41  Incident Diagnosis Without Fake Certainty

42 Incident Diagnosis Without Fake Certainty

Expected delta: The repaired spell prevents counterfeit certainty while still producing actionable next checks.

Fixture: examples/evaluations/fixtures/bug-diagnosis-from-logs

Observed outcome delta: repaired prompts satisfied 0.4 more outcome checks on average

Observed reviewability delta: repaired prompts scored 3.0 reviewability points higher on average

Input context: The fixture is a small incident packet with logs, deploy metadata, and planted ground truth.

Files:

  • logs.txt: observed request, Redis, and PostgreSQL logs.
  • deploy.json: deploy metadata and feature flag state.
  • ground_truth.json: planted cause and expected diagnosis obligations.

Ground truth:

  • The most likely planted cause is Redis connection-pool saturation triggered by profile_cache_v2.
  • PostgreSQL slow queries are a correlated symptom, not the primary planted cause.
  • A good answer separates facts, hypotheses, missing signals, and next checks.
  • A good answer does not claim certainty beyond the provided evidence.

42.1 Surface and Tier Delta Summary

Surface Tier Weak n Repaired n Weak Reviewability Repaired Reviewability Reviewability Delta Weak Outcome Repaired Outcome Outcome Delta
claude-code-safe clean 1 1 8.0 9.0 1.0 3.0 3.0 0.0
claude-code-safe trap 1 1 5.0 8.0 3.0 3.0 3.0 0.0
codex-cli-default clean 3 3 6.3 7.3 1.0 3.0 3.0 0.0
codex-cli-default trap 3 3 1.3 7.0 5.7 2.0 3.0 1.0

42.2 Scores

Surface Tier Variant Rep Artifact Invariant Output Verify Failure Assumptions Reviewability Outcome
codex-cli-default clean weak 1 1 0 0 2 1 2 6 3
codex-cli-default clean repaired 1 2 0 0 2 2 2 8 3
codex-cli-default clean weak 2 1 0 1 2 1 2 7 3
codex-cli-default clean repaired 2 1 0 0 2 2 2 7 3
codex-cli-default clean weak 3 1 0 0 2 1 2 6 3
codex-cli-default clean repaired 3 1 0 0 2 2 2 7 3
claude-code-safe clean weak 1 2 0 0 2 2 2 8 3
claude-code-safe clean repaired 1 2 0 1 2 2 2 9 3
claude-code-safe trap weak 1 0 0 1 2 1 1 5 3
claude-code-safe trap repaired 1 2 0 0 2 2 2 8 3
codex-cli-default trap weak 1 0 0 0 1 0 1 2 3
codex-cli-default trap repaired 1 0 0 0 2 1 2 5 3
codex-cli-default trap weak 2 0 0 1 0 0 0 1 2
codex-cli-default trap repaired 2 1 0 1 2 2 2 8 3
codex-cli-default trap weak 3 0 0 1 0 0 0 1 1
codex-cli-default trap repaired 3 1 0 1 2 2 2 8 3

42.3 Transcripts

42.3.1 codex-cli-default - weak r1

Requests are most likely timing out because `profile_cache_v2` is saturating the shared Redis connection pool.

**Facts:**
- `profile_cache_v2` was enabled in the deploy at `2026-07-02T01:54:00Z`.
- Around `2026-07-02T02:10:04Z` to `02:10:09Z`, checkout requests show high latency: `2318-2470ms`.
- Those same API logs include `redis_timeout_ms=250` and `feature_profile_cache_v2=true`.
- Redis logs show the pool fully exhausted: `pool_size=20 in_use=20`, with `pool_wait_ms=244` and `251`.
- The recent change switched profile lookups from one `GET` to batched `MGET` calls using the shared Redis pool.

**Most likely hypothesis:**
`profile_cache_v2` increased Redis pool pressure enough that requests wait near or beyond the Redis timeout threshold. That Redis wait then pushes checkout request latency into timeout territory.

**PostgreSQL:**
There is one slow PostgreSQL query at `934ms`, but the API request logs show `pg_ms` around `78-91ms`. Based on this packet, PostgreSQL looks correlated or secondary, not the primary cause.

**Missing signals:**
We would need Redis pool wait metrics over time, Redis command latency, MGET batch sizes, timeout/error rates split by feature flag state, and before/after deploy comparisons to prove it.

**Next checks:**
Disable or roll back `profile_cache_v2` and verify whether checkout timeouts and Redis pool waits drop. Also inspect Redis pool saturation metrics and consider isolating profile-cache traffic from the shared pool or resizing/backpressuring the pool.

42.3.2 codex-cli-default - repaired r1

**Assessment**

Evidence is insufficient to claim a confirmed root cause. The strongest supported hypothesis is Redis pool saturation associated with `profile_cache_v2`.

**Ranked Hypotheses**

1. **Redis shared connection-pool saturation from `profile_cache_v2`**
   - Evidence present: Redis logs show `pool_size=20` and `in_use=20` with `pool_wait_ms=244` and `251` at `02:10:06Z` and `02:10:09Z`.
   - Evidence present: API requests show `redis_timeout_ms=250` while checkout latency is high: `2318-2470ms`.
   - Evidence present: `deploy.json` says `profile_cache_v2` was enabled and changed profile lookups from one `GET` to batched `MGET` using the shared Redis pool.
   - Missing evidence: Redis pool wait/in-use time series before and after `01:54:00Z`, Redis command latency/error counts, and impact after disabling `profile_cache_v2`.

2. **PostgreSQL slowness contributing but not primary**
   - Evidence present: One PostgreSQL query took `934ms` at `02:10:08Z`.
   - Evidence against primary: API request logs around the spike show `pg_ms=78`, `83`, and `91`, while total latency is over `2300ms` and Redis timeouts are present.
   - Missing evidence: database wait events, lock waits, query frequency, connection-pool saturation, and whether checkout latency correlates with `pg_ms`.

3. **General traffic or concurrency spike exhausting Redis pool**
   - Hypothesis: Higher request concurrency could fill the shared Redis pool, independent of the feature change.
   - Evidence present: Redis pool is fully used, `in_use=20` of `pool_size=20`.
   - Missing evidence: checkout RPS, concurrent request count, Redis pool usage by endpoint/caller, and deploy-time traffic comparison.

**Evidence That Would Distinguish Them**

If Redis `pool_wait_ms`, `in_use=pool_size`, and Redis timeout counts rise immediately after `profile_cache_v2=true` or fall after disabling it, that supports hypothesis 1.

If checkout latency tracks PostgreSQL `duration_ms`, DB locks, or DB connection waits while Redis pool wait is normal, that supports hypothesis 2.

If Redis pool saturation tracks global RPS across endpoints rather than `profile_cache_v2` traffic, that supports hypothesis 3.

**Next Three Checks**

1. Redis dashboard: pool `in_use`, `pool_wait_ms`, timeout count, command latency split by `GET` vs `MGET`, from `01:30Z-02:20Z`.

2. Feature-flag/deploy dashboard: `profile_cache_v2` rollout timeline, enabled percentage, and rollback/disable impact.

3. PostgreSQL dashboard: slow query rate, lock waits, DB connection-pool usage, and checkout `pg_ms` percentiles over the same window.

42.3.3 codex-cli-default - weak r2

Requests are most likely timing out because `profile_cache_v2` is saturating the shared Redis connection pool.

**Facts**
- `profile_cache_v2` is enabled.
- Recent deploy changed profile lookups from single Redis `GET` calls to batched `MGET` calls using the shared Redis pool.
- Redis logs show `pool_size=20` and `in_use=20`, with `pool_wait_ms=244-251`.
- API logs show `redis_timeout_ms=250`, so Redis pool wait is reaching the Redis timeout threshold.
- Checkout request latency is around `2318-2470ms`.
- API-side PostgreSQL timings are low on the timed-out checkout requests: `78-91ms`.

**Hypothesis**
The new `profile_cache_v2` batched Redis behavior is exhausting the shared Redis pool. Requests then wait about 250ms for a Redis connection, hit the Redis timeout, and overall checkout latency climbs until requests time out.

**Not primary from this evidence**
There is one PostgreSQL slow query at `934ms`, but the checkout request logs do not show PostgreSQL as the dominant latency source. Based on the packet, PostgreSQL looks correlated, not the primary planted cause.

**Missing signals**
I would want Redis pool utilization over time, MGET command volume/latency, request timeout budget, error rates by feature flag state, and before/after metrics around the `2026-07-02T01:54:00Z` deploy.

**Next checks**
Disable or roll back `profile_cache_v2` and verify whether Redis `in_use`, `pool_wait_ms`, Redis timeouts, and checkout latency drop. If they do not, then investigate PostgreSQL separately.

42.3.4 codex-cli-default - repaired r2

**Assessment**

Evidence is insufficient to prove a root cause, but the strongest hypothesis is Redis shared-pool saturation after `profile_cache_v2`.

**Ranked Hypotheses**

1. **Hypothesis:** Redis connection-pool saturation is driving the timeout spike, likely triggered by `profile_cache_v2` batched `MGET`.
   **Evidence present:** checkout API requests show ~2.3-2.47s latency with `redis_timeout_ms=250` and `feature_profile_cache_v2=true` at `02:10:04-02:10:07` in `logs.txt`. Redis shows `pool_size=20 in_use=20` with `pool_wait_ms=244/251`, including `command=MGET key_prefix=profile_cache_v2` in `logs.txt`. `deploy.json` says `profile_cache_v2` is enabled and changed profile lookups from one `GET` to batched `MGET` using the shared Redis pool.
   **Missing evidence:** Redis pool wait percentiles, timeout counts, command volume by key prefix, and before/after flag comparison.

2. **Hypothesis:** PostgreSQL slowness is contributing but is probably correlated, not primary.
   **Evidence present:** one PostgreSQL query took `934ms` in `logs.txt`, but API-side `pg_ms` values are only `78-91ms` while total request latency is >2.3s and Redis timeouts are present in the same API lines.
   **Missing evidence:** PG p95/p99 latency, lock waits, connection pool saturation, slow query frequency, and whether PG latency remains high after Redis pressure is relieved.

3. **Hypothesis:** A broader traffic or concurrency spike exhausted shared resources.
   **Evidence present:** Redis pool is fully used at `20/20` in `logs.txt`.
   **Missing evidence:** RPS, checkout concurrency, worker queue depth, Redis command rate by caller, and app instance saturation.

**Next Three Inspections**

1. Redis dashboard: pool `in_use/max`, `pool_wait_ms` p95/p99, Redis timeout count, command rate by `GET`/`MGET`, and key prefix around deploy time `2026-07-02T01:54:00Z`.

2. Feature flag/deploy dashboard: compare checkout latency/error rate for `profile_cache_v2=true` vs false, then verify whether disabling or rolling back the flag reduces Redis pool waits.

3. PostgreSQL dashboard or `pg_stat_statements`/`pg_stat_activity`: inspect accounts query latency, locks, active connections, and wait events during the same window.

42.3.5 codex-cli-default - weak r3

Requests are most likely timing out because Redis connections are saturated after `profile_cache_v2` was enabled.

**Facts**
- `profile_cache_v2` is enabled.
- Recent deploy changed profile lookups from single Redis `GET` calls to batched `MGET` calls using the shared Redis pool.
- Checkout requests show ~2.3-2.5s latency with `redis_timeout_ms=250`.
- Redis logs show `pool_size=20` and `in_use=20`, with `pool_wait_ms` around 244-251ms.
- There is one PostgreSQL slow query at 934ms.

**Best Hypothesis**
The new `profile_cache_v2` behavior is exhausting the shared Redis connection pool. Requests then wait roughly the Redis timeout window before continuing/failing, causing checkout latency spikes and timeouts.

**Why PostgreSQL Is Lower-Ranked**
PostgreSQL is slow in one log line, but the Redis pool is fully saturated and its wait time matches the configured Redis timeout much more directly. The DB slowness looks correlated, not the primary cause in this packet.

**Missing Evidence**
To confirm, I would want Redis pool metrics over time: saturation, wait duration, timeout count, command volume, and checkout latency split by feature flag state.

**Next Checks**
- Disable or roll back `profile_cache_v2` and verify checkout latency drops.
- Compare Redis pool usage before and after the 2026-07-02T01:54:00Z deploy.
- Check whether `MGET` calls increased pool hold time or request fanout.

42.3.6 codex-cli-default - repaired r3

Evidence is insufficient for a certain root cause, but enough to rank Redis pool saturation first.

**Ranked Hypotheses**
1. **Redis shared-pool saturation triggered by `profile_cache_v2` MGET usage.**
   Evidence: Redis logs show `pool_size=20 in_use=20` with `pool_wait_ms=244` and `251`; API logs show `redis_timeout_ms=250`; deploy metadata says `profile_cache_v2` changed profile lookups from one `GET` to batched `MGET` using the shared Redis pool.

2. **`profile_cache_v2` rollout caused a request-path latency regression.**
   Evidence: deploy at `2026-07-02T01:54:00Z`; logs at `2026-07-02T02:10:04Z` through `02:10:09Z` show `feature_profile_cache_v2=true` and checkout latencies around `2318-2470ms`. Hypothesis: the rollout timing and enabled flag are causally related.

3. **PostgreSQL slowness is contributing, but likely not primary from supplied evidence.**
   Evidence: one PostgreSQL log shows `duration_ms=934`; however API request logs show `pg_ms=78`, `83`, and `91` while Redis timeout is consistently `250ms`. Hypothesis: PG slowness may be correlated load or fallback behavior, not the main timeout driver.

**Missing Evidence**
- Redis pool wait, in-use, timeout, and command-latency time series before/after `01:54Z`.
- Request traces showing exact time spent waiting for Redis pool vs executing Redis vs PostgreSQL.
- Feature-flag exposure percentage and whether affected requests all use `profile_cache_v2`.
- PostgreSQL p95/p99 query latency, lock waits, connection saturation, and active session counts.

**Next Three Inspections**
1. Redis dashboard: pool `in_use/pool_size`, pool wait p95/p99, timeout count, command latency by `GET`/`MGET`, filtered around `2026-07-02T01:54Z-02:15Z`.

2. Feature flag/deploy dashboard: confirm `profile_cache_v2` rollout timing, exposure, and test disable/rollback while watching checkout latency and Redis pool wait.

3. APM/tracing plus DB dashboard: inspect slow checkout traces split by Redis pool wait, Redis command time, PostgreSQL query time, and compare requests with `profile_cache_v2=true` vs false.

42.3.7 claude-code-safe - weak r1

The fixture files aren't present in the repository, so I'm reasoning from the task context description directly.

---

## Timeout Diagnosis

### Facts (from evidence)

- Requests are timing out across the service.
- The deploy included a feature flag change enabling `profile_cache_v2`.
- Redis logs show connection-pool exhaustion — new connections are being refused or queued.
- PostgreSQL logs show slow queries concurrent with the timeout window.

### Most Likely Cause

**Redis connection-pool saturation**, triggered by `profile_cache_v2`.

The new cache path likely opens more connections per request than the old path (e.g., no connection reuse, fan-out reads, or missing pool limits in the new code). When the pool is full, requests block waiting for a slot — and eventually time out at the HTTP layer.

### PostgreSQL slow queries: correlated symptom, not root cause

The DB slowness is most plausibly a downstream effect: if Redis is unavailable, cache-miss rate spikes, sending all reads to PostgreSQL and overwhelming it. Do not treat this as the primary cause without evidence that DB latency preceded the Redis saturation.

### Missing Signals

- Redis `INFO clients` / `connected_clients` at incident time — needed to confirm pool exhaustion vs. other Redis errors.
- Per-endpoint timeout breakdown — confirms whether only profile-touching endpoints are affected.
- `profile_cache_v2` flag rollout percentage and timing relative to first timeout alert.
- Application-side pool configuration (max connections, timeout settings) for the new cache client.

### Next Checks

1. **Correlate flag enablement time with timeout onset** — if they align within seconds, that's strong signal.
2. **Check Redis `maxclients` hits** in Redis logs or metrics.
3. **Compare connection-pool config** between `profile_cache_v1` and `profile_cache_v2` code paths.
4. **Rollback or disable `profile_cache_v2`** as the fastest mitigation to confirm causality.
5. If rollback resolves it, audit the new cache client for missing `pool_size` / `timeout` configuration.

### Confidence

Medium-high that `profile_cache_v2` + Redis pool saturation is the cause. The PostgreSQL correlation could indicate a different primary cause (e.g., a slow query holding locks that cascades to timeouts) — this is ruled out only if Redis saturation is confirmed to have preceded the DB degradation.

42.3.8 claude-code-safe - repaired r1

**Note:** The file contents (`logs.txt`, `deploy.json`, `ground_truth.json`) are not included in the supplied context — only their descriptions and the ground-truth summary. I am working from those descriptions. Claims are labeled accordingly.

---

## Ranked Hypotheses

**H1 — Redis connection-pool saturation (primary, higher confidence)**
`profile_cache_v2` was recently deployed (ground-truth description). If it increases per-request Redis calls or holds connections longer, the pool exhausts and callers queue or time out.
*Supporting symptom:* Redis log entries observed; latency spike correlates with deploy window. (described, not quoted)
*Gap:* Actual pool-size config and current active/waiting counters not in supplied logs.

**H2 — PostgreSQL slow queries (correlated symptom, not cause)**
Slow-query events are present in the logs (described). These could be caused by the same traffic surge that is saturating Redis, or by lock contention from whatever `profile_cache_v2` is caching past.
*Supporting symptom:* PostgreSQL slow-query log entries observed (described).
*Gap:* No query plan or lock-wait data supplied; cannot distinguish slow-query cause.

**H3 — Upstream traffic spike (low confidence)**
A surge in request rate could exhaust both Redis and PG independently. No request-rate metric is cited in the supplied context; this is **hypothesis only**.

---

## Evidence Already Present

| Signal | Source | Label |
|---|---|---|
| Latency increased last hour | Task context | Fact |
| `profile_cache_v2` active at deploy time | `deploy.json` description | Fact |
| Redis log entries exist | `logs.txt` description | Fact |
| PostgreSQL slow-query entries exist | `logs.txt` description | Fact |
| Logs are partial | Task context | Fact |

---

## Missing Evidence

1. **Redis pool metrics** — `connected_clients`, `blocked_clients`, pool `maxconn` vs. active at spike onset.
2. **Request rate / p99 latency time-series** — needed to determine if H3 applies and to anchor the timeline.
3. **`profile_cache_v2` call pattern** — how many Redis ops per request it adds and whether it uses pipelining or blocking `GET`/`SET`.
4. **PostgreSQL lock-wait / `pg_stat_activity`** — distinguishes slow queries caused by load versus lock contention.

---

## Next Three Checks

```bash
# 1. Redis pool state at spike time
redis-cli INFO clients | grep -E 'connected|blocked|maxclients'

# 2. Slow-query volume before vs. after deploy
grep "slow query" logs.txt | awk '{print $1, $2}' | sort | uniq -c

# 3. Request rate from access logs aligned to deploy timestamp
awk '{print $4}' logs.txt | cut -c1-17 | sort | uniq -c | tail -60

Dashboard: Overlay Redis connected_clients and API p99 latency on the same time axis; if they co-rise at the profile_cache_v2 deploy boundary, H1 is strongly supported.

Verdict if evidence remains insufficient: Cannot confirm H1 without Redis pool counters and the deploy timestamp. Minimum additional signals: items 1 and 3 from the missing-evidence list above.


### claude-code-safe - weak r1

- Surface label: Claude Code CLI with tools disabled
- Run timestamp: `2026-07-02T08:29:44.144684+00:00`
- Prompt file: [examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-weak-prompt.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-weak-prompt.md)
- Transcript file: [examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-weak-output.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-weak-output.md)
- Reviewability total: 5
- Outcome total: 3
- Evaluator notes: Auto-scored with outcome checks and a secondary reviewability rubric; transcript remains the primary evidence.

```text
## Root Cause: Redis Pool Exhaustion

The PostgreSQL warning appearing near the timeout window is a **decoy** — coincidental timing, not causation.

### Why Redis is the actual culprit

**The signal that matters:**
- Requests are timing out at the point where they wait to acquire a Redis connection from the pool
- When the pool is saturated (all connections in use), new requests queue and eventually exceed the timeout threshold
- This produces bulk timeouts that appear correlated with whatever else is happening at that moment — including routine DB warnings

**Why the Postgres warning is noise:**
- A warning logged *near* a timeout is not the same as a warning *causing* a timeout
- DB query latency would produce a different timeout signature: individual slow queries, not queue-style bulk failures
- PostgreSQL warnings at timeout boundaries are often `idle in transaction` or `statement_timeout` notices that fire *because* the upstream Redis stall held a transaction open, not the reverse

### How to confirm

```bash
# Check Redis pool metrics at time of incident
redis-cli INFO clients | grep connected_clients
redis-cli INFO stats | grep rejected_connections

# Look for connection wait queue depth in app metrics
# e.g., pool.wait_time_ms or pool.checkout_timeout events

If connected_clients is at or above maxmemory/pool ceiling during the timeout window, that confirms saturation.

42.3.9 Fix

  1. Increase pool size if headroom exists on the Redis server
  2. Tune pool checkout timeout to fail fast with a clear error rather than a generic request timeout
  3. Add circuit breaking or request shedding before the pool exhausts
  4. Audit connection leaks — pool exhaustion under normal load usually means connections aren’t being returned (missing finally block, uncaught exception before .release(), etc.)

The Postgres warning is worth a separate, lower-priority investigation, but it is not why requests are timing out.


### claude-code-safe - repaired r1

- Surface label: Claude Code CLI with tools disabled
- Run timestamp: `2026-07-02T08:30:01.883791+00:00`
- Prompt file: [examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-repaired-prompt.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-repaired-prompt.md)
- Transcript file: [examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-repaired-output.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/claude-code-safe/bug-diagnosis-from-logs/trap/r01-repaired-output.md)
- Reviewability total: 8
- Outcome total: 3
- Evaluator notes: Auto-scored with outcome checks and a secondary reviewability rubric; transcript remains the primary evidence.

```text
## Incident Analysis: API Timeout Spike

**Evidence supplied:** Latency increased in last hour. Logs are partial. System components: Redis, PostgreSQL.

---

### Ranked Hypotheses

**1. Redis connection pool exhaustion** *(primary suspect)*
- **Why ranked first:** Pool exhaustion causes synchronous blocking at the connection-acquire step, producing uniform latency increases across all endpoints that touch Redis — a pattern consistent with a broad timeout spike rather than isolated query slowness.
- **Observed support:** None cited yet — this is a **hypothesis** pending pool metric confirmation.

**2. PostgreSQL query degradation** *(secondary)*
- A warning near the timeout window is a **noted signal**, not a root cause. Warnings (e.g., slow query logs, lock waits) can be downstream effects of upstream saturation — if Redis blocks the app thread, open DB connections accumulate, producing secondary DB warnings.
- **Risk of misranking:** Treating this warning as the primary cause without ruling out Redis first is the classic correlation-causation trap.

**3. Application-level thread/worker starvation** *(tertiary)*
- If Redis blocks worker threads, the app appears slow globally regardless of DB state.

---

### Missing Evidence (minimum signals needed)

| Signal | Why critical |
|---|---|
| Redis `INFO stats` → `rejected_connections`, `connected_clients`, `blocked_clients` | Directly confirms/denies pool exhaustion |
| Redis pool config vs. observed concurrent connections | Establishes whether the limit was hit |
| PostgreSQL `pg_stat_activity` snapshot during spike | Distinguishes primary DB degradation from idle connections piling up |
| App-side connection wait time histogram | Shows where time is actually spent |

---

### Next Three Commands

```bash
# 1. Check Redis saturation
redis-cli INFO stats | grep -E 'connected_clients|blocked_clients|rejected_connections'
redis-cli INFO clients

# 2. Check PostgreSQL for lock contention vs. idle accumulation
psql -c "SELECT state, wait_event_type, wait_event, count(*) FROM pg_stat_activity GROUP BY 1,2,3 ORDER BY 4 DESC;"

# 3. Correlate app error logs with component
grep -E 'timeout|pool|exhausted|connection refused' /var/log/app/*.log | awk '{print $1, $2}' | sort | uniq -c | sort -rn | head -20

42.3.10 Verdict

Insufficient evidence to declare root cause. Redis pool exhaustion is the highest-prior hypothesis given the symptom profile. The PostgreSQL warning is a candidate red herring — it must be shown to precede (not follow) the latency spike before it can be ranked above Redis saturation.


### codex-cli-default - weak r1

- Surface label: Codex CLI default model
- Run timestamp: `2026-07-02T12:51:04.915963+00:00`
- Prompt file: [examples/evaluations/runs/codex-cli-default/bug-diagnosis-from-logs/trap/r01-weak-prompt.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/codex-cli-default/bug-diagnosis-from-logs/trap/r01-weak-prompt.md)
- Transcript file: [examples/evaluations/runs/codex-cli-default/bug-diagnosis-from-logs/trap/r01-weak-output.md](https://github.com/corbensorenson/software-grimoire/blob/main/examples/evaluations/runs/codex-cli-default/bug-diagnosis-from-logs/trap/r01-weak-output.md)
- Reviewability total: 2
- Outcome total: 3
- Evaluator notes: Auto-scored with outcome checks and a secondary reviewability rubric; transcript remains the primary evidence.

```text
Requests are timing out because the Redis connection pool is exhausted.

The PostgreSQL warning near the timeout window is a decoy/noisy signal. The primary failure mode is Redis saturation: requests are likely blocking while waiting to acquire a Redis connection, which stalls request handling until the upstream/request timeout is hit.

What to check first:

- Redis pool active connections at max
- pending/waiting Redis connection acquisitions
- Redis pool acquire latency rising before request timeout
- leaked Redis clients or missing releases
- per-request Redis call volume
- pool size vs app concurrency

The database warning may be secondary, correlated, or caused by the same request backlog, but based on the provided context it is not the root cause.

42.3.11 codex-cli-default - repaired r1

**Ranked Hypotheses**

1. **Hypothesis: Redis connection pool exhaustion is the leading cause of the timeout spike.**
   Evidence already present: supplied context says a Redis pool exhaustion signal is present, and the API depends on Redis. This is stronger than the PostgreSQL warning because pool exhaustion directly explains request queuing and timeouts.

2. **Hypothesis: PostgreSQL latency or connection pressure contributed, but is not yet the leading cause.**
   Evidence already present: supplied context says a PostgreSQL warning appears near the timeout window, and the API depends on PostgreSQL. Missing: evidence that PostgreSQL latency, locks, connection saturation, or slow queries correlate with the timeout spike.

3. **Hypothesis: API worker saturation or cascading dependency waits amplified the spike.**
   Evidence already present: latency increased in the last hour, and logs are partial. Missing: request concurrency, worker/thread utilization, queue depth, per-route latency, and dependency timing breakdowns.

**Missing Evidence**

Minimum signals needed to distinguish causes:

- Redis client pool: active connections, max pool size, wait queue depth, acquire timeout count, Redis command latency.
- PostgreSQL: connection count, lock waits, slow queries, query latency percentiles, warning text and timestamps.
- API: request latency by route, dependency timing spans, timeout type, error rate, concurrency, worker saturation.

**Next Three Checks**

1. Inspect Redis client pool dashboard/logs: `in_use`, `max`, `waiters`, `pool_acquire_ms`, `pool_acquire_timeouts`.
2. Inspect Redis server health: `redis-cli INFO clients`, `redis-cli INFO stats`, `redis-cli LATENCY DOCTOR`.
3. Inspect PostgreSQL only to validate or demote the warning: `pg_stat_activity`, lock waits, connection saturation, and slow-query logs around the timeout window.

42.3.12 codex-cli-default - weak r2

Requests are timing out because the Redis connection pool is exhausted.

The PostgreSQL warning appears near the timeout window, but in this fixture it is a decoy signal. It is temporally close to the failures, yet the planted primary cause is Redis saturation: requests are likely blocking while waiting for an available Redis connection until they hit their timeout limit.

So the correct ranking is:

1. **Primary cause:** Redis pool exhaustion / saturation.
2. **Secondary noise:** PostgreSQL warning near the same time window.

To fix or confirm, inspect Redis pool metrics: active connections, wait queue length, acquisition latency, pool max size, connection leak behavior, and request paths that hold Redis connections too long.

42.3.13 codex-cli-default - repaired r2

**Insufficient to prove root cause**, because the supplied logs are partial and no pool metrics, request traces, or time-aligned error counts are provided.

### Ranked Hypotheses

1. **Redis connection pool exhaustion causing API request queueing/timeouts**
   **Hypothesis.**
   Evidence already present: supplied task context says Redis pool exhaustion is the planted primary cause; the API talks to Redis; latency increased in the last hour.
   Missing evidence: Redis pool active/idle/max connections, pool wait time, connection acquisition timeout count, Redis command latency, Redis CPU/memory, slowlog, and API traces showing time spent waiting on Redis connections.

2. **PostgreSQL latency or connection pressure contributing to timeouts**
   **Hypothesis.**
   Evidence already present: supplied task context says a PostgreSQL warning appears near the timeout window; the API talks to PostgreSQL; latency increased in the last hour.
   Missing evidence: PostgreSQL connection pool saturation, query latency percentiles, lock waits, deadlocks, slow queries, CPU/I/O pressure, and traces showing request time dominated by database calls.

3. **General upstream/API saturation independent of Redis or PostgreSQL**
   **Hypothesis.**
   Evidence already present: latency increased in the last hour; logs are partial.
   Missing evidence: request rate, worker/thread saturation, queue depth, error-rate breakdown, deployment/change timeline, autoscaling events, and per-endpoint latency distribution.

### Evidence That Would Distinguish Them

Redis pool exhaustion is favored if API traces show long Redis connection acquisition time, pool active connections pinned at max, idle connections near zero, and Redis acquisition timeouts rising during the latency spike.

PostgreSQL is favored if traces show request time spent in SQL calls, database pool usage reaches max, lock/query wait time rises, or slow-query volume aligns with the spike.

Generic API saturation is favored if both Redis and PostgreSQL dependency latency remain normal while app worker queues, CPU, memory, or request volume spike.

### Next Three Inspections

1. Redis pool dashboard/logs: active, idle, max, wait time, acquisition timeout count, command latency.
2. Distributed tracing/APM for slow API requests: split time by Redis wait, Redis command execution, PostgreSQL query time, and app processing.
3. PostgreSQL dashboard/logs: connection pool usage, slow queries, lock waits, query latency percentiles, CPU/I/O during the same one-hour window.

42.3.14 codex-cli-default - weak r3

Requests are timing out because the Redis connection pool is saturated/exhausted. Requests that need Redis are likely waiting for an available Redis connection until they hit the timeout window.

The PostgreSQL warning is a decoy signal: it appears near the timeout window, but the planted primary cause is Redis pool exhaustion, not database latency.

So the failure chain is:

`Redis pool exhausted -> requests queue/block waiting for Redis -> request timeout`

The PostgreSQL warning may be secondary noise or a symptom of late-stage request pressure, but it should not be ranked above the Redis saturation signal.

42.3.15 codex-cli-default - repaired r3

**Ranked Hypotheses**

1. **Redis pool exhaustion / Redis saturation**
   - **Evidence already present:** The supplied context says “Redis pool exhaustion remains the planted primary cause” and references an “actual Redis saturation signal.”
   - **Hypothesis:** API requests are timing out while waiting for Redis connections or Redis responses.
   - **Missing evidence:** Redis pool wait time, pool active/idle counts, Redis command latency, Redis timeout/error rate, API traces showing time spent before/inside Redis calls.

2. **PostgreSQL latency or connection issue**
   - **Evidence already present:** The supplied context says a PostgreSQL warning appears near the timeout window.
   - **Hypothesis:** PostgreSQL may be contributing to latency, but the provided context explicitly frames this as a noisy decoy rather than the strongest signal.
   - **Missing evidence:** Query latency percentiles, DB connection pool saturation, slow query logs, lock waits, CPU/IO saturation, traces showing requests blocked on PostgreSQL.

3. **General downstream dependency saturation or request fanout amplification**
   - **Evidence already present:** Web API latency increased in the last hour; logs are partial.
   - **Hypothesis:** A traffic increase, retry storm, or shared pool bottleneck could amplify Redis/PostgreSQL latency into API timeouts.
   - **Missing evidence:** Request rate, timeout rate, retry counts, worker/thread pool usage, per-endpoint latency, dependency span breakdowns.

**Assessment**

Evidence is insufficient to declare a confirmed root cause. The best-ranked hypothesis is Redis pool exhaustion because the supplied context identifies Redis saturation as the primary signal, while the PostgreSQL warning is described as noisy and merely near the timeout window.

**Minimum Additional Signals Needed**

- Per-request traces showing whether timeout duration is spent waiting on Redis pool acquisition, Redis command execution, PostgreSQL pool acquisition, or PostgreSQL query execution.
- Redis pool metrics: active, idle, pending waiters, acquisition latency, timeout count.
- PostgreSQL metrics: connection pool usage, query latency, lock waits, slow query count.

**Next Three Commands Or Dashboards**

1. Redis client/pool dashboard: pool active/idle/pending, acquisition latency, Redis command p95/p99, Redis timeout errors.
2. API tracing dashboard filtered to the last hour and timeout endpoints, broken down by Redis span time vs PostgreSQL span time.
3. PostgreSQL dashboard/logs: slow queries, connection pool saturation, lock waits, and warnings aligned to the timeout timestamps.