Incident timeline calculator
Calculate response intervals with UTC-normalized timestamps and a range for uncertain onset.
- Bring
- Incident timestamps and evidence
- Get
- Response intervals with unknowns and recovery evidence
The working toolkit
Turn incident records, service measurements and planning assumptions into results you can explain. Start with an example, then make it your own.
15 tools
Reconstruct what happened, compare detection times and communicate clearly.
Calculate response intervals with UTC-normalized timestamps and a range for uncertain onset.
Compare mean, median and range while keeping missing and excluded incidents visible.
Turn confirmed impact, response actions and the next checkpoint into a clear status update.
Build usable procedures and verify the corrective work.
Create a service procedure with escalation, bounded mitigation and recovery checks.
Follow a corrective action from delivery to its verification test and remaining risk.
Inspect latency, error budgets, page volume and the effects of retries.
Calculate the failure allowance and remaining budget in event counts or minutes.
Compare two windows of error rates with the SLO and your chosen burn threshold.
Measure page volume, classification coverage and estimated responder effort without hiding unreviewed alerts.
See the slow tail behind an average with percentiles, threshold counts and a latency distribution.
Inspect retry delays, timeout bounds and the extra calls a failure can create before setting a retry policy.
Size a service for failure, plan on-call coverage and estimate time recovered by automation.
Estimate rotation load and available coverage when people take leave or are not yet ready for on-call.
Estimate recurring work, net time recovered and the effort payback period for an automation.
Check whether measured capacity can absorb forecast demand when instances are unavailable.
Estimate token costs and examine the mistakes in an AI decision.
Model token spend across calls, retries and caching using the rates you supply.
Compare a binary AI decision with reviewed outcomes and see which mistakes an accuracy score can hide.
Connect the steps
01 / 3 steps
Reconstruct the response, review corrective actions and update the runbook.
Open workflow: Review an incident02 / 3 steps
Draft a runbook, work through an example and record the gaps to resolve.
Open workflow: Prepare an incident response03 / 3 steps
Calculate the allowance, inspect burn rate and connect the result to your release policy.
Open workflow: Review a reliability budgetExplore synthetic cases that show what incident records and measurements can establish.
Measurement completeness labIncident decision-log replay kitMarkdown download
A Markdown procedure with fields for diagnosis, mitigation, escalation and recovery checks.
View instructions & downloads: Incident runbook templatePython + JSON download
A small Python example that returns pass, fail or unknown from observations gathered separately from the agent being evaluated.
View instructions & downloads: Incident-agent recovery graderOnline guide
Calculations, service-level objective fields, and release-policy examples to adapt with your team.
View instructions: Error-budget worksheet and examplesOnline code guide
Logging configuration that preserves operational evidence and failure exit status.
View instructions: Python logging exampleInteractive lab + Python and CSV
Compare confirmed success, no eligible traffic and missing outcomes using six reproducible synthetic cohorts.
View instructions & downloads: Measurement completeness labInteractive lab + Python and JSON
Replay ten synthetic records that separate proposal, authorization, execution and verified service outcomes.
View instructions & downloads: Incident decision-log replay kit