The two follow-ups left open by v0.23.17. One is a real fix; the other turned out to need explaining rather than fixing. **Redis had no memory ceiling.** v0.23.17 stopped the poller from growing Redis without bound, but nothing stopped anything else from doing so, and the host had no protection either way. Redis now runs with a 512 MB cap (REDIS_MAXMEMORY). The eviction policy is the part worth care. `allkeys-lru` would be actively dangerous here: BullMQ job data carries no TTL, so an LRU sweep across all keys could discard queued work with no trace. `volatile-lru` evicts only keys that set an expiry — which is exactly the poller's caches and in-flight claims, all of which are safe to lose because losing one merely causes an earlier re-poll. Verified rather than assumed: sampled BullMQ job keys report ttl=-1 and poller cache keys 528-3408s. If pressure ever exhausts the volatile keys Redis refuses writes instead of evicting queue state, which is loud and survivable. **The 14% fast-poll failure rate is not a bug.** Current rate across all devices and job kinds is 0% over 1,462 attempts. The historical 230,707 failures were genuine device downtime: device_availability records 324 outages totalling ~1,003 hours across four lab devices, which at a 30-second cadence and two attempts per cycle predicts ~240,700 failures — within 4% of what was recorded. Nothing to fix; retention had simply been hoarding an accurate count. It did expose real waste, though. Periodic polls no longer retry in-job, because the schedule already is the retry: a device that did not answer is unlikely to answer a second later, and each extra attempt occupies a worker for up to the job timeout. On a fleet with several devices down that doubled the capacity they consumed — the same capacity the rest of the fleet was short of in #114. It also doubled the recorded failure count, which is how ~1,000 hours of downtime came to look like 231k distinct faults. User-initiated full syncs keep their retries. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
141 lines
4.0 KiB
YAML
141 lines
4.0 KiB
YAML
version: '3.8'
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services:
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nginx:
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build:
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context: .
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dockerfile: nginx/Dockerfile
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ports:
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- "${HTTP_PORT:-80}:80"
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- "${HTTPS_PORT:-443}:443"
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volumes:
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- certs_data:/certs
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depends_on:
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backend:
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condition: service_healthy
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restart: unless-stopped
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networks:
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- app-network
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backend:
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build:
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context: ./backend
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dockerfile: Dockerfile
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environment:
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NODE_ENV: production
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TZ: ${TZ:-UTC}
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DATABASE_URL: postgresql://mikrotik:${DB_PASSWORD:-mikrotik_secure_pw}@postgres:5432/mikrotik_manager
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REDIS_URL: redis://redis:6379
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INFLUXDB_URL: http://influxdb:8086
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INFLUXDB_TOKEN: ${INFLUXDB_TOKEN:-mytoken123456789}
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INFLUXDB_ORG: ${INFLUXDB_ORG:-mikrotik-manager}
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INFLUXDB_BUCKET: ${INFLUXDB_BUCKET:-metrics}
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# Leave unset to auto-generate & persist strong secrets on first boot
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# (stored in the app_data volume). Set them to pin your own values.
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JWT_SECRET: ${JWT_SECRET:-}
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ENCRYPTION_KEY: ${ENCRYPTION_KEY:-}
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CORS_ORIGIN: ${CORS_ORIGIN:-https://localhost,http://localhost,https://127.0.0.1,http://127.0.0.1}
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PORT: 3001
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NETFLOW_BIND_PORT: 2055
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ports:
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# NetFlow/IPFIX collector — UDP goes straight to the backend (nginx not involved).
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# Host port must match the netflow_collector_port app setting (default 2055).
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- "${NETFLOW_PORT:-2055}:2055/udp"
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depends_on:
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postgres:
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condition: service_healthy
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redis:
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condition: service_healthy
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influxdb:
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condition: service_healthy
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volumes:
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- backups_data:/app/backups
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- certs_data:/certs
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- app_data:/app/data
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cap_add:
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- NET_RAW
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restart: unless-stopped
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networks:
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- app-network
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healthcheck:
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test: ["CMD", "wget", "-qO-", "http://127.0.0.1:3001/api/health"]
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interval: 15s
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timeout: 10s
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retries: 5
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start_period: 30s
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postgres:
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image: postgres:15-alpine
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environment:
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TZ: ${TZ:-UTC}
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POSTGRES_DB: mikrotik_manager
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POSTGRES_USER: mikrotik
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POSTGRES_PASSWORD: ${DB_PASSWORD:-mikrotik_secure_pw}
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volumes:
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- postgres_data:/var/lib/postgresql/data
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restart: unless-stopped
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networks:
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- app-network
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U mikrotik -d mikrotik_manager"]
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interval: 10s
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timeout: 5s
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retries: 5
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start_period: 10s
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redis:
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image: redis:7-alpine
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# A memory ceiling so a runaway producer can never take the host down. The
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# eviction policy is deliberately volatile-lru rather than allkeys-*: BullMQ
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# job data carries no TTL and must never be evicted (that would silently
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# destroy queued work), while the poller's caches and in-flight claims all
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# set one and are safe to drop. If pressure ever exhausts the volatile keys
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# Redis refuses writes instead of evicting queue state — loud, and survivable.
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command: >
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redis-server --appendonly yes
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--maxmemory ${REDIS_MAXMEMORY:-512mb}
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--maxmemory-policy volatile-lru
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volumes:
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- redis_data:/data
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restart: unless-stopped
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networks:
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- app-network
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healthcheck:
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test: ["CMD", "redis-cli", "ping"]
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interval: 10s
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timeout: 5s
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retries: 5
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influxdb:
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image: influxdb:2.7
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environment:
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DOCKER_INFLUXDB_INIT_MODE: setup
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DOCKER_INFLUXDB_INIT_USERNAME: admin
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DOCKER_INFLUXDB_INIT_PASSWORD: ${INFLUXDB_ADMIN_PASSWORD:-admin_password_123}
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DOCKER_INFLUXDB_INIT_ORG: ${INFLUXDB_ORG:-mikrotik-manager}
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DOCKER_INFLUXDB_INIT_BUCKET: ${INFLUXDB_BUCKET:-metrics}
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DOCKER_INFLUXDB_INIT_ADMIN_TOKEN: ${INFLUXDB_TOKEN:-mytoken123456789}
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volumes:
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- influxdb_data:/var/lib/influxdb2
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restart: unless-stopped
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networks:
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- app-network
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healthcheck:
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test: ["CMD", "influx", "ping"]
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interval: 15s
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timeout: 10s
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retries: 10
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start_period: 30s
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volumes:
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postgres_data:
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redis_data:
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influxdb_data:
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backups_data:
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certs_data:
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app_data:
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networks:
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app-network:
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driver: bridge
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