KT Intake

Capture incident context, sync updates, and export crisp summaries without leaving the bridge.

Problem Summary

Evidence & Affected Object

Detection Source
Evidence Collected
Examples: alerts, error messages, metric spikes/drops, log lines, screenshots, reproducible steps.
Hardware name and model, Function/Module/Method, Container/Service/API, datastore/volume/bucket/table, network element, identity/policy/role, pipeline/job.

Baseline vs Current Behavior

What was the expected behavior?
What have you measured or verified against the baseline (using the same metrics as above), and what symptoms are you observing now?

Describe The Problem

Impact

Current Impact

Who or what is currently affected? Quantify: users/tenants/regions, transactions failing, SLI/SLO deltas (avail %, p95/p99, error %), data at risk (loss/corruption/exposure), workarounds.

Future Impact

If unresolved, what is the likely future impact? Blast radius growth, SLO/SLA breach, revenue/penalties, compliance, backlog/consumer lag, churn, on-call fatigue.

Timeframe

When will the Future Impact become Current Impact? (Best Estimate). What deadlines/SLAs do we need to be aware of?
Current Service Recovery Stage

Problem Analysis

KT Question IS — facts only IS NOT — similar & reasonable and could be but is not occuring Distinctions — Unique characteristics about the IS Changes — Changes that happened in on around or about each Distinction

Possible Causes

Capture hypotheses and pressure test them against the KT IS / IS NOT evidence. Start with the suspect, accusation, and impact; then walk each cause through the table.