runbook

DE//AGENT currently lists 4 resources under runbook: 4 tutorials. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Read a failing expectation precisely — column, rule, value — via Respond to a failing quality expectation
• Quantify a failure — how many rows and which ones — via Respond to a failing quality expectation
• Decide block vs quarantine vs pass-with-warning on evidence — via Respond to a failing quality expectation
• Diff shuffle write and input bytes run-over-run — via Attribute a 4x Spark cost regression
• Attribute a cost regression to one stage — via Attribute a 4x Spark cost regression
• Gate deploys on shuffle/scan metrics — via Attribute a 4x Spark cost regression
• Confirm a query regression from symptoms and query history — via Incident — the dashboard query that went slow
• Collect the evidence packet — query_id, partitions ratio, bytes, queue split — via Incident — the dashboard query that went slow

4 more objectives live on the individual resource pages.

These resources map to stages: Data Quality (1), Reliability (1), Warehousing (1), Cloud (1). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. Respond to a failing quality expectation score 34.15 — beginner
2. Attribute a 4x Spark cost regression score 34.15 — intermediate
3. Incident — the dashboard query that went slow score 34.15 — intermediate

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Respond to a failing quality expectation.

• Respond to a failing quality expectation — A quality expectation failed in production and bad data may be reaching consumers. Follow the data-quality-failure runbook: read the failure precisely, quantify it, then make the o… details
• Attribute a 4x Spark cost regression — One job's compute cost quadrupled overnight with no functional change. Run the 4x runbook: diff shuffle and input bytes run-over-run, find the guilty stage, reverse the regression … details
• Incident — the dashboard query that went slow — Run the slow-query runbook as an incident: confirm the regression, split scan cost from compute contention, pull partitions_scanned and bytes from query history as evidence, apply … details
• Incident — the job that quadrupled in cost overnight — An invoice alert or a cost-per-run dashboard spike lands: one job's compute cost quadrupled with no functional change. Work the runbook — diff shuffle write and input bytes run-ove… details

Adjacent topics: tutorial (4 shared), incident (3 shared), cost (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.