observability-triage
GitHub用于 Cloudflare Workers 生产环境错误排查,提供观测数据查询配方、计数陷阱及已知噪声过滤规则。
Trigger Scenarios
Install
npx skills add every-app/open-seo --skill observability-triage -g -y
SKILL.md
Frontmatter
{
"name": "observability-triage",
"metadata": {
"internal": true
},
"description": "Triage OpenSEO production errors in Cloudflare Workers Observability — verified query recipes, counting gotchas, and a known-noise filter list applied automatically. Use when asked to review Cloudflare logs\/observability, count OOMs or worker errors, compare error rates between periods, or investigate a prod error spike."
}
Observability triage
Query Cloudflare Workers Observability for prod errors, count them correctly, and skip the noise that has already been investigated to a dead end. Apply the known-noise list below without re-investigating those entries.
Access
- Resolve the account at runtime — never hardcode it: the
cloudflare-apiMCP server pre-bindsaccountIdinmcp__cloudflare-api__execute, andnpx wrangler whoamiprints it. The workers to triage are the ones this repo deploys (seealchemy.run.ts): the main app worker plus the aux workers (audit engine, landing, self-host). - Query via the
cloudflare-apiMCP server (mcp__cloudflare-api__execute). If its tools are absent, run its authenticate flow and give the user the URL — wrangler's OAuth token gets a 403 on the observability API (missing scope), so don't burn time on curl-with-wrangler-token. - PostHog is the second error source but cannot see
exceededMemory/canceled/responseStreamDisconnectedoutcomes — worker-outcome questions are answerable only here.
Query recipes (verified shapes)
POST /accounts/{account_id}/workers/observability/telemetry/query. All of these are load-bearing; the API's 400s are opaque:
-
queryId: "adhoc"is required. Timeframe is epoch milliseconds:timeframe: { from, to }. -
Count invocations by outcome:
{ "queryId": "adhoc", "timeframe": { "from": 0, "to": 0 }, "parameters": { "datasets": ["cloudflare-workers"], "filters": [ { "key": "$metadata.type", "operation": "eq", "value": "cf-worker-event", "type": "string" } ], "calculations": [{ "operator": "count", "alias": "count" }], "groupBys": [ { "value": "$workers.scriptName", "type": "string" }, { "value": "$workers.outcome", "type": "string" } ], "limit": 100 }, "view": "calculations", "limit": 100 } -
The
cf-worker-eventfilter is what makes counts mean invocations; without it you count every log line. -
Raw samples:
view: "events", emptycalculations/groupBys, smalllimit. Events carry$metadata(service,trigger,level,message,fingerprint,requestId) and$workers(outcome,scriptName,scriptVersion,wallTimeMs,cpuTimeMs,eventType). -
Error-level app logs grouped by message: filter
$metadata.level eq error, groupBy$metadata.message. -
Verified filter operations:
eq,neq. Percentiles: the API wants"median", not"p50". Filter for substrings client-side on fetched events. -
Useful drill-downs: groupBy
$metadata.trigger(route),$workers.scriptVersion(did a deploy change the rate mid-window),$workers.event.request.headers.user-agent.
Counting gotchas
- Grouped results are unsorted and effectively capped (~10 rows returned regardless of
limit). A missing group ≠ zero. To see error outcomes, add$workers.outcome neq okinstead of hoping the error rows make the cut; sort client-side. - One isolate death fans out. An OOM kills every request pinned to the isolate at the same instant — cluster raw OOM events by timestamp before reading the count as user impact.
- Message prefixes fragment groups. Logs with leading timestamps (better-auth's format) split one error into N single-count groups; grouped-by-message counts badly understate them. Sample events and merge client-side.
- Prod deploys are manual — main being fixed doesn't mean prod runs the fix. Check
$workers.scriptVersionand the scripts'modified_onbefore concluding a fix didn't work.
Known noise — filter these out, do not re-investigate
Entries land here only after an investigation proved there is no first-party emit site to fix or demote. Each keeps the one condition that would make it real signal again.
1. SAM chat Durable Object lifecycle (close code 1006)
- Messages (one phenomenon, counted three ways):
Connection closed: this Durable Object instance is no longer active. Reconnect or retry the request.(hibernation/eviction),Durable Object reset because its code was updated.(deploy), plus the paired invocation summary whose$metadata.errorisclose. - Identify by:
eventType: "hibernatableWebSocket", entrypointSamChatAgent/OnboardingChatAgent,webSocketType: "close", code: 1006, wasClean: false,outcome: "exception", single-digitwallTimeMs,cpuTimeMs: 0, no stack. Fingerprints3aa4cac26653d09a0a41100a33d413ae(exception),0ae15457af49b4d9a117eeecf66b040a(summary). - Why unfixable: the DO is destroyed under the JS — its IoContext is already aborted when workerd delivers
webSocketClose, so the firstawaitnever settles.partyserveralready try/catches the whole close path; anonCloseoverride would catch nothing. - Nothing breaks: transcripts persist per message in DO SQLite, PartySocket reconnects unconditionally, and credit metering (
onChatResponse) never fires on an aborted turn. - Real signal: a sustained rise that does not correlate with a deploy (would mean mid-conversation evictions beyond hibernation).
2. Network connection lost.
- Identify by: fingerprint
be89d4ff7a64cb4d4dceae0f51cfe708, or the message verbatim. Runtime-generated shape:source.levelabsent,source.exceptionpresent,$metadata.origin: "fetch"— the opposite of every app log (source.levelpresent, noexception). - Why unfixable: workerd's own record of a client disconnecting mid-stream; the exception never enters app code — the sibling request event for the same
requestIdhasoutcome: "ok". No emit site exists;wrangler.jsoncobservability config has no per-message filter. Do not add try/catch around the stream handlers (dead ceremony). - Real signal: if the
/mcpshare of this group grows, treat it as a tool-call-latency symptom (clients timing out and cancelling) and route it to the /mcp performance track — not to this log group.
Runtime-vs-app litmus test
Before investigating any unfamiliar error event: source.level absent + source.exception present ⇒ the Workers runtime wrote it, not the app. There is no call site to grep for; judge it by the sibling request's outcome.
Adding an entry
Add to this list only after establishing there is no first-party emit site (grep the message; check the runtime-vs-app litmus above) and nothing is left in a wrong state. Every entry must include identify-by markers (fingerprint if stable) and its real-signal condition.
Version History
- 3632f40 Current 2026-09-09 14:48


