Queries · q337 · VP Platform Engineering · week 2, night 1
“Did the 20 carts.remind failures in Nov 2025 share a common root cause (pointing to one shared bug/config issue) or look like scattered, tenant-specific problems (pointing to load/capacity)?”
Fictional people at a fictional company, each played by a language-model agent. Who they are and what they are told
Week 1; shared with Samuel Whitcombe, Head of Merchant Success
Leadership wants a review of platform reliability in 2025: failed and slow background jobs, health check failures, rate limiting, webhook delivery problems, and which merchants felt them.
The manager, at the start of week 2
Subject: Re: 2025 Platform Reliability Review — good start, a few things I need tightened up
Lucas,
Thanks — this is useful and more honest than I expected on the limits of what we can see. A few things stood out and need more work before Friday's memo goes to leadership.
First, the retention gap is itself a finding, not just a caveat. We're flying with 90 days of job history and 60 days of health-check history — that means we genuinely don't know how 2025 looked before October. I want that stated plainly and separately in the memo as a reliability/observability gap in its own right, not buried as a footnote under the carts.remind story.
Second, the ERP/WMS/Accounting webhook stuck-retry pattern is, to me, the most important and actionable thing in here — more than the one-week carts.remind incident. I want that properly validated and sized, not eyeballed, before we say anything about it to leadership.
Questions for this week:
On rate limiting: agreed, drop it for this cycle — don't spend a slot trying to force an answer out of config data alone. Just flag it as a 2026 instrumentation ask, as you already have.
Priority for your remaining slots: #1 and #2 above. The webhook/sync issue is the one I can take into a fix-it conversation with engineering next week if the numbers hold up — I'd rather have that nailed down than more polish on the carts.remind narrative.
Diego
The analyst · week 2, night 1, request 3 of 3
Diego wants the webhook stuck-retry finding properly validated before it goes to leadership, and that's explicitly his #1 and #2 priority this week, so two of tonight's three slots go there: first, a correct tenant-level view (fixing last week's broken join) showing exactly how many merchants have ERP/WMS/Accounting sync webhooks stuck above a real threshold and what revenue/order volume sits behind them, so we can say concentrated-in-big-accounts vs long-tail; second, a full-year monthly trend of that same stuck-rate (webhook_deliveries has clean 12-month coverage, unlike job_runs/health_checks) to tell if this is longstanding or a recent regression. I'm using my third slot on Diego's #3 (carts.remind confidence) since it's a cheap, high-value pull: the actual error_message on the 20 failed runs will tell us in one query whether this was one shared root cause (supports his 'latent risk that could recur' concern being containable) or scattered causes (supports a load/capacity read). I'm deferring Diego's #4 (checking if tickets from the 10 affected tenants actually mention sync/reminders/carts) to night 2 since it needs careful text-search scoping and isn't his top priority this week.
The engineer · 1 dry run on the empty schema, then the submission
select t.name as tenant_name, jr.queued_at, jr.started_at, jr.finished_at, jr.error_message, jr.attempt from job_runs jr join jobs j on j.id = jr.job_id join tenants t on t.id = jr.tenant_id where j.handler = 'carts.remind' and jr.status = 'failed' and jr.queued_at >= date '2025-11-01' and jr.queued_at < date '2025-12-01' order by jr.queued_at asc, t.name asc
“Query compiles cleanly against the schema.”
“Submitted. The report returns one row per failed carts.remind run in November 2025 (tenant name, queued/started/finished timestamps, full error message, and attempt number), ordered by queue time then tenant — ready for Lucas to eyeball whether the error strings cluster around one cause or scatter across tenants.”
As Lucas Moreau saw it, from the small dataset the agents worked on
tenant_name | queued_at | started_at | finished_at | error_message | attempt -----------------------+-------------------------+-------------------------+-------------------------+-----------------------------------------+-------- Gratlinie Outdoor | 2025-11-28 14:40:04.027 | 2025-11-28 14:40:05.004 | 2025-11-28 14:40:06.074 | 503 Service Unavailable: storefront API | 3 Marrowby & Vane | 2025-11-28 14:40:05.741 | 2025-11-28 14:40:10.093 | 2025-11-28 14:40:12.292 | 503 Service Unavailable: storefront API | 3 Cinder Peak Sports Co. | 2025-11-28 14:40:06.352 | 2025-11-28 14:40:06.776 | 2025-11-28 14:40:08.558 | 503 Service Unavailable: storefront API | 3 Petalcourt Beauty | 2025-11-28 14:40:06.878 | 2025-11-28 14:40:08.079 | 2025-11-28 14:40:09.171 | 503 Service Unavailable: storefront API | 3 Brennquell Kaffee | 2025-11-28 14:40:06.939 | 2025-11-28 14:40:07.282 | 2025-11-28 14:40:08.716 | 503 Service Unavailable: storefront API | 3 Kibblewick | 2025-11-28 14:40:07.143 | 2025-11-28 14:40:07.534 | 2025-11-28 14:40:08.362 | 503 Service Unavailable: storefront API | 3 Fennel & Flint | 2025-11-28 14:40:08.753 | 2025-11-28 14:40:12.312 | 2025-11-28 14:40:13.509 | 503 Service Unavailable: storefront API | 3 Studio Vrij | 2025-11-28 14:40:09.151 | 2025-11-28 14:40:12.35 | 2025-11-28 14:40:14.566 | 503 Service Unavailable: storefront API | 3 Ampfeld Elektronik | 2025-11-28 14:40:09.362 | 2025-11-28 14:40:11.517 | 2025-11-28 14:40:12.429 | 503 Service Unavailable: storefront API | 3 Cragsley Outfitters | 2025-11-28 14:40:09.758 | 2025-11-28 14:40:11.022 | 2025-11-28 14:40:13.348 | 503 Service Unavailable: storefront API | 3 Gratlinie Outdoor | 2025-11-28 15:40:03.673 | 2025-11-28 15:40:06.151 | 2025-11-28 15:40:07.4 | 503 Service Unavailable: storefront API | 3 Kibblewick | 2025-11-28 15:40:05.175 | 2025-11-28 15:40:07.89 | 2025-11-28 15:40:11.728 | 503 Service Unavailable: storefront API | 3 Cragsley Outfitters | 2025-11-28 15:40:05.504 | 2025-11-28 15:40:06.246 | 2025-11-28 15:40:09.483 | 503 Service Unavailable: storefront API | 3 Fennel & Flint | 2025-11-28 15:40:05.605 | 2025-11-28 15:40:10.525 | 2025-11-28 15:40:11.663 | 503 Service Unavailable: storefront API | 3 Studio Vrij | 2025-11-28 15:40:05.75 | 2025-11-28 15:40:06.179 | 2025-11-28 15:40:07.151 | 503 Service Unavailable: storefront API | 3 Ampfeld Elektronik | 2025-11-28 15:40:05.814 | 2025-11-28 15:40:06.925 | 2025-11-28 15:40:08.173 | 503 Service Unavailable: storefront API | 3 Marrowby & Vane | 2025-11-28 15:40:06.447 | 2025-11-28 15:40:10.262 | 2025-11-28 15:40:11.83 | 503 Service Unavailable: storefront API | 3 Cinder Peak Sports Co. | 2025-11-28 15:40:07.655 | 2025-11-28 15:40:08.369 | 2025-11-28 15:40:09.655 | 503 Service Unavailable: storefront API | 3 Petalcourt Beauty | 2025-11-28 15:40:09.473 | 2025-11-28 15:40:14.407 | 2025-11-28 15:40:15.307 | 503 Service Unavailable: storefront API | 3 Brennquell Kaffee | 2025-11-28 15:40:10.038 | 2025-11-28 15:40:11.938 | 2025-11-28 15:40:15.191 | 503 Service Unavailable: storefront API | 3 (20 rows)
The memo and the queries that followed; links found by title, so inferred
Later queries that build on this report:
It builds on:
Changed only where the benchmark needs the same result on every system
select t.name as tenant_name, jr.queued_at, jr.started_at, jr.finished_at, jr.error_message, jr.attempt jr.queued_at AS queued_at, jr.started_at AS started_at, jr.finished_at AS finished_at, jr.error_message AS error_message, jr.attempt AS attemptfrom job_runs jrjoin jobs j on j.id = jr.job_idjoin tenants t on t.id = jr.tenant_idwhere j.handler = 'carts.remind' and jr.status = 'failed' and jr.queued_at >= date '2025-11-01' and jr.queued_at < date '2025-12-01'order by jr.queued_at asc, t.name ascorder by jr.queued_at asc NULLS LAST, t.name asc NULLS LAST, jr.id asc NULLS LAST
select t.name as tenant_name, jr.queued_at AS queued_at, jr.started_at AS started_at, jr.finished_at AS finished_at, jr.error_message AS error_message, jr.attempt AS attempt from job_runs jr join jobs j on j.id = jr.job_id join tenants t on t.id = jr.tenant_id where j.handler = 'carts.remind' and jr.status = 'failed' and jr.queued_at >= date '2025-11-01' and jr.queued_at < date '2025-12-01' order by jr.queued_at asc NULLS LAST, t.name asc NULLS LAST, jr.id asc NULLS LAST
The agents' own records, as the role play wrote them; only the personal data of the person who ran it is redacted
Report request from Lucas Moreau (analyst for the VP Platform Engineering): Title: Carts.remind Failure Root Cause: Error Messages Question: Did the 20 carts.remind failures in Nov 2025 share a common root cause (pointing to one shared bug/config issue) or look like scattered, tenant-specific problems (pointing to load/capacity)? Grain: one row per failed carts.remind job run (20 rows expected) Columns: - tenant_name - queued_at - started_at - finished_at - error_message - attempt Details: Table job_runs joined to jobs (handler='carts.remind') and tenants, filtered to status='failed' and queued_at in November 2025 (the same 20 rows identified in last week's handler breakdown). Show the full error_message text and attempt number for each failed run so we can see if they cluster around one error string/cause or vary. Order by queued_at ascending, tie-break tenant_name ascending. Check your query with the warehouse's dry_run tool, then hand it in with submit.
dry_runselect t.name as tenant_name, jr.queued_at, jr.started_at, jr.finished_at, jr.error_message, jr.attempt from job_runs jr join jobs j on j.id = jr.job_id join tenants t on t.id = jr.tenant_id where j.handler = 'carts.remind' and jr.status = 'failed' and jr.queued_at >= date '2025-11-01' and jr.queued_at < date '2025-12-01' order by jr.queued_at asc, t.name asc
STATUS: COMPILES (dry run on the empty schema, no data read) COLUMNS: tenant_name, queued_at, started_at, finished_at, error_message, attempt
submitselect t.name as tenant_name, jr.queued_at, jr.started_at, jr.finished_at, jr.error_message, jr.attempt from job_runs jr join jobs j on j.id = jr.job_id join tenants t on t.id = jr.tenant_id where j.handler = 'carts.remind' and jr.status = 'failed' and jr.queued_at >= date '2025-11-01' and jr.queued_at < date '2025-12-01' order by jr.queued_at asc, t.name asc
Submitted to tonight's batch. Your work on this request is done.