Three proposals addressing the 2026-02-25 trace pipeline OOM crash (114K CIDs): 1. trace-events-memory-triage: fetchmany iterator (read_sql_df_slow_iter), admission control (50K CID limit for non-MSD), cache skip for large queries, early memory release with gc.collect() 2. trace-async-job-queue: RQ-based async jobs for queries >20K CIDs, separate worker process with isolated memory, frontend polling via useTraceProgress composable, systemd service + deploy scripts 3. trace-streaming-response: chunked Redis storage (TRACE_STREAM_BATCH_SIZE=5000), NDJSON stream endpoint (GET /api/trace/job/<id>/stream), frontend ReadableStream consumer for progressive rendering, backward-compatible with legacy single-key storage All three proposals archived. 1101 tests pass, frontend builds clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
38 lines
1.0 KiB
Desktop File
38 lines
1.0 KiB
Desktop File
[Unit]
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Description=MES Dashboard Trace Worker (RQ, Conda Runtime)
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Documentation=https://github.com/your-org/mes-dashboard
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After=network.target redis-server.service
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Requires=redis-server.service
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[Service]
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Type=simple
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User=www-data
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Group=www-data
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WorkingDirectory=/opt/mes-dashboard
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EnvironmentFile=-/opt/mes-dashboard/.env
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Environment="PYTHONPATH=/opt/mes-dashboard/src"
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ExecStart=/usr/bin/env bash -lc 'exec "${CONDA_BIN:-/opt/miniconda3/bin/conda}" run --no-capture-output -n "${CONDA_ENV_NAME:-mes-dashboard}" rq worker "${TRACE_WORKER_QUEUE:-trace-events}" --url "${REDIS_URL:-redis://localhost:6379/0}"'
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KillSignal=SIGTERM
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TimeoutStopSec=60
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Restart=always
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RestartSec=10
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StandardOutput=journal
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StandardError=journal
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SyslogIdentifier=mes-dashboard-trace-worker
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# Memory protection: trace worker handles large queries independently.
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# MemoryMax prevents single large job from killing the VM.
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MemoryHigh=3G
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MemoryMax=4G
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NoNewPrivileges=yes
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PrivateTmp=yes
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ProtectSystem=strict
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ReadWritePaths=/opt/mes-dashboard/logs
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[Install]
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WantedBy=multi-user.target
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