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release-checklist

Audit database migration changes before a Bifrost release for lock contention, deadlocks, and delayed application startup. Receive pass, warning, or failure results, a release recommendation, and concrete remediation steps without modifying files.

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Pre-release safety audit for the Bifrost repo. Scans database migrations changed in a release for high-scale deadlock / lock-contention risks and for work that blocks application boot time, then produces a pass/warn/fail report with a concrete remediation plan. Invoked with /release-checklist [git-ref-range]. Built to grow - new checks are appended to the Checks Registry.

集成工具PostgreSQL
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适用场景

  • Review migration safety before a release
  • Check index creation risks on large log tables
  • Find migration work that delays application startup
  • Get remediation steps for a selected Git change range

包含的文件(1)

  • SKILL.md10.2 KB

SKILL.md(原文)

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Release Checklist

A pre-release safety audit. Given a set of changes destined for release, run every check in the Checks Registry below and produce one consolidated report. This skill is read-only: it diagnoses, recommends a concrete fix for every finding, and never edits files. Applying a fix is a separate, explicitly-approved step.

The registry currently holds two migration-safety checks. It is designed to grow - see Adding a New Check.

Scope: what "the release" means

Determine the change set to audit, in this order:

  1. If the user passed a git ref or range (e.g. /release-checklist v1.4.0..HEAD or /release-checklist origin/dev), use it.
  2. Otherwise default to everything not yet on the main branch: diff origin/dev...HEAD (three-dot) and also include uncommitted working-tree changes.
  3. If that range is empty, tell the user and ask for an explicit range.

Gather the raw material once, up front:

git fetch origin --quiet
git diff --stat origin/dev...HEAD
git diff origin/dev...HEAD -- '**/migrations.go' '**/matviews.go'
git status --porcelain

Migrations here are Go-defined, not .sql files. They live in:

  • framework/configstore/migrations.go - config DB (providers, keys, virtual keys, budgets)
  • framework/logstore/migrations.go - log DB (request logs; the high-volume table)
  • framework/logstore/matviews.go - materialized views over the log DB

A release with no diff in these files has no migration risk - record both migration checks as PASS (no migrations changed) and move on.

Migration system facts (needed by both checks)

  • All migrations run synchronously at boot. triggerMigrations() executes the full ordered migration list during store init, before the process serves traffic.
  • Supported databases: PostgreSQL and SQLite only. No MySQL. Lock behavior differs sharply between the two - judge both.
  • Migrations are cluster-serialized behind Postgres advisory lock 1000001 with a 5-minute acquisition timeout. A slow migration on one pod stalls every other pod's boot.
  • Each migration func runs in a transaction by default (Options.UseTransaction = true). A transaction holds every lock until the func returns - migration duration is lock duration.
  • Established escape hatch for heavy work: index builds and materialized views run in post-startup background goroutines under separate advisory locks (1000002 for indexes, 1000005/1000006 for matviews) - see framework/logstore/postgres.go, ensurePerformanceIndexes(), ensureMatViews(). migrationAddProviderHistogramIndex is intentionally a near-no-op that defers the real CREATE INDEX CONCURRENTLY there. This deferral pattern is the correct fix for anything heavy.

Checks Registry

Check 1 - Migrations that can deadlock or pile up under high-scale data

Goal: catch migrations whose locking is safe on a laptop but catastrophic on a production table with hundreds of millions of rows (notably the logstore request-log table).

For every added/modified migration func in the diff, flag:

SignalWhy it is dangerous at scale
CREATE INDEX without CONCURRENTLYSHARE lock for the whole build - all writes block for minutes/hours on a large table.
CREATE INDEX CONCURRENTLY with UseTransaction = truePostgres forbids CONCURRENTLY in a transaction - runtime error. Needs UseTransaction = false or the background path.
ALTER TABLE (add/drop column, add constraint, change type) on a hot tableTakes ACCESS EXCLUSIVE; queues behind in-flight queries, then every new query queues behind it - a cluster-wide stall.
ADD COLUMN with a volatile / non-constant DEFAULTRewrites the whole table under ACCESS EXCLUSIVE. A constant default is metadata-only and fine on PG11+.
ADD ... FOREIGN KEY / ADD CONSTRAINT validated immediatelyLocks both tables and scans the child. Prefer NOT VALID then a separate VALIDATE CONSTRAINT.
Bulk UPDATE/DELETE/backfill over the whole table in one transactionHolds row locks until commit; collides with live writes; bloats the table. Must be batched.
Order-dependent backfill, or migrations locking tables A-then-B vs B-then-AClassic deadlock: two transactions grab the same locks in opposite order.
SQLite drop-column path (CREATE TABLE ... AS SELECT + DROP + RENAME) on a large tableFull table copy under SQLite's single global write lock - blocks every writer.

Report per flag: func name, file:line, the exact signal, realistic production impact, and a concrete remedy (add CONCURRENTLY + UseTransaction = false, batch the backfill, defer to ensurePerformanceIndexes, add the FK as NOT VALID, etc.).

Severity: FAIL if writes to a high-volume table (logstore logs) can be blocked or a deadlock is plausible; WARN for config-DB tables (low row counts, but still flag).

Check 2 - Migrations that block boot-up time

Goal: because triggerMigrations() runs synchronously before the process serves traffic, any migration whose runtime grows with row count delays - or past the 5-minute advisory-lock timeout, breaks - every pod's startup.

Flag any added/modified migration whose cost scales with data volume:

SignalWhy it blocks boot
Any non-CONCURRENTLY CREATE INDEXBuild time scales with row count; runs inside boot.
CREATE INDEX CONCURRENTLY placed directly in triggerMigrationsEven concurrent builds take minutes/hours on big tables; belongs in the background goroutine path.
Table rewrite: volatile-default ADD COLUMN, type change, SQLite drop-column copyRewrites/copies every row during boot.
Data backfill loop / bulk UPDATE over an unbounded row setRuntime = O(rows); unbounded backfills have no ceiling.
matviews.go - creating or fully refreshing a matview in the synchronous pathMatview build scans the base table; must use the ensureMatViews() background path.
Anything that could realistically exceed the 5-minute advisory-lock timeoutOther pods fail to acquire lock 1000001 and crash-loop.

Expected safe pattern: heavy work is a near-no-op migration; the real build runs post-startup in a background goroutine. Compare each new heavy migration against migrationAddProviderHistogramIndex - if it does the heavy lifting inline, that is the finding.

Report per flag: func name, file:line, why runtime scales with data, risk at production row counts, and the remedy (move to the background path / batch it / make the default constant).

Severity: FAIL if the operation can plausibly exceed the 5-minute lock timeout on a production-sized table; WARN otherwise.


Report format

Output one consolidated report. Do not edit any files - this skill recommends fixes, it does not apply them.

# Release Checklist - <ref range>

Audited: <N> files changed, <M> migration func(s) added/modified
Migration files touched: <list, or "none">

## Check 1 - High-scale deadlock / lock contention
Status: PASS | WARN | FAIL
<findings: severity - func name - file:line - impact - remedy>

## Check 2 - Boot-time-blocking migrations
Status: PASS | WARN | FAIL
<findings ...>

## Remediation Plan
<one table row per WARN/FAIL finding from every check; see rules below>

## Summary
<overall: SHIP / SHIP WITH WARNINGS / DO NOT SHIP>
<one line per FAIL that must be resolved before release>

Remediation Plan table

Collect every WARN and FAIL finding from all checks into one table - this is the actionable outcome of the audit. If every check is PASS, drop the table and write No remediation needed - all checks passed. instead.

#Impacted migration (func @ file:line)CheckSeverityOffending operation / queryRecommended change
  • Impacted migration - the migration func and its file:line.
  • Offending operation / query - the exact SQL or migrator call that triggers the signal (e.g. CREATE INDEX idx_logs_foo ON logs(foo)), quoted verbatim or tightly paraphrased. This is what is wrong.
  • Recommended change - the precise fix: the corrected statement, the option to flip (UseTransaction = false), or the path to move to (ensurePerformanceIndexes). This is what to do instead.

When a fix needs more than a table cell (multi-line SQL, a Go code change), keep the table row short and add a ### Fix <#> - <func name> block below the table with a before/after the reader can apply directly:

### Fix 1 - migrationAddFooIndex   (framework/logstore/migrations.go:1234)
- // current - blocks all writes on logs for the whole build
- CREATE INDEX idx_logs_foo ON logs(foo)
+ // append to performanceIndexes; built CONCURRENTLY off the boot path
+ CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_logs_foo ON logs(foo)
Why: keeps the boot path O(1); the real build runs in ensurePerformanceIndexes.

Rules: overall is DO NOT SHIP if any check is FAIL, SHIP WITH WARNINGS if any WARN, else SHIP. Always show every check even when it passes - a visible PASS (no migrations changed) is a real result. Never silently drop a check, and never drop the Remediation Plan when there is at least one WARN/FAIL.

Adding a new check

This skill is meant to grow. To add a check:

  1. Add a ### Check N - <title> subsection under Checks Registry, following Checks 1 and 2: a one-line Goal, a signal table, a per-finding report instruction, and a severity rule.
  2. If it needs background facts, add them once under "Migration system facts" (or a new facts heading) so they are stated once and reused.
  3. Add the check's heading to the Report format template. Its WARN/FAIL findings flow into the shared Remediation Plan table automatically - no per-check table needed.
  4. Keep checks independent - one check failing must not stop the others from running.

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