fix(pusher): prevent ghost WebSocket connections leaking memory

[beastoin]

Summary

Fixes ghost WebSocket connections in both pusher and transcribe that leak ~15MB each, and introduces production-grade structured concurrency utilities (utils/async_tasks.py) following FastAPI best practices.

Root cause

When a background task (GCS upload, webhook, diarizer call) hangs after the WebSocket disconnects, the old asyncio.gather() pattern blocks forever — preventing cleanup. The connection gauge is never decremented and ~15MB per ghost connection is leaked.

Fix: Structured concurrency utilities + supervisor pattern

New module: utils/async_tasks.py — same pattern as utils/executors.py (thread pools) and utils/http_client.py (HTTP clients): named utilities with bounded resources, clean shutdown, and Prometheus observability.

Utility	Purpose	Replaces
supervise_tasks()	asyncio.wait(FIRST_COMPLETED) supervisor loop	Inline supervisor in both WS handlers
drain_tasks()	Timeout-bounded task cancellation with force-cancel	Manual cancel-loop + gather in finally blocks
gather_with_logging()	Bounded fan-out with exception logging	asyncio.gather(*coros, return_exceptions=True) (silent failures)
gather_chunked()	Chunked fan-out for large coroutine lists	Manual chunking in app_integrations
create_named_task()	Tracked task creation with done-callback cleanup	Raw asyncio.create_task()
sleep_until_shutdown()	Interruptible sleep that wakes on shutdown event	Raw asyncio.sleep() in polling loops

Instant drain on disconnect (shutdown event pattern)

Problem: drain_tasks(cancel=False) waits up to 30s for bg tasks, but polling tasks (e.g. _record_usage_periodically with 60s sleep) are mid-asyncio.sleep() and can't observe shutdown — they sit idle until the sleep finishes or drain times out.

Solution: Per-connection asyncio.Event (shutdown_event) that fires on disconnect. All polling loops use sleep_until_shutdown(event, seconds) instead of raw asyncio.sleep(). Pollers wake instantly (<1ms) on disconnect while heavy tasks (LLM processing) still get their full cancel=False grace period.

Affected loops:

• transcribe.py: _record_usage_periodically (60s), send_heartbeat (10s), _pusher_heartbeat (20s), pusher reconnect backoff (variable)
• pusher.py: process_private_cloud_queue (1s), process_speaker_sample_queue (15s), process_transcript_queue (1s), process_audio_bytes_queue (1s)

Best practices applied (sourced from research)

• zhanymkanov/fastapi-best-practices (10k+ stars): Use structured concurrency; BackgroundTasks only for sub-second fire-and-forget
• FastAPI #3934: Tasks spawned in WS handlers are NOT cancelled on disconnect — manual cleanup required
• Python 3.11 TaskGroup: Auto-cancels siblings on first failure
• roguelynn: asyncio exception handling: gather(return_exceptions=True) hides bugs — prefer explicit exception checking
• GatherResult[T] type (codex recommendation): Return typed results instead of None for failed items

Bug classes eliminated

Bug Class	Old Pattern	New Pattern
Silent exception swallowing	gather(*coros, return_exceptions=True) with no inspection	gather_with_logging() logs every failure with label
Orphaned tasks on first failure	gather() propagates exception but siblings keep running	supervise_tasks() exits loop, then drain_tasks() cleans up
Unbounded fan-out	50+ integrations × 1800 sessions = 90k concurrent connections	Semaphore-bounded via max_concurrency parameter
30s drain delay on disconnect	Polling tasks mid-asyncio.sleep() ignore shutdown	sleep_until_shutdown() wakes pollers instantly via Event

Changes

File	Change
utils/async_tasks.py	NEW — 6 structured concurrency utilities with Prometheus metrics
routers/pusher.py	Refactored: supervisor, drain, shutdown event for all queue processors
routers/transcribe.py	Refactored: supervisor, drain, shutdown event for all polling loops
utils/app_integrations.py	Replaced 3× raw gather(return_exceptions=True) with gather_with_logging()
tests/unit/test_async_tasks.py	NEW — 88 tests: behavioral, structural, shutdown event, boundary edge cases
tests/unit/test_pusher_ghost_connections.py	Updated structural tests to verify utility usage
test.sh	Added test_async_tasks.py
CLAUDE.md	WebSocket concurrency rules
AGENTS.md	Synced WebSocket concurrency rules
docs/.../listen_pusher_pipeline.mdx	Task supervision section

Prometheus metrics added

Metric	Type	Purpose
async_supervisor_exit_total{label,reason}	Counter	Track supervisor exits by reason (disconnect/crash/lifetime_done)
async_drain_timeout_total{label}	Counter	Detect drain operations that hit timeout
async_drain_duration_seconds{label}	Histogram	Monitor drain latency
async_gather_failures_total{label}	Counter	Prove exceptions are caught, not swallowed
async_gather_duration_seconds{label}	Histogram	Detect slow fan-outs

Test plan

• 88 unit tests pass (45 async_tasks + 43 ghost connections) — includes boundary edge cases for zero/negative timeouts, concurrency serialization, and chunk ordering
• Backend boot check clean
• L1: 5-min podcast streaming — 107 segments, 1911 words, connection held for full 279s
• L1: Client disconnect mid-stream — clean abort, "Session ended, aborting Pusher retry" in logs
• L1: 3× concurrent streams — all 3/3 connections held, 16 total segments, no event loop blocking
• L2: Backend + pusher integrated (5-min podcast) — 107 segments, 1928 words, backend→pusher WS active throughout
• L2: Backend + pusher integrated (disconnect) — clean lifecycle: disconnect detected, pusher reconnect ended, conversation cleaned up
• CODEx reviewer approved (2 iterations — fixed zero-timeout edge case in sleep_until_shutdown)
• CODEx tester approved (2 iterations — added boundary tests for drain/gather/chunked/shutdown)
• CI: Lint & Format Check passed

Risks

• Behavior change in drain_tasks: drain_tasks(cancel=False) first waits, then force-cancels on timeout. The old inline pattern did the same but with explicit TimeoutError handling. Risk is minimal since the utility implements the same logic.
• gather_with_logging returns GatherResult: Callers that used raw gather results need to access .value instead. Only app_integrations.py is affected and its callers don't use return values from gather.
• Finite task misclassification: If a truly lifetime task is marked finite, its completion won't trigger teardown. Mitigated by explicit finite_tasks set with only 2 members, plus structural tests.
• shutdown_event is per-connection: Each WS connection creates one asyncio.Event. At 1800 concurrent connections this is ~1800 Event objects — negligible memory overhead (<1KB each).

Closes #7280

🤖 Generated with Claude Code

[greptile-apps]

Greptile Summary

This PR reduces pusher pod resource requests from 700m/4.5Gi to 350m/2.5Gi while leaving limits unchanged at 700m/4.5Gi, shifting QoS from Guaranteed to Burstable and doubling schedulable capacity from 24 to 48 pods across the 12-node dedicated pool so HPA can reach its 40-replica maximum.

• CPU and memory utilization data strongly supports the reduction — average CPU was ~14% of request and average memory ~12%, with the new request still providing ~55% headroom above the observed CPU max.
• The capacity math (4 pods/node × 12 nodes = 48 ≥ 40 HPA max + 2 maxSurge) is correct, and the PDB (minAvailable: 80%) and rolling update settings (maxUnavailable: 1, maxSurge: 2) are compatible with the new density.
• One outlier pod at 2964Mi sits above the new 2.5Gi memory request; under Burstable QoS this makes it an eviction candidate during node memory pressure, which the PR acknowledges and plans to monitor.

Confidence Score: 4/5

Safe to merge with monitoring in place; the scheduling math is correct and the change unblocks HPA scaling as intended.

The change is a single-file, well-documented resource request reduction backed by real utilization data. The capacity arithmetic checks out end-to-end. The one area to watch is the memory outlier pod (2964Mi observed vs 2.5Gi new request): under Burstable QoS that pod is an eviction candidate during node memory pressure, which is a present operational risk rather than a purely theoretical one. Keeping limits at 4.5Gi and deploying to a dedicated node pool mitigates the worst outcomes, but the gap between request and observed peak is worth monitoring closely during rollout.

Only backend/charts/pusher/prod_omi_pusher_values.yaml changed; watch memory eviction metrics for pusher pods after rollout, particularly the outlier pod that has previously reached ~2964Mi.

Important Files Changed

Filename	Overview
backend/charts/pusher/prod_omi_pusher_values.yaml	CPU requests halved (0.7→0.35) and memory requests nearly halved (4.5Gi→2.5Gi) while keeping limits unchanged, shifting QoS class from Guaranteed to Burstable; HPA and scheduling math is correct but memory request sits below the observed 2964Mi peak for one pod.

Flowchart

%%{init: {'theme': 'neutral'}}%%
flowchart TD
    HPA["HPA\n(min: 20, max: 40)\nmetric: activeConnectionsPerPod=30"]
    HPA -->|"wants >24 pods\n(was blocked)"| SCHED

    subgraph SCHED["Kubernetes Scheduler"]
        direction TB
        OLD["Before\nCPU req: 700m\nMem req: 4.5Gi\n→ 2 pods/node\n→ 24 max schedulable"]
        NEW["After\nCPU req: 350m\nMem req: 2.5Gi\n→ 4 pods/node\n→ 48 max schedulable"]
    end

    SCHED --> NODE["12 pusher-pool-v3 nodes\nAllocatable: 1930m CPU / 13485Mi Mem\nUsable after DaemonSet: 1571m / 12362Mi"]

    NODE --> QOS["QoS: Burstable\nLimits: 700m CPU / 4.5Gi Mem\n(unchanged)"]
    QOS --> RISK["Risk: pods using >\nrequest memory\nare eviction candidates\nunder node pressure"]
    QOS --> OK["HPA can now scale\nup to 40 replicas\n(42 with maxSurge=2)\n< 48 capacity ✓"]

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_{Reviews (1): Last reviewed commit: "fix(pusher): increase memory request to ..." | Re-trigger Greptile}

[greptile-apps]

Memory request below observed peak usage

The new 2.5Gi request (2560Mi) is below the single observed outlier pod at 2964Mi. Under Burstable QoS, kubelet evicts pods whose actual memory usage exceeds their request when a node hits memory pressure — meaning that outlier pod becomes an eviction candidate even without approaching the 4.5Gi limit. Since this is a dedicated node pool the risk is low during normal operation, but a coordinated spike (e.g., multiple pods hitting jemalloc fragmentation peaks simultaneously) could trigger cascading evictions. Consider adding an eviction alert on kube_pod_container_status_restarts_total for the pusher namespace as a rollout safeguard, and evaluate whether 2.75Gi or 3Gi is a safer floor given the observed outlier.

[beastoin]

Changed-path coverage checklist

Path ID	Sequence ID(s)	Changed path	Happy-path test	Non-happy-path test	L1 result + evidence	L2 result + evidence	L3 result + evidence	If untested: justification
P1	N/A	prod_omi_pusher_values.yaml:requests.cpu 700m→350m	YAML parses, request ≤ limit, capacity math confirms 4 pods/node	Invalid value (negative, > limit) — not applicable to a human-edited number field	PASS — YAML validation + capacity math script	N/A (config-only, no app integration)	Pending — requires Helm upgrade to prod
P2	N/A	prod_omi_pusher_values.yaml:requests.memory 4.5Gi→3Gi	YAML parses, request ≤ limit, capacity math confirms 4 pods/node	Invalid value — not applicable	PASS — YAML validation + capacity math script	N/A (config-only, no app integration)	Pending — requires Helm upgrade to prod

L1 evidence

YAML validation:

• requests.cpu = 0.35 (350m), requests.memory = 3Gi
• limits.cpu = 0.7 (700m), limits.memory = 4.5Gi
• All requests ≤ limits ✅

Capacity math (automated script):

• Usable per node after DaemonSets: 1571m CPU, 12362Mi memory
• Pods per node: min(1571/350, 12362/3072) = min(4, 4) = 4
• Total cluster capacity: 4 × 12 = 48 pods
• HPA max(40) + maxSurge(2) = 42 < 48 ✅

beast omi dev doctor: status=ok, no CRITICAL failures

L1 synthesis

Both changed paths (P1, P2) validated via YAML parsing, constraint checking (requests ≤ limits), and capacity math proving 48 pods fit on the existing 12-node pool. Non-happy-path testing is not applicable — these are static numeric values in a Helm chart with no branching logic. No paths remain untested at L1.

by AI for @beastoin

[beastoin]

@beastoin The pusher code change looks correct for the ghost-connection leak, but this PR changes listen/pusher timeout and shutdown processing (WS_RECEIVE_TIMEOUT, BG_DRAIN_TIMEOUT, and speaker-sample drain behavior in backend/routers/pusher.py) without updating docs/doc/developer/backend/listen_pusher_pipeline.mdx; the backend agent rules explicitly require that doc to be updated when pusher timeouts or processing flow change. Can you add the doc update in this PR?

---

by AI for @beastoin

[beastoin]

Test Evidence — CP8 + CP9A + CP9B Complete

CP8: Test Coverage (TESTS_APPROVED)

31 unit tests across 7 test classes, all passing:

Class	Tests	Coverage
TestConstants	7	Exact values (300s, 30s), relationships, existence
TestReceiveTimeoutBehavior	2	Timeout fires on dead, doesn't fire on active
TestDrainTimeout	3	Hung cancelled, healthy completes, mixed scenario
TestSpeakerSampleShutdownDrain	1	Pending samples processed on shutdown
TestGaugeDecrement	4	Normal exit, error, hung bg, old pattern demo
TestStructuralIntegrity	5	Source pattern string checks
TestProductionFlowStructure	9	AST-verified: gauge try/finally, receive-then-drain ordering, force-cancel, bg task separation

CP9A: Level 1 — Standalone Pusher Test

• Doctor: 18/18 passed
• Boot check: import clean (5.8s)
• Pusher started on port 10240, all 4 WS connections opened and closed cleanly
• Post-test: 0 TCP connections (no ghost connections)
• Memory: VmRSS 339100 kB stable, 58 threads

CP9B: Level 2 — Backend + Pusher Integrated

• Backend on port 10241, Pusher on port 10242
• Full /v4/listen WS flow:
  • Connected with ADMIN_KEY auth
  • Received: service_status: initiating → processing → stt_initiating → ready
  • Sent silence keepalive
  • Disconnected cleanly (code=1000)
• Backend log: Client disconnected: code=1000 reason=normal_closure
• Pusher log: connection open, received conversation_id
• Post-test: 0 ghost connections

Changed-Path Coverage

Path ID	Changed path	Happy-path	Non-happy-path
P1	pusher.py:receive_tasks — WS_RECEIVE_TIMEOUT	PASS (L2: active connection works)	PASS (unit: timeout fires on dead)
P2	pusher.py:_websocket_util_trigger — receive-then-drain	PASS (L2: clean disconnect)	PASS (unit: hung bg cancelled)
P3	pusher.py:_websocket_util_trigger — BG_DRAIN_TIMEOUT	PASS (unit: healthy drains)	PASS (unit: mixed hung/healthy)
P4	pusher.py:process_speaker_sample_queue — is_shutdown	PASS (unit: samples processed)	N/A (old bug was silent drop)
P5	pusher.py:finally — cancel all tasks	PASS (L1+L2: 0 ghost connections)	PASS (unit: gauge always decrements)

by AI for @beastoin

[beastoin]

CP9 Changed-Path Coverage Checklist

Changed executable paths

Path ID	Changed path	Happy-path test	Non-happy-path test	L1 result + evidence	L2 result + evidence
P1	async_tasks.py:supervise_tasks — FIRST_COMPLETED supervisor loop	5-min podcast stream completes, supervisor detects disconnect	BG task crash triggers supervisor exit	L1 PASS: 107 segs, 1911 words over 279s; unit test test_crash_exit	—
P2	async_tasks.py:drain_tasks — timeout-bounded cancellation	Drain completes within 30s on disconnect	Force-cancel after timeout	L1 PASS: clean disconnect in test; unit test test_drain_timeout_force_cancels	—
P3	async_tasks.py:sleep_until_shutdown — interruptible sleep	Pollers wake on shutdown_event	Zero/negative timeout edge cases	L1 PASS: 6 unit tests including zero-timeout regression; live test disconnect clean	—
P4	async_tasks.py:gather_with_logging — bounded fan-out	Fan-out with max_concurrency=1 serializes	Partial failure logs exceptions	L1 PASS: unit tests test_all_succeed, test_partial_failure, test_gather_concurrency_one	—
P5	async_tasks.py:create_named_task — tracked task creation	Task created with name, added to set	Task removed from set on exception	L1 PASS: unit tests test_task_has_name, test_task_removed_from_set_on_exception	—
P6	pusher.py:_websocket_util_trigger — supervisor+drain refactor	5-min streaming, all queue processors run	Disconnect: shutdown_event fires, queues drain	L1 PASS: podcast + disconnect test, "Session ended, aborting" in logs	—
P7	transcribe.py:websocket_endpoint — supervisor+drain+shutdown_event	5-min podcast, all bg tasks supervised	Disconnect mid-stream, pollers wake instantly	L1 PASS: podcast test 279s + disconnect test 5s	—
P8	transcribe.py:_record_usage_periodically — shutdown_event sleep	Usage recorded during 5-min session	Shutdown_event wakes 60s sleep instantly	L1 PASS: podcast test ran full session; shutdown event tested via disconnect	—
P9	transcribe.py:send_heartbeat — shutdown_event sleep	Heartbeat pings sent during session	Shutdown_event wakes 10s sleep	L1 PASS: connection held for 279s with heartbeats	—
P10	transcribe.py:_pusher_heartbeat — shutdown_event sleep	Heartbeat data frames sent every 20s	Shutdown_event wakes 20s sleep	L1 PASS: pusher heartbeat ran during session	—
P11	transcribe.py:pusher_reconnect_backoff — shutdown_event in retry	N/A (pusher not running locally)	Shutdown_event aborts backoff sleep	L1 PASS: "Session ended, aborting Pusher retry" in logs	—
P12	app_integrations.py:trigger_realtime_integrations — gather_with_logging	Integrations fan-out bounded	Exception in one integration doesn't crash others	L1 PASS: structural test verifies import; unit test covers gather_with_logging semantics	—
P13	pusher.py:process_*_queue (4 queues) — shutdown_event sleep	Queues process items during session	Shutdown_event wakes idle queues	L1 PASS: 3× concurrent test, all connections held	—

L1 Live Test Evidence

• Backend started: beast omi dev start backend on port 8700, boot-check clean
• Podcast 5m: PASSED — 279s streamed in 285.7s, 107 segments, 1911 words, first segment 22.8s, connection held
• Disconnect: PASSED — 5s audio then abrupt close, "Session ended, aborting Pusher retry" in backend logs
• Concurrent 3x: PASSED — 3/3 connections held, 16 total segments, no event loop blocking
• Unit tests: 88 passed in 2.64s

by AI for @beastoin

[beastoin]

CP9B — Level 2 Live Test Evidence (Backend + Pusher Integrated)

Services: beast omi dev start backend pusher — backend on 8700, pusher on 8701, auto-linked via HOSTED_PUSHER_API_URL

Podcast 5m (integrated)

• Result: PASSED
• Duration: 279s streamed in 285.7s
• Segments: 107, Words: 1928
• First segment latency: 22.6s
• Connection held throughout
• Backend → Pusher WS connection active during session

Disconnect (integrated)

• Result: PASSED
• 5s audio then abrupt disconnect
• Backend logs: "WebSocket disconnected", "Pusher reconnect loop ended", "Clean up the conversation"
• Conversation lifecycle ran correctly after disconnect

Backend log traces

INFO:routers.transcribe:Pusher reconnect loop ended (state=degraded) test-streaming-5577-disconnect
INFO:routers.transcribe:Clean up the conversation 30252b36, reason: no content
INFO:routers.transcribe:finalize_processing_conversations len(processing): 1

Unit tests

• 88 passed in 2.64s (both test files)

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