turns error budgets into an enforceable release policy.

₹149 one-time

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What this skill helps you do

  • SLI definition
  • Target selection
  • Budget policy design

How SLO & Error Budget Designer works

You provide

User journeys, current performance, and stakeholder targets

It inspects

Good events over valid events, both explicitly defined

It decides

Targets plus the budget policy agreed before it is needed

You verify

Replay historical data and confirm the SLI tracks pain

What it checks first

SLO & Error Budget Designer defines SLIs that reflect user experience, sets defensible targets, and turns error budgets into an enforceable release policy. Use it when the work involves SLI definition, Target selection, Budget policy design.

  1. Whether the SLI is defined as a ratio of good events to valid events, with both terms written down.
  2. Whether the measurement point reflects user experience or internal component health.
  3. Historical performance, since a target set without it is either trivially met or immediately violated.
  4. Whether the budget policy was agreed before it was needed, which determines if it will be honored.
  5. How valid events are counted, because excluding the wrong failures inflates the number.

Failure modes it recognizes

  • Availability measured at the load balancer, so an application returning errors with HTTP 200 looks healthy.
  • A target set at 99.99 percent without the architecture or budget to support it, so it is quietly ignored.
  • Aggregating across regions or tenants, hiding a total outage for a subset of users.
  • Excluding client errors that are actually caused by a server-side contract change.
  • A burn-rate alert that only fires after the budget is already exhausted.
  • Multiple teams measuring "availability" differently, making the numbers non-comparable.

Answers it will reject

  • Setting the target to 100 percent, which removes the ability to ship anything.
  • Choosing a target by benchmarking competitors rather than by user tolerance and cost.
  • Treating the SLO as a performance review metric, which reliably corrupts the measurement.
  • Defining an SLO with no agreed consequence when the budget is spent.

Decision rules it applies

  • Write the SLI as good events over valid events and define both terms explicitly before choosing a target.
  • Derive the target from observed performance and user tolerance, not from a round number.
  • Agree the budget policy — what stops when the budget is spent — before the first violation.
  • Measure as close to the user as possible; component health is diagnosis, not an SLI.

Evidence it asks for

  • Replay historical data against the candidate SLI and confirm it moves when users were actually harmed.
  • Alert on burn rate over multiple windows so both fast and slow burns are caught.
  • Report budget consumption per release so the cost of change is visible.

The method inside

  1. Turn SLI definition into explicit functional requirements and quality-attribute constraints.
  2. Model the critical path, state, trust, and failure boundaries that govern target selection.
  3. Compare viable designs for budget policy design against weighted constraints and operational ownership.
  4. Select a design with consequences, rollout stages, observability, and a reversible adoption path.

Deliverables

  • SLI definition assessment
  • Target selection decision and action plan
  • Budget policy design verification checklist

Evidence requirements

  • User-visible symptoms and SLO impact
  • Timeline, telemetry, deploys, and dependency state
  • Current mitigations and operational constraints

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

We want to set SLOs for our API but nobody agrees on what number to pick or what happens when we miss it.

Expected output

The disagreement is usually about the SLI, not the target. Define it as a ratio of good events to valid events with both terms written down, because "availability" without that definition lets every team measure something different. Then set the target from observed performance and agree the budget policy before you need it...

Boundaries and compatibility

Ideal for

  • SLI definition: produce a decision or artifact grounded in supplied evidence.
  • Target selection: produce a decision or artifact grounded in supplied evidence.
  • Budget policy design: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Replacing incident command authority
  • Calling a trigger the root cause without a causal chain

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.