{ "meta": { "provider": "claude", "model": "claude-sonnet-5", "version": "1.2.8", "commit": "b6de6e1", "date": "2026-10-28 11:22 UTC", "rounds": 2 }, "stopped": null, "summary": { "held_out": { "runs": 22, "incidents": 20, "root_cause": 19, "strict": 13, "lenient": 20, "commit_expected": 12, "commit_correct": 12, "distractor_blamed": 6, "healthy": 2, "healthy_silent": 2, "mean_alerting": 1.15, "errors": 0, "cost_usd": 0.8903, "mean_seconds": 35.7 }, "all": { "runs": 22, "incidents": 20, "root_cause": 19, "strict": 13, "lenient": 20, "commit_expected": 12, "commit_correct": 12, "distractor_blamed": 6, "healthy": 2, "healthy_silent": 2, "mean_alerting": 1.15, "errors": 0, "cost_usd": 0.8903, "mean_seconds": 35.7 }, "consistency": { "scenarios": 11, "stable": 10 } }, "results": [ { "id": "h01_connection_leak", "set": "held_out", "category": "bad deploy", "name": "Connection leak on an error path (pool size unchanged)", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 58.1, "cost_usd": 0.065978, "tokens_input": 2329, "tokens_output": 6132, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "inventory-api", "affected_services": [], "description": "Repeated SQLAlchemy QueuePool timeouts in inventory-api's reserve() flow, caused by a database session that is never closed when a reservation is rejected for insufficient stock.", "root_cause": "Commit 4b0e77d1 (feat(stock): reject reservations above availability) refactored StockService.reserve() in inventory/stock.py from a context-managed session ('with self.db.session() as s:') to manual session handling. In the new code, when row.available < qty the function raises OutOfStock(sku) BEFORE reaching s.commit()/s.close(), so the checked-out database connection is never returned to the pool. Under continued reservation traffic (including repeated out-of-stock attempts), connections leak one-by-one until the pool (size 40, overflow 0) is exhausted, after which every subsequent reserve() call blocks for the full 30s pool timeout and raises sqlalchemy.exc.TimeoutError, exactly matching the stack trace at stock.py line 57. Errors begin appearing ~126-130 minutes after the commit, consistent with the time needed for leaked connections to accumulate to the pool limit under production traffic.", "recommendation": "Wrap the reserve() session logic in try/finally (or restore the 'with self.db.session() as s:' context manager) so the session is always closed/rolled back, including on the OutOfStock exception path. Add pool exhaustion alerting and a session-leak check in code review for any manual session.close() patterns.", "linked_commits": [ { "sha": "4b0e77d1", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed six identical sqlalchemy.exc.TimeoutError ERROR log entries from inventory-api, all with the same stack frame at stock.py line 57 inside StockService.reserve(), recurring every minute from 14:36 to 14:41.\n2. This pattern \u2014 a fixed-size QueuePool repeatedly hitting its limit \u2014 suggested a connection/session leak rather than a transient load spike, so I checked recent code changes touching stock.py.\n3. Commit 4b0e77d1 shows the exact line in the stack trace: it replaced a context-managed session with manual session handling and added an early 'raise OutOfStock(sku)' before s.commit()/s.close(), meaning the session is left open whenever a reservation is rejected for insufficient stock.\n4. CPU metrics for the same window remained stable (24-31%), ruling out a resource-contention or traffic-surge explanation and reinforcing that the exhaustion is caused by the leaked sessions rather than external load.\n5. The commit timestamp (12:30) precedes the first error (14:36) by ~126 minutes, consistent with gradual pool exhaustion as leaked sessions accumulated under live traffic, confirming the causal link." }, { "severity": "INFO", "confidence": "LOW", "component": "inventory-api", "affected_services": [], "description": "HTTP server read_timeout was lowered from 30s to 25s shortly before the reservation errors appeared, which shortens the window for slow/leaked-connection requests to complete and could cause premature client-facing timeouts that mask or compound the underlying pool exhaustion.", "root_cause": "Commit 9c1d2e3f (chore: lower read timeout) reduced config/http.yaml server.read_timeout from 30s to 25s. While not directly tied to a log error, this change tightens the tolerance for slow backend responses right before the connection-pool exhaustion incident began, increasing the likelihood that requests fail faster/noisier once pool contention starts.", "recommendation": "Re-evaluate whether 25s read_timeout is appropriate given the DB session leak fix in progress; consider reverting or tuning only after the pool-leak bug is resolved to avoid masking the root cause with timeout-driven retries.", "linked_commits": [ { "sha": "9c1d2e3f", "provider": "unknown", "project_id": null } ], "reasoning": "1. I noted a config diff lowering read_timeout from 30s to 25s committed at 13:40, about an hour before the first QueuePool timeout error.\n2. I checked whether this timing correlated with the error onset but found no direct log evidence tying the timeout value itself to the TimeoutError stack traces, which reference the DB pool timeout (30.00s), not the HTTP read_timeout.\n3. Because there is no runtime evidence directly implicating this change, I report it as a lower-confidence, code-review-only finding rather than a confirmed root cause." } ], "answer": { "services": [ "inventory-api" ], "cause": [ [ "leak", "not closed", "never closed", "stays open", "left open", "not released", "never released", "not returned", "close" ] ], "blame_sha": "4b0e77d1", "wrong_shas": [ "9c1d2e3f" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "not blamed 9c1d2e3": false, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h02_retry_storm", "set": "held_out", "category": "bad deploy", "name": "Retry storm from a client change overloads a healthy service", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 49.0, "cost_usd": 0.053124, "tokens_input": 1052, "tokens_output": 5102, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "ratings-svc", "affected_services": [ "product-page" ], "description": "ratings-svc's request queue saturated (1024 waiting) and began returning 503s, triggering product-page's newly-configured zero-delay retry storm (10 attempts, fixed 0ms backoff, no jitter), which further overloaded ratings-svc and drove its CPU to 99%.", "root_cause": "Commit e5a91b02 (2026-10-18T14:26:00Z) in web/src/clients/ratings.ts changed the ratings client retry policy from attempts:3 with exponential backoff+jitter to attempts:10 with a fixed 0ms delay. Four minutes later, product-page began retrying failed ratings calls up to 10 times with no delay between attempts. This thundering-herd of immediate retries overwhelmed ratings-svc, filling its request queue (1024 waiting) and causing it to return 503 Service Unavailable, which in turn triggered more retries from product-page in a feedback loop. Traces confirm 2600/4200 spans (62%) errored during the window, concentrated in ratings-svc's GET /ratings/{sku} endpoint, and ratings-svc CPU climbed to a 99% peak / 98% current with an increasing trend as it struggled to process the retry flood.", "recommendation": "Revert or fix the retry configuration in web/src/clients/ratings.ts to restore exponential backoff with jitter and a capped attempt count (e.g., 3-4 attempts); add a circuit breaker on the product-page ratings client to stop retrying once ratings-svc is returning 503s; consider adding queue-depth-based load shedding or autoscaling on ratings-svc.", "linked_commits": [ { "sha": "e5a91b02", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed WARN logs from product-page showing 'retrying (attempt 1/10)' repeated 20 times alongside ERROR logs from ratings-svc showing '503 Service Unavailable: request queue full (1024 waiting)' repeated 6 times in the same 14:30-14:39 window.\n2. The auto-correlation engine matched these ratings-svc span errors to the log errors with HIGH confidence, and traces showed 2600 of 4200 spans (62%) erroring, concentrated on ratings-svc's GET /ratings/{sku} endpoint \u2014 consistent with a service being overwhelmed rather than an isolated bug.\n3. I checked recent code changes and found commit e5a91b02 at 14:26:00Z, four minutes before the first error log, which changed the ratings client's retry config from 3 attempts with exponential backoff+jitter to 10 attempts with a fixed 0ms delay \u2014 removing all throttling between retries.\n4. Metrics confirmed ratings-svc CPU rose to 83% avg / 99% peak / 98% current with an increasing trend, matching the timeline of the retry storm rather than a pre-existing load issue, since product-page's own CPU stayed flat at ~35-41%.\n5. I ruled out a ratings-svc-only failure (e.g., a bad deploy on that service) because no code changes were recorded for ratings-svc in this window \u2014 the only change was the product-page retry policy, which directly explains the queue-full/503/retry feedback loop." } ], "answer": { "services": [ "product-page" ], "cause": [ [ "retry", "retries", "retrying" ], [ "backoff", "back-off", "storm", "amplif", "10 attempts", "attempts", "delay" ] ], "blame_sha": "e5a91b02", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h03_kafka_rebalance", "set": "held_out", "category": "config", "name": "Kafka consumer rebalance loop after a poll-size change", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 56.6, "cost_usd": 0.064326, "tokens_input": 1183, "tokens_output": 6196, "issues": [ { "severity": "WARNING", "confidence": "HIGH", "component": "order-events-consumer", "affected_services": [], "description": "The order-events-consumer is repeatedly exceeding max.poll.interval.ms (300000ms), causing Kafka consumer group rebalances and failed offset commits (CommitFailedException) every ~6 minutes since a config change increased max-poll-records from 500 to 5000.", "root_cause": "Commit 71f0c3aa (perf(consumer): fetch more records per poll, 2026-10-18T14:15:00Z) increased spring.kafka.consumer.max-poll-records from 500 to 5000 while leaving max.poll.interval.ms unchanged at 300000ms. The 10x larger batch size increases the time required to process each poll() call beyond the 5-minute interval limit, triggering the Kafka client to assume the consumer is dead and the broker to rebalance the partitions away. This produces the recurring 'consumer poll timeout has expired' warnings followed by CommitFailedException when the consumer tries to commit offsets for partitions it no longer owns. The pattern begins ~7 minutes after the commit and repeats on a consistent ~6-minute cycle matching the rebalance/reprocessing loop. The CPU peak of 88% (vs 58% avg) is consistent with the increased per-poll processing load from larger batches.", "recommendation": "Roll back max-poll-records to a value the processing pipeline can handle within max.poll.interval.ms (e.g., revert to 500), or proportionally increase max.poll.interval.ms to accommodate the larger batch size. Add monitoring/alerting on poll-timeout warnings and rebalance frequency to catch regressions from future tuning changes.", "linked_commits": [ { "sha": "71f0c3aa", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed a repeating pattern of WARN 'poll timeout expired' immediately followed by ERROR 'CommitFailedException' at regular ~6-minute intervals in the order-events-consumer logs.\n2. This pattern strongly suggests the consumer's processing time per poll() exceeds max.poll.interval.ms, causing Kafka to rebalance partitions away from the consumer before it can commit.\n3. I checked recent code changes and found commit 71f0c3aa, timestamped 7 minutes before the first warning, which increased max-poll-records tenfold (500->5000) without adjusting max.poll.interval.ms.\n4. I cross-checked the CPU metrics, which show a peak of 88% (above the 80% threshold) consistent with heavier per-poll processing load introduced by the larger batch size, corroborating the timing correlation.\n5. No other code changes or dependencies were present in the window, so the config diff is the most plausible and well-correlated root cause." } ], "answer": { "services": [ "order-events-consumer" ], "cause": [ [ "poll", "max-poll-records", "max.poll" ], [ "5000", "records", "rebalanc", "interval", "processing time" ] ], "blame_sha": "71f0c3aa", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h04_clock_skew", "set": "held_out", "category": "infrastructure", "name": "Clock skew on one node rejects valid tokens", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 47.3, "cost_usd": 0.051968, "tokens_input": 884, "tokens_output": 5020, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "auth-gateway", "affected_services": [], "description": "auth-gateway is rejecting every JWT it receives with 'token used before issued', repeating every 2 minutes for at least 14 minutes straight. The token's iat (issued-at) claim is consistently ahead of the gateway's local clock, which is the signature of clock skew between the token issuer and the auth-gateway host rather than a genuine malformed/forged token.", "root_cause": "The auth-gateway's system clock (or the upstream token issuer's clock) has drifted out of sync, causing issued JWTs to carry an 'iat' timestamp that is in the future relative to the gateway's 'now'. Every incoming token is therefore rejected by the standard iat-not-in-future validation check, regardless of whether the token is otherwise valid. The uniform 2-minute cadence and identical error message across all 8 occurrences indicates a systemic clock offset rather than isolated bad tokens.", "recommendation": "Check NTP/chrony sync status and system clock offset on the auth-gateway host and the token-issuing service; resync clocks immediately. As a stop-gap, add a small clock-skew tolerance (e.g. 30-60s leeway) to the JWT iat validation to absorb minor drift while the root clock sync issue is fixed.", "linked_commits": [], "reasoning": "1. I observed 8 identical ERROR log lines from auth-gateway over a 14-minute window, all with the message 'token used before issued' comparing iat vs now.\n2. This specific error phrasing (iat > now) only occurs when the token's issued-at timestamp appears to be in the future from the validator's perspective, which points to a clock synchronization problem rather than a token forgery or logic bug.\n3. I checked the one code change in the window (gateway/auth/logging.go) and found it only adds a logging import with no changes to auth/validation logic, ruling out this deploy as the cause of the rejections.\n4. The consistent 2-minute interval and identical error across all entries rules out a transient network blip and supports a persistent systemic clock offset as the root cause." }, { "severity": "WARNING", "confidence": "MEDIUM", "component": "auth-gateway", "affected_services": [], "description": "Commit 2aa7d19c adds an import of 'log/slog' to gateway/auth/logging.go but the visible diff shows no usage of the package within the file. In Go, an imported package that is never referenced causes a compile-time failure ('imported and not used'), which would break the build for this file if no further usage was added elsewhere in the same commit.", "root_cause": "Commit 2aa7d19c (branch main, 'chore(auth): structured logging for token checks') adds '+import \"log/slog\"' to gateway/auth/logging.go with no corresponding usage shown in the diff, risking a Go compiler error for an unused import.", "recommendation": "Verify the full commit actually uses slog somewhere in logging.go (e.g. slog.Info/slog.Error calls); if not, either add the intended logging calls or remove the unused import before merging to avoid a broken build.", "linked_commits": [ { "sha": "2aa7d19c", "provider": "unknown", "project_id": null } ], "reasoning": "1. I reviewed the diff for commit 2aa7d19c and saw only a single added import line with no accompanying code that references the slog package.\n2. Go's compiler rejects unused imports, so I flagged this as a potential build-breaking change introduced just before the auth-gateway error window began.\n3. I checked whether this commit could explain the JWT rejection errors and found it touches only logging, not token validation logic, so I kept it as a separate, lower-severity code-quality finding rather than conflating it with the auth failures." } ], "answer": { "services": [ "node-c", "chronyd", "auth-gateway" ], "cause": [ [ "clock", "time sync", "ntp", "chrony", "skew", "drift" ] ], "blame_sha": null, "wrong_shas": [ "2aa7d19c" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "not blamed 2aa7d19": false, "focused": true }, "kind": "incident", "alerting": 2, "commit_expected": false } }, { "id": "h05_hpa_cap", "set": "held_out", "category": "config", "name": "Autoscaler capped at 2 replicas during a traffic spike", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 34.9, "cost_usd": 0.040716, "tokens_input": 1278, "tokens_output": 3816, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "search-api", "affected_services": [ "ingress-nginx", "web" ], "description": "search-api is CPU-saturated (91% avg, peak 100%, current 99%, trend INCREASING) after its HPA maxReplicas was reduced from 20 to 2, causing ingress-nginx upstream timeouts on /search and 30s p99 latency spikes observed in traces.", "root_cause": "Commit d3c4b5a6 (ops-bot, 2026-10-18T09:00:00Z) changed deploy/k8s/search-api-hpa.yaml, reducing maxReplicas from 20 to 2. Within hours search-api CPU climbed to 91% avg / 100% peak with an increasing trend, the HPA could no longer scale out to absorb load, and requests queued behind the capped pod count. This manifested as repeated ingress-nginx 'upstream timed out' errors on http://search-api.prod.svc:8080/search starting at 14:40 and a 30000ms GET /search span in trace f00d0001, with 410 errors recorded out of 3000 spans in the window.", "recommendation": "Revert or raise search-api-hpa.yaml maxReplicas back to a safe ceiling (e.g. 20) and redeploy immediately; add a PodDisruptionBudget/alert on HPA cap changes and CPU>90% sustained to prevent recurrence.", "linked_commits": [ { "sha": "d3c4b5a6", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed repeated ingress-nginx ERROR logs every minute from 14:40 to 14:45 all pointing at the same upstream: search-api.prod.svc:8080/search timing out.\n2. I checked the metrics summary and found search-api CPU running at 91% avg / 100% peak / 99% current with an INCREASING trend, far above the 90% CPU_HIGH threshold, suggesting a capacity bottleneck rather than a code bug.\n3. I cross-referenced recent commits and found d3c4b5a6 which cut search-api's HPA maxReplicas from 20 to 2 just hours before the CPU saturation and timeouts began, directly limiting the service's ability to scale.\n4. I confirmed with distributed traces showing a 30000ms GET /search span (trace f00d0001) and 410 errors out of 3000 spans, consistent with request queuing/timeouts caused by insufficient replica capacity rather than an application-level defect.\n5. I ruled out the second commit (dashboard panel addition) as unrelated since it only adds a monitoring panel and touches no service logic." } ], "answer": { "services": [ "search-api" ], "cause": [ [ "replica", "hpa", "autoscal", "scale", "scaling" ], [ "2", "max", "cap", "limit" ] ], "blame_sha": "d3c4b5a6", "wrong_shas": [ "a0b1c2d3" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "not blamed a0b1c2d": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h06_migration_lock", "set": "held_out", "category": "bad deploy", "name": "Migration rewrites a large table and locks it", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 43.4, "cost_usd": 0.047702, "tokens_input": 1381, "tokens_output": 4494, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "orders-api", "affected_services": [], "description": "orders-api is repeatedly failing to commit order updates with 'canceling statement due to lock timeout' while locking tuple (412,7) in relation orders_order, starting ~5 minutes after a schema migration touched that exact table/column.", "root_cause": "Commit 5f6e7d8c (2026-10-18T14:08:00Z) adds migration 0058_order_total_precision.py which runs AlterField on orders.Order.total to change its DecimalField precision (max_digits=14, decimal_places=4). On PostgreSQL, AlterField that changes a column's numeric precision/scale requires an ACCESS EXCLUSIVE lock on the table for the duration of the rewrite/validation, which blocks all concurrent reads/writes to orders_order. Five minutes after the migration commit, orders-api begins throwing repeated OperationalError: canceling statement due to lock timeout while trying to lock the same tuple/relation, consistent with production traffic queuing behind the migration's exclusive lock (or behind contention it left in its wake) until statements exceed Postgres's lock_timeout.", "recommendation": "Roll back or re-run this migration using a zero-downtime strategy: add the new precision column alongside the old one, backfill asynchronously, then swap/rename in a fast follow-up migration instead of altering the column type in place. Additionally, set an explicit short lock_timeout and statement_timeout with retry/backoff for schema migrations, and run them during low-traffic windows with pg_locks monitoring to catch blocking before it cascades to API errors.", "linked_commits": [ { "sha": "5f6e7d8c", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed 10 identical ERROR log lines from orders-api between 14:13 and 14:17, all citing OperationalError: canceling statement due to lock timeout on the same tuple/relation orders_order.\n2. I checked recent code changes and found commit 5f6e7d8c at 14:08, five minutes before the errors began, which adds a migration performing AlterField on orders_order.total \u2014 the exact table referenced in the error context.\n3. I confirmed AlterField changing DecimalField precision requires an ACCESS EXCLUSIVE lock in Postgres, which explains sustained lock contention on orders_order rather than an isolated one-off query issue.\n4. CPU metrics stayed stable (40% avg, 72% peak) during this window, ruling out a resource-exhaustion cause and reinforcing that the lock timeouts are schema/lock-driven rather than load-driven." } ], "answer": { "services": [ "orders-api", "postgres", "orders_order" ], "cause": [ [ "lock", "locked", "locking" ], [ "migration", "alter", "rewrite", "0058" ] ], "blame_sha": "5f6e7d8c", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h07_feature_flag", "set": "held_out", "category": "config", "name": "Feature-flag rollout with no deploy", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 37.7, "cost_usd": 0.0409, "tokens_input": 1175, "tokens_output": 3855, "issues": [ { "severity": "WARNING", "confidence": "MEDIUM", "component": "tax-svc", "affected_services": [], "description": "tax-svc's v2 tax engine repeatedly fails to resolve a tax rule for region CA-QC (Quebec, Canada), rejecting 12 orders over a 6-minute window.", "root_cause": "The v2 tax engine's rule table is missing an entry for region CA-QC, causing every order from that region to throw TaxRuleNotFound. Commit 8a9b0c1d (test(tax): more fixtures) only added a US-NY test fixture and did not address CA-QC, indicating the production rule set for engine v2 was never populated with Quebec-specific tax rules (which commonly require distinct handling due to combined GST/QST). This is a data/config completeness gap in the v2 engine rollout rather than a transient failure, since the error recurs steadily every ~60-120 seconds across sequential order IDs.", "recommendation": "Add the missing CA-QC tax rule configuration to the v2 engine rule table (including GST/QST handling), add a regression test/fixture specifically for CA-QC, and audit the v2 rule set for other missing Canadian provinces before continuing rollout.", "linked_commits": [ { "sha": "8a9b0c1d", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed 12 consecutive ERROR logs from tax-svc, all TaxRuleNotFound for region=CA-QC on engine=v2, spaced roughly every minute across sequential order IDs, which points to a systematic missing-configuration issue rather than a one-off fault.\n2. I checked the only code change in the window, commit 8a9b0c1d, which adds a 'US-NY' entry to tax/tests/fixtures.py \u2014 this confirms the team is actively building out the fixture/rule set for engine v2 but has not yet added CA-QC, supporting the missing-config hypothesis.\n3. I ruled out a transient or network-related cause (no connection/timeout signatures, no restart or deploy events in the logs) and confirmed the failure is deterministic per-region, consistent with a static rule lookup gap rather than an infrastructure problem.\n4. The auto-correlation engine found 0 high-confidence matches between the commit and the errors, so while the commit shows active related work it does not prove causation \u2014 I therefore treat the commit as supporting context rather than a direct trigger." } ], "answer": { "services": [ "tax-svc", "flags-svc" ], "cause": [ [ "flag", "rollout", "new-tax-engine", "engine=v2", "v2" ], [ "rule", "region", "ca-qc", "quebec" ] ], "blame_sha": null, "wrong_shas": [ "8a9b0c1d" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "not blamed 8a9b0c1": false, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": false } }, { "id": "h08_rate_limited", "set": "held_out", "category": "bad deploy", "name": "Carrier API rate limit after a polling schedule change", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 29.0, "cost_usd": 0.036006, "tokens_input": 1323, "tokens_output": 3336, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "shipping-rates", "affected_services": [], "description": "shipping-rates service is continuously hit with 429 Too Many Requests errors from the carrier rates API, with X-RateLimit-Remaining at 0 and a Retry-After of 3600 seconds, indicating the service has exhausted its API quota and is locked out for the next hour.", "root_cause": "Commit c1d2e3f4 (feat(shipping): fresher carrier rates, 2026-10-18T13:10:00Z) changed the rates-refresh-cronjob schedule in deploy/k8s/rates-refresh-cronjob.yaml from every 15 minutes (\"*/15 * * * *\") to every minute (\"* * * * *\"). This 15x increase in call frequency to the carrier's /v2/rates endpoint exceeded the carrier API's rate limit, causing it to return 429 Too Many Requests with X-RateLimit-Remaining: 0 and Retry-After: 3600 starting roughly one hour after the deploy. Because the retry-after window is a full hour, the service will remain locked out of fresh rate data until the quota resets, unless the cronjob frequency is reverted.", "recommendation": "Revert deploy/k8s/rates-refresh-cronjob.yaml schedule back to \"*/15 * * * *\" (or a frequency within the carrier's documented rate limit), add exponential backoff and Retry-After-aware handling in the shipping-rates client, and implement local caching of rate responses to reduce call volume to the carrier API.", "linked_commits": [ { "sha": "c1d2e3f4", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed a continuous stream of 429 Too Many Requests errors from shipping-rates targeting the carrier's /v2/rates endpoint, starting at 14:10:00 and repeating every minute through 14:19:00, with X-RateLimit-Remaining consistently at 0.\n2. I checked the recent code changes and found commit c1d2e3f4 at 13:10:00Z, one hour before the errors began, which modified the rates-refresh-cronjob schedule from every 15 minutes to every minute.\n3. The timing gap (~1 hour) and consistent Retry-After: 3600 value are consistent with the cronjob exhausting the carrier's hourly rate limit quota shortly after the schedule change took effect.\n4. I ruled out other causes since there are no other commits or service changes in the window, and the error pattern (every-minute cadence, 429 status, zero remaining quota) directly matches the new cron frequency rather than an unrelated carrier-side outage." } ], "answer": { "services": [ "shipping-rates" ], "cause": [ [ "429", "rate limit", "rate-limit", "too many requests", "quota" ], [ "schedule", "cron", "every minute", "polling", "frequency", "15" ] ], "blame_sha": "c1d2e3f4", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h10_benign_spike", "set": "held_out", "category": "healthy", "name": "Traffic spike absorbed by autoscaling (nothing wrong)", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 8.2, "cost_usd": 0.00923, "tokens_input": 375, "tokens_output": 848, "issues": [], "answer": { "services": [ "web" ], "cause": [], "blame_sha": null, "wrong_shas": [], "max_issues": 2, "benign_max": "WARNING", "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "silent": true }, "kind": "healthy", "alerting": 0, "commit_expected": false } }, { "id": "h11_red_herring", "set": "held_out", "category": "infrastructure", "name": "Rotated SMTP password, next to old unrelated 404 noise", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 12.9, "cost_usd": 0.016894, "tokens_input": 797, "tokens_output": 1530, "issues": [ { "severity": "CRITICAL", "confidence": "MEDIUM", "component": "notifications-svc", "affected_services": [], "description": "notifications-svc is repeatedly failing to authenticate with its SMTP provider, causing all outbound email notifications to fail.", "root_cause": "The notifications-svc is consistently receiving SMTP error code 535 (5.7.8 Authentication credentials invalid) when attempting to authenticate with its mail server, indicating the configured SMTP username/password or app-specific token is incorrect, expired, or revoked.", "recommendation": "Verify and rotate the SMTP credentials used by notifications-svc (check for expired app passwords or recently rotated secrets at the mail provider). Update the service's secret/config store and redeploy or restart the service to pick up valid credentials. Add alerting on repeated SMTPAuthenticationError to catch credential expiry proactively.", "linked_commits": [], "reasoning": "1. I observed 8 consecutive ERROR log lines from notifications-svc, each an identical smtplib.SMTPAuthenticationError (535 Authentication credentials invalid) spaced one minute apart from 14:32 to 14:39.\n2. This pattern suggests a persistent, unresolved credential issue rather than a transient network blip, since every single attempt over 8 minutes failed with the exact same authentication error code.\n3. With only logs available for this org, I cannot confirm via metrics/traces/code whether a recent deploy or secret rotation caused this, but the uniformity and repetition of the error strongly and specifically points to invalid SMTP credentials as the root cause rather than an intermittent network or server-side issue." } ], "answer": { "services": [ "notifications-svc" ], "cause": [ [ "smtp", "email", "mail" ], [ "credential", "password", "auth", "535", "rotat" ] ], "blame_sha": null, "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [ "mobile-gateway" ] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "focused": true, "no critical on mobile-gateway": true }, "kind": "incident", "alerting": 1, "commit_expected": false } }, { "id": "h12_es_watermark", "set": "held_out", "category": "infrastructure", "name": "Elasticsearch disk watermark blocks writes for three services", "round": 1, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 28.6, "cost_usd": 0.032684, "tokens_input": 1022, "tokens_output": 3064, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "elasticsearch-cluster", "affected_services": [ "audit-svc", "logging-api", "search-api" ], "description": "The shared Elasticsearch cluster exceeded its flood-stage disk watermark, causing it to automatically set a read-only-allow-delete block on indices. This blocked writes from three independent services (logging-api, search-api, audit-svc), each targeting a different index (app-logs-2026.10.18, products-v7, audit-2026.10).", "root_cause": "The underlying Elasticsearch cluster's disk usage crossed the flood-stage watermark threshold, triggering ES's built-in protection mechanism which applies a 'read-only-allow-delete' index block to prevent disk exhaustion. This is a cluster-wide storage capacity issue, not a per-service bug \u2014 the three services (logging-api, search-api, audit-svc) are independent clients writing to different indices (app-logs-2026.10.18, products-v7, audit-2026.10) and all failed with identical ClusterBlockException errors within a 5-minute window, confirming a single shared root cause rather than three unrelated failures.", "recommendation": "Free up disk space on the Elasticsearch data nodes immediately (delete/relocate old indices, expand storage, or trigger ILM rollover/delete policies), then clear the index blocks by running `PUT /_all/_settings {\"index.blocks.read_only_allow_delete\": null}` once disk usage drops below the high watermark. Set up alerting on ES disk watermark thresholds and consider enabling automated ILM to prevent recurrence.", "linked_commits": [], "reasoning": "1. I observed three different services (logging-api, search-api, audit-svc) throwing the identical ClusterBlockException error referencing 'disk usage exceeded flood-stage watermark' within the same few minutes.\n2. This pattern \u2014 same error signature across unrelated services pointing to indices rather than application logic \u2014 suggested a shared infrastructure dependency failure rather than three independent service bugs.\n3. I checked the recent code commit (CSS button styling) and found it unrelated in timing, scope, and content to backend/index behavior, ruling out a deploy-caused regression.\n4. I confirmed the common thread was the Elasticsearch cluster disk watermark protection mechanism, which blocks writes across any index once triggered, explaining why multiple unrelated services failed simultaneously." } ], "answer": { "services": [ "elasticsearch", "es-data-2" ], "cause": [ [ "disk", "watermark", "flood" ], [ "read-only", "read only", "readonly", "block" ] ], "blame_sha": null, "wrong_shas": [ "f1e2d3c4" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": false, "lenient": true, "checks": { "detected": true, "top service": false, "top cause": true, "not blamed f1e2d3c": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": false } }, { "id": "h01_connection_leak", "set": "held_out", "category": "bad deploy", "name": "Connection leak on an error path (pool size unchanged)", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 45.3, "cost_usd": 0.053566, "tokens_input": 2328, "tokens_output": 4891, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "inventory-api", "affected_services": [], "description": "inventory-api is repeatedly failing to acquire a database session with 'QueuePool limit of size 40 overflow 0 reached, connection timed out' every minute starting at 14:36:00, indicating the connection pool is exhausted and not being replenished.", "root_cause": "Commit 4b0e77d1 ('feat(stock): reject reservations above availability') refactored StockService.reserve() in inventory/stock.py to replace the `with self.db.session() as s:` context manager with a manually-managed session (`s = self.db.session()` ... `s.commit(); s.close()`). The new code raises OutOfStock(sku) when row.available < qty BEFORE reaching s.commit()/s.close(), so any reservation attempt that exceeds available stock leaves the SQLAlchemy session \u2014 and its underlying DB connection \u2014 open and never returned to the pool. Over repeated requests this steadily leaks connections out of the QueuePool (size 40, overflow 0) until the pool is fully exhausted, after which every subsequent call to self.db.session() in reserve() blocks for the full 30s timeout and raises sqlalchemy.exc.TimeoutError, exactly matching the stack trace (views.py:88 -> stock.py:57) seen every minute from 14:36 to 14:41.", "recommendation": "Revert/fix inventory/stock.py to guarantee session cleanup on all code paths: wrap the reserve() logic in a try/finally (or restore the `with self.db.session() as s:` context manager) so OutOfStock and any other exception still closes/releases the session back to the pool. Add a connection-pool-in-use gauge/alert and a test that asserts the session is closed when OutOfStock is raised.", "linked_commits": [ { "sha": "4b0e77d1", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed six identical sqlalchemy.exc.TimeoutError tracebacks from inventory-api, all pointing to stock.py line 57 (self.db.session()), occurring once per minute with no recovery.\n2. A 'QueuePool limit reached' error with overflow 0 and a hard 30s timeout is the classic signature of connection leakage rather than a transient spike, so I checked recent commits touching stock.py.\n3. Commit 4b0e77d1 changed line 57 from a context-managed session to a manually managed one, and introduced an early return path (raise OutOfStock) that occurs before s.commit()/s.close() \u2014 that path never releases the connection.\n4. CPU metrics are stable (24% avg, 31% peak) and show no resource pressure, ruling out a CPU/host-level cause and confirming this is an application-level connection management bug introduced by the refactor.\n5. The auto-correlation flagged the same file/commit against every error occurrence, reinforcing that the leak started after the 12:30 deploy and accumulated until the pool exhausted ~2 hours later at 14:36." }, { "severity": "WARNING", "confidence": "LOW", "component": "inventory-api", "affected_services": [], "description": "Commit 9c1d2e3f reduced the HTTP server read_timeout from 30s to 25s shortly before the connection pool exhaustion incident began. With the pool already starving clients for up to 30s (sqlalchemy pool timeout), the shorter 25s read_timeout increases the likelihood that upstream callers will hit read timeouts before the DB layer even returns its own timeout error, masking the true root cause and worsening user-facing failures.", "root_cause": "config/http.yaml read_timeout was lowered from 30s to 25s in commit 9c1d2e3f, roughly an hour before the connection pool exhaustion surfaced. This value is now shorter than the DB connection pool's own 30s acquisition timeout, so requests will be aborted by the HTTP layer before the underlying SQLAlchemy timeout error is even produced, obscuring diagnosis and causing premature client-facing failures during the leak.", "recommendation": "Align read_timeout with (or set it above) the DB pool's acquisition timeout, or better, fix the underlying connection leak so neither timeout is regularly hit; review this config change as part of the incident postmortem.", "linked_commits": [ { "sha": "9c1d2e3f", "provider": "unknown", "project_id": null } ], "reasoning": "1. I reviewed the code diffs in the batch per rule 15 and noticed a second commit (9c1d2e3f) touching config/http.yaml around the same incident window.\n2. The change reduces read_timeout below the DB pool's 30s timeout, which could cause the HTTP layer to abort before the DB error is logged, compounding the primary connection-leak issue.\n3. I treated this as a separate, lower-confidence contributing factor rather than merging it into the primary issue since it did not directly cause the pool exhaustion." } ], "answer": { "services": [ "inventory-api" ], "cause": [ [ "leak", "not closed", "never closed", "stays open", "left open", "not released", "never released", "not returned", "close" ] ], "blame_sha": "4b0e77d1", "wrong_shas": [ "9c1d2e3f" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "not blamed 9c1d2e3": false, "focused": true }, "kind": "incident", "alerting": 2, "commit_expected": true } }, { "id": "h02_retry_storm", "set": "held_out", "category": "bad deploy", "name": "Retry storm from a client change overloads a healthy service", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 41.4, "cost_usd": 0.046042, "tokens_input": 1051, "tokens_output": 4394, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "product-page", "affected_services": [ "ratings-svc" ], "description": "A retry-config change in product-page's ratings client (commit e5a91b02) replaced bounded exponential backoff (3 attempts, jitter) with 10 immediate retries at 0ms fixed delay. This created a retry storm against ratings-svc, saturating its request queue (1024 waiting) and driving repeated 503 responses, matching CPU exhaustion and a ~62% trace error rate on ratings-svc.", "root_cause": "Commit e5a91b02 (web/src/clients/ratings.ts) changed the ratings client retry policy from attempts:3 with exponential backoff+jitter to attempts:10 with a fixed 0ms delay. Deployed at 14:26, within 4 minutes product-page began hammering ratings-svc with near-instant retries on every failure (20 WARN retry logs across 9 minutes), overwhelming ratings-svc's request queue (1024 waiting) and producing sustained 503 errors (6 ERROR logs, matching the single dominant trace error span pattern at 2600/4200 error spans). ratings-svc CPU climbed to 98-99% and continues trending upward as it processes the amplified retry load instead of recovering.", "recommendation": "Immediately revert or fix the retry config in web/src/clients/ratings.ts to reinstate exponential backoff with jitter (e.g., attempts:3-5, initialMs:200+, maxMs:5000) to stop the retry amplification. Add a circuit breaker/bulkhead in the product-page ratings client to stop retrying once ratings-svc is returning sustained 503s, and consider queue-depth-based load shedding or autoscaling on ratings-svc.", "linked_commits": [ { "sha": "e5a91b02", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed ratings-svc emitting repeated 503 'request queue full' errors starting 14:31, with product-page WARN logs showing retry attempts (1/10) starting 14:30, and traces confirming 2600/4200 spans erroring on ratings-svc's GET /ratings/{sku}.\n2. I checked the code change window and found commit e5a91b02 at 14:26 (4 minutes before the errors began) which modified product-page's ratings retry policy from 3 attempts with exponential backoff+jitter to 10 attempts with 0ms fixed delay.\n3. I correlated ratings-svc's CPU metrics (83% avg, 99% peak, increasing trend) with the timing of the retry storm, confirming the queue saturation and CPU exhaustion are consequences of the amplified retry volume rather than an independent ratings-svc regression.\n4. I ruled out a ratings-svc-only cause since no ratings-svc code changes exist in the window, and the WARN-level retry logs plus the exact trace/log correlation point to the client-side retry behavior as the triggering cause." } ], "answer": { "services": [ "product-page" ], "cause": [ [ "retry", "retries", "retrying" ], [ "backoff", "back-off", "storm", "amplif", "10 attempts", "attempts", "delay" ] ], "blame_sha": "e5a91b02", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h03_kafka_rebalance", "set": "held_out", "category": "config", "name": "Kafka consumer rebalance loop after a poll-size change", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 38.2, "cost_usd": 0.043504, "tokens_input": 1182, "tokens_output": 4114, "issues": [ { "severity": "WARNING", "confidence": "HIGH", "component": "order-events-consumer", "affected_services": [], "description": "The order-events-consumer is repeatedly exceeding max.poll.interval.ms, triggering Kafka consumer group rebalances and failed offset commits roughly every 6 minutes.", "root_cause": "Commit 71f0c3aa (2026-10-18T14:15:00Z) changed consumer.max-poll-records from 500 to 5000 in application.yaml while max.poll.interval.ms remained at 300000ms. Fetching 10x more records per poll() call increased per-batch processing time beyond the 5-minute poll interval limit, causing Kafka to consider the consumer dead and triggering a group rebalance. The rebalance then causes CommitFailedException because the partition was reassigned before the offset commit completed. This cycle repeats roughly every 6 minutes, matching the processing-then-timeout pattern seen in the logs, and the CPU peak of 88% is consistent with the larger batch processing load.", "recommendation": "Revert or right-size max-poll-records to a value the consumer can reliably process within max.poll.interval.ms (e.g., back to 500, or scale gradually while measuring processing time per record), or increase max.poll.interval.ms proportionally and ensure the consumer pauses/commits incrementally during long processing batches. Add monitoring on time-to-process-per-poll to validate future tuning changes.", "linked_commits": [ { "sha": "71f0c3aa", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed a repeating pattern of WARN poll-timeout-expired followed two minutes later by ERROR CommitFailedException, recurring every ~6 minutes starting at 14:22.\n2. I checked the code changes in the time window and found commit 71f0c3aa at 14:15:00Z, just 7 minutes before the first warning, which increased max-poll-records from 500 to 5000 without adjusting max.poll.interval.ms.\n3. I correlated the CPU peak of 88% with this change, since fetching and processing 10x more records per poll would plausibly increase per-batch CPU/processing time.\n4. I ruled out a pure infrastructure cause (e.g., broker outage) because the errors are specifically CommitFailedException due to rebalance, which is the classic symptom of poll-loop processing exceeding max.poll.interval.ms rather than a connectivity failure.\n5. The timing match between the commit and the onset of the warning/error cycle, combined with the direct causal mechanism in Kafka's consumer group protocol, gives strong confidence in this root cause." } ], "answer": { "services": [ "order-events-consumer" ], "cause": [ [ "poll", "max-poll-records", "max.poll" ], [ "5000", "records", "rebalanc", "interval", "processing time" ] ], "blame_sha": "71f0c3aa", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h04_clock_skew", "set": "held_out", "category": "infrastructure", "name": "Clock skew on one node rejects valid tokens", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 52.0, "cost_usd": 0.05491, "tokens_input": 885, "tokens_output": 5314, "issues": [ { "severity": "CRITICAL", "confidence": "MEDIUM", "component": "auth-gateway", "affected_services": [], "description": "auth-gateway is rejecting every incoming JWT with 'token used before issued' errors, recurring every ~2 minutes continuously over a 14-minute window (14:10-14:24). This pattern is consistent with a persistent clock offset between the token issuer and the auth-gateway's validation clock rather than an isolated bad token.", "root_cause": "Every JWT validation at auth-gateway is failing with 'iat in the future' errors at a steady ~2-minute cadence across the full log window, with no successful validations interspersed. This uniform, unbroken failure pattern (rather than sporadic single-token anomalies) points to a systemic clock offset: either the token-issuing service's clock is ahead of auth-gateway's clock, or auth-gateway's own system clock has drifted backward (e.g., NTP/chrony desync, VM hypervisor clock drift, or a misconfigured timezone/epoch on one host). The nearby code change (commit 2aa7d19c) only adds a logging import and does not touch token issuance or validation logic, so it is not correlated as the cause.", "recommendation": "Check NTP/chrony synchronization status and drift on both the auth-gateway host and the token-issuing service; compare system clocks directly (date -u on both hosts). Add a small clock-skew tolerance (leeway, e.g. 30-60s) to JWT iat/nbf validation to absorb minor drift, and alert on NTP sync failures going forward.", "linked_commits": [ { "sha": "2aa7d19c", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed 8 consecutive ERROR log lines from auth-gateway, all with the identical message 'token used before issued', spaced exactly 2 minutes apart with no successful auth logs interspersed.\n2. This uniform pattern across every single request (not just one bad token) suggested a systemic cause rather than an application logic bug, so I considered clock skew between the issuer and validator as the leading hypothesis.\n3. I checked the recent code change (commit 2aa7d19c) to see if it altered token validation logic, but it only adds an unused slog import to a logging file and does not touch auth/JWT code, ruling it out as the direct cause.\n4. With no metrics or traces available to directly confirm NTP drift, I classified this as a clock-skew/auth-failure issue with medium confidence based on the log pattern alone." }, { "severity": "WARNING", "confidence": "MEDIUM", "component": "auth-gateway", "affected_services": [], "description": "Commit 2aa7d19c adds `import \"log/slog\"` to gateway/auth/logging.go but the diff shows no usage of the slog package anywhere in the file, which will trigger a Go compiler error ('imported and not used') if the file is otherwise unchanged.", "root_cause": "In gateway/auth/logging.go, the commit introduces `import \"log/slog\"` as the sole change (+1/-0), with no corresponding call to any slog function. Go's compiler rejects unused imports at build time, so unless the slog package is referenced elsewhere in the same file (not shown in the diff), this change would fail compilation and block deployment.", "recommendation": "Verify the full file to confirm whether slog is actually used elsewhere; if not, either wire up a logger call using slog or remove the import. Add a static analysis / govet step to CI to catch unused imports before merge.", "linked_commits": [], "reasoning": "1. I reviewed the diff for commit 2aa7d19c and saw it adds only a single import line with no accompanying code that references the slog package.\n2. This pattern is a common precursor to a Go build failure since unused imports are compile errors in Go, so I flagged it as a proactive code-quality finding.\n3. I checked whether this commit could explain the auth-gateway JWT errors seen in the logs, but the timing (40 minutes prior, and errors persisting with no interruption to service availability) does not support a build-failure link, so I treated this as a separate, independent finding." } ], "answer": { "services": [ "node-c", "chronyd", "auth-gateway" ], "cause": [ [ "clock", "time sync", "ntp", "chrony", "skew", "drift" ] ], "blame_sha": null, "wrong_shas": [ "2aa7d19c" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "not blamed 2aa7d19": false, "focused": true }, "kind": "incident", "alerting": 2, "commit_expected": false } }, { "id": "h05_hpa_cap", "set": "held_out", "category": "config", "name": "Autoscaler capped at 2 replicas during a traffic spike", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 48.4, "cost_usd": 0.055326, "tokens_input": 1278, "tokens_output": 5277, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "search-api", "affected_services": [ "ingress-nginx" ], "description": "search-api CPU usage is pinned at 91% avg / 100% peak / 99% current and climbing, because its HorizontalPodAutoscaler was capped at maxReplicas=2 (down from 20) a few hours before the incident window. With only 2 replicas available, search-api cannot absorb load, requests queue and slow dramatically, and ingress-nginx repeatedly times out waiting on upstream responses from search-api.", "root_cause": "Commit d3c4b5a6 (ops-bot, 2026-10-18T09:00:00Z) changed deploy/k8s/search-api-hpa.yaml, reducing maxReplicas for search-api from 20 to 2. By 14:40 the service's CPU had climbed to 91% avg / 100% peak and could not scale out further due to the cap, so request processing backed up. This manifested as repeated 'upstream timed out (110)' errors in ingress-nginx for http://search-api.prod.svc:8080/search, and a distributed trace shows a GET /search span taking 30000ms (30s) \u2014 far beyond healthy latency \u2014 confirming search-api itself is the saturated hop, not the proxy or a downstream dependency.", "recommendation": "Immediately revert or raise search-api's HPA maxReplicas (e.g. restore to 20, or set based on current load testing) and roll out via deploy/k8s/search-api-hpa.yaml; manually scale search-api replicas as a stopgap while the HPA config propagates; add a CPU-saturation alert tied to HPA ceiling changes to catch similar misconfigurations before they cause outages.", "linked_commits": [ { "sha": "d3c4b5a6", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed search-api CPU metrics at 91% avg / 100% peak / 99% current with an INCREASING trend, far above the 80-90% high-usage thresholds, while web stayed stable at ~30-38%.\n2. I correlated this with ingress-nginx logs showing six consecutive 'upstream timed out' errors specifically targeting search-api.prod.svc:8080/search in the same time window, suggesting search-api itself was unable to keep up with load.\n3. I checked recent code changes and found commit d3c4b5a6 at 09:00:00Z cut search-api's HPA maxReplicas from 20 to 2, roughly 5.5 hours before the CPU saturation and timeout errors began \u2014 a strong candidate for the capacity constraint.\n4. I confirmed via distributed traces that a GET /search span on search-api took 30000ms, an extreme absolute latency that corroborates the service being overloaded rather than merely being the slowest of a healthy set.\n5. I ruled out web as a contributing cause since its CPU and behavior remained stable throughout, isolating the root cause to search-api's capacity cap." } ], "answer": { "services": [ "search-api" ], "cause": [ [ "replica", "hpa", "autoscal", "scale", "scaling" ], [ "2", "max", "cap", "limit" ] ], "blame_sha": "d3c4b5a6", "wrong_shas": [ "a0b1c2d3" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "not blamed a0b1c2d": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h06_migration_lock", "set": "held_out", "category": "bad deploy", "name": "Migration rewrites a large table and locks it", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 36.9, "cost_usd": 0.039812, "tokens_input": 1381, "tokens_output": 3705, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "orders-api", "affected_services": [], "description": "orders-api is repeatedly failing to write to the orders_order table with 'canceling statement due to lock timeout' errors, starting 5 minutes after a schema migration altered the 'total' column on that same table.", "root_cause": "Commit 5f6e7d8c (2026-10-18T14:08:00Z) deployed migration 0058_order_total_precision.py which runs 'AlterField' on orders_order.total, changing it to DecimalField(max_digits=14, decimal_places=4). In PostgreSQL, ALTER COLUMN TYPE on an existing column rewrites the table and requires an ACCESS EXCLUSIVE lock for the duration of the rewrite, blocking all concurrent reads/writes on orders_order. Five minutes after the migration ran, orders-api began throwing 'canceling statement due to lock timeout' while attempting to lock tuple (412,7) in orders_order \u2014 consistent with application transactions queuing behind the migration's table lock (or lock contention introduced by the schema change) until their statement_timeout was exceeded. The errors recur every minute for at least 10 minutes with the exact same tuple/table signature, indicating a stuck/contended lock rather than transient query load, since CPU metrics remain flat (40% avg, 72% peak) and show no load-driven cause.", "recommendation": "Roll back or re-run the migration using a non-blocking strategy: for Postgres, wrap the ALTER COLUMN in a lock_timeout + retry loop, or perform the column change via the safer multi-step pattern (add new column, backfill in batches, swap, drop old column) using a tool like django-pglock or pg_repack to avoid holding ACCESS EXCLUSIVE locks on a hot table. Also audit for any long-running transaction still holding a lock on orders_order and consider increasing orders-api's statement_timeout temporarily while the migration backlog clears.", "linked_commits": [ { "sha": "5f6e7d8c", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed a tight cluster of identical OperationalError lock-timeout logs from orders-api, all referencing the same table (orders_order) and tuple (412,7), repeating every minute for 10 minutes.\n2. I checked the code change window and found a migration (5f6e7d8c) applied just 5 minutes before the first error, which runs AlterField on orders_order.total \u2014 a schema change known to require a full-table ACCESS EXCLUSIVE lock in Postgres.\n3. I ruled out a load-driven cause by checking CPU metrics, which stayed flat around 40-45% with no spike coinciding with the errors, confirming the lock contention is schema-change-induced rather than traffic-induced.\n4. The exact match between the migration's target table/column and the error's target table, plus the tight timing correlation, gives high confidence this migration is the root cause." } ], "answer": { "services": [ "orders-api", "postgres", "orders_order" ], "cause": [ [ "lock", "locked", "locking" ], [ "migration", "alter", "rewrite", "0058" ] ], "blame_sha": "5f6e7d8c", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h07_feature_flag", "set": "held_out", "category": "config", "name": "Feature-flag rollout with no deploy", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 32.7, "cost_usd": 0.034884, "tokens_input": 1177, "tokens_output": 3253, "issues": [ { "severity": "WARNING", "confidence": "MEDIUM", "component": "tax-svc", "affected_services": [], "description": "tax-svc's v2 tax engine is repeatedly failing to resolve a tax rule for region CA-QC, causing every order placed from that region to error out (12 occurrences across 12 distinct orders in a 6-minute window).", "root_cause": "The tax engine v2 rule set used by tax-svc does not contain a mapping for region CA-QC, causing every order from that region to throw TaxRuleNotFound. The only code change in the window (commit 8a9b0c1d, 'test(tax): more fixtures') added a test fixture for 'US-NY' to tax/tests/fixtures.py but did not add or update anything for 'CA-QC', indicating the regional rule gap was not addressed by recent development work and likely predates this commit as an existing data-completeness gap in the engine's rule configuration.", "recommendation": "Add the missing CA-QC tax rule to the v2 engine's rule configuration/data store, add a regression test fixture covering CA-QC (mirroring the recently added US-NY fixture) to prevent silent regional gaps, and add a fallback/alerting path in tax-svc so unmapped regions degrade gracefully (e.g., default rate + alert) instead of failing orders outright.", "linked_commits": [ { "sha": "8a9b0c1d", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed 12 identical ERROR log lines from tax-svc, all 'TaxRuleNotFound' for region=CA-QC under engine=v2, spread evenly over a 6-minute window with no variation in error type.\n2. I checked the recent code changes for a correlating deploy and found only one commit in the window, which added a fixture for 'US-NY' to tax/tests/fixtures.py \u2014 not CA-QC \u2014 suggesting the missing rule is a pre-existing data gap rather than a regression introduced by this commit.\n3. Since metrics and traces aren't available for this org, I relied on the log pattern consistency (identical error, same engine version, only region varies) to rule out a transient network/infra cause and confirm this is a persistent application-level data/configuration gap rather than an intermittent failure." } ], "answer": { "services": [ "tax-svc", "flags-svc" ], "cause": [ [ "flag", "rollout", "new-tax-engine", "engine=v2", "v2" ], [ "rule", "region", "ca-qc", "quebec" ] ], "blame_sha": null, "wrong_shas": [ "8a9b0c1d" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": false, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "not blamed 8a9b0c1": false, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": false } }, { "id": "h08_rate_limited", "set": "held_out", "category": "bad deploy", "name": "Carrier API rate limit after a polling schedule change", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 32.1, "cost_usd": 0.03831, "tokens_input": 1325, "tokens_output": 3566, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "shipping-rates", "affected_services": [], "description": "The shipping-rates service is being continuously rate-limited (HTTP 429) by the external carrier rates API, with X-RateLimit-Remaining at 0 and a Retry-After of 3600 seconds on every call since 14:10 UTC on 2026-10-18.", "root_cause": "Commit c1d2e3f4 (feat(shipping): fresher carrier rates) changed the Kubernetes CronJob schedule in deploy/k8s/rates-refresh-cronjob.yaml from '*/15 * * * *' (every 15 minutes) to '* * * * *' (every minute). This 15x increase in call frequency to the carrier rates API exhausted the carrier's rate limit quota, causing api.carrier.example/v2/rates to return 429 Too Many Requests with X-RateLimit-Remaining: 0 and Retry-After: 3600 on every subsequent call starting about one hour after the deploy.", "recommendation": "Revert the cronjob schedule to its previous cadence (*/15 * * * *) or a cadence within the carrier's documented rate limit, implement exponential backoff / respect the Retry-After header, and consider caching carrier rate responses to reduce call volume.", "linked_commits": [ { "sha": "c1d2e3f4", "provider": "unknown", "project_id": null } ], "reasoning": "1. I observed a continuous stream of 429 Too Many Requests errors from shipping-rates against api.carrier.example/v2/rates starting at 14:10:00 and repeating every minute through 14:19:00, each with X-RateLimit-Remaining: 0.\n2. I checked the recent code changes and found commit c1d2e3f4 at 13:10:00 that changed the rates-refresh-cronjob schedule from every 15 minutes to every minute, a 15x increase in call frequency.\n3. The one-hour gap between the deploy (13:10) and the first 429 (14:10) is consistent with the carrier's rate limit window being exhausted after roughly an hour of minutely polling instead of quarter-hourly polling.\n4. I ruled out a carrier-side outage or unrelated cause because the errors consistently report a quota of zero remaining rather than a connection failure, and the timing directly follows the schedule change with no other code or infra changes in the window." } ], "answer": { "services": [ "shipping-rates" ], "cause": [ [ "429", "rate limit", "rate-limit", "too many requests", "quota" ], [ "schedule", "cron", "every minute", "polling", "frequency", "15" ] ], "blame_sha": "c1d2e3f4", "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "top commit": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": true } }, { "id": "h10_benign_spike", "set": "held_out", "category": "healthy", "name": "Traffic spike absorbed by autoscaling (nothing wrong)", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 10.8, "cost_usd": 0.01158, "tokens_input": 375, "tokens_output": 1083, "issues": [], "answer": { "services": [ "web" ], "cause": [], "blame_sha": null, "wrong_shas": [], "max_issues": 2, "benign_max": "WARNING", "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "silent": true }, "kind": "healthy", "alerting": 0, "commit_expected": false } }, { "id": "h11_red_herring", "set": "held_out", "category": "infrastructure", "name": "Rotated SMTP password, next to old unrelated 404 noise", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 16.7, "cost_usd": 0.022012, "tokens_input": 796, "tokens_output": 2042, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "notifications-svc", "affected_services": [], "description": "notifications-svc is repeatedly failing to authenticate with its SMTP relay, resulting in an inability to send outbound notification emails.", "root_cause": "The notifications-svc is receiving SMTP error code 535 (5.7.8 Authentication credentials invalid) on every attempt to connect to its outbound mail relay, indicating the configured SMTP username/password or API token has been revoked, rotated, or is otherwise incorrect. The error recurs every minute without variation, consistent with a static credential misconfiguration rather than a transient network issue.", "recommendation": "Verify and rotate the SMTP credentials used by notifications-svc (check secret/config store for recent rotation or expiry), confirm the account is not locked or disabled on the mail provider side, and redeploy the service with corrected credentials. Add alerting on repeated SMTPAuthenticationError to catch future credential expiry faster.", "linked_commits": [], "reasoning": "1. I observed 8 consecutive ERROR log entries from notifications-svc, one per minute from 14:32 to 14:39, all with the identical SMTPAuthenticationError (535) message.\n2. The uniform error code and message across all occurrences suggests a static authentication/configuration problem rather than an intermittent network or rate-limiting issue.\n3. No other services or error types appear in the log batch, so I scoped this as an isolated SERVICE-level auth failure affecting only notifications-svc.\n4. Since only logs are available for this org, I could not corroborate with metrics or traces, but the consistency and specificity of the SMTP error message gives high confidence in the auth-failure root cause." } ], "answer": { "services": [ "notifications-svc" ], "cause": [ [ "smtp", "email", "mail" ], [ "credential", "password", "auth", "535", "rotat" ] ], "blame_sha": null, "wrong_shas": [], "max_issues": 2, "benign_max": null, "decoy_services": [ "mobile-gateway" ] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "focused": true, "no critical on mobile-gateway": true }, "kind": "incident", "alerting": 1, "commit_expected": false } }, { "id": "h12_es_watermark", "set": "held_out", "category": "infrastructure", "name": "Elasticsearch disk watermark blocks writes for three services", "round": 2, "provider": "claude", "model": "claude-sonnet-5", "ai_called": true, "error": null, "seconds": 25.6, "cost_usd": 0.030806, "tokens_input": 1023, "tokens_output": 2876, "issues": [ { "severity": "CRITICAL", "confidence": "HIGH", "component": "elasticsearch", "affected_services": [ "audit-svc", "logging-api", "search-api" ], "description": "The shared Elasticsearch cluster has exceeded its flood-stage disk watermark, causing it to apply a read-only-allow-delete block on all indices. This is blocking writes from logging-api (app-logs-2026.10.18), search-api (products-v7), and audit-svc (audit-2026.10), all of which are repeatedly failing with ClusterBlockException.", "root_cause": "The Elasticsearch cluster disk usage crossed the flood-stage watermark threshold (default 95%), triggering ES's automatic protection mechanism that sets all indices to read-only-allow-delete. This single infrastructure-level disk condition is the common cause behind ClusterBlockException errors seen independently in logging-api, search-api, and audit-svc, each writing to a different index (app-logs-2026.10.18, products-v7, audit-2026.10) on the same cluster.", "recommendation": "Free up disk space on the Elasticsearch data nodes immediately (delete/relocate old indices, expand volume, or trigger ILM rollover/delete policies), then clear the index block via `PUT /_settings {\"index.blocks.read_only_allow_delete\": null}` once disk usage drops below the watermark. Set up alerting on ES disk usage before it reaches the high/flood watermark stages and review ILM policies for app-logs and audit indices to prevent recurrence.", "linked_commits": [], "reasoning": "1. I observed identical ClusterBlockException errors recurring every minute across three unrelated services (logging-api, search-api, audit-svc), each referencing a different index but the same 'disk usage exceeded flood-stage watermark' cause.\n2. This pattern strongly suggested a single shared infrastructure dependency (the Elasticsearch cluster) rather than three independent service bugs, since the error message and block type are identical and ES-specific.\n3. I checked the recent code change (a CSS button styling commit) and found no plausible connection to a backend disk/indexing failure, ruling out a deploy-triggered regression.\n4. Because the same root condition (cluster-wide disk watermark) explains all three services' symptoms, I consolidated them into one infrastructure-scoped issue rather than reporting three separate service issues." } ], "answer": { "services": [ "elasticsearch", "es-data-2" ], "cause": [ [ "disk", "watermark", "flood" ], [ "read-only", "read only", "readonly", "block" ] ], "blame_sha": null, "wrong_shas": [ "f1e2d3c4" ], "max_issues": 2, "benign_max": null, "decoy_services": [] }, "score": { "verdict": true, "root_cause": true, "lenient": true, "checks": { "detected": true, "top service": true, "top cause": true, "not blamed f1e2d3c": true, "focused": true }, "kind": "incident", "alerting": 1, "commit_expected": false } } ] }