Cloud Deployment of MarketPulse's O&M Solution
The following deployment scenarios are recommended to ensure continuous and stable operation of the service:
- Process management assurance: Use the built-in daemon manager (python -m MarketPulse.daemon_manager start), which automatically handles process hangs and recovery, and generates a market_pulse.pid file to record the status of the process.
- Log monitoring system: The logging system rotates automatically, market_pulse.log (10MB/5 backups) and daemon.log (5MB/3 backups) are stored in the logs directory, and you can set up regular log analysis via crontab.
- Failure recovery mechanisms: It is recommended to work with supervisor and other process monitoring tools, when the service is abnormal exit automatically restart, the basic commands include: status to view the status, restart hot update configuration
Deployment points: 1) Use cp .env.example .env to keep the API key properly; 2) Use foreground mode (python -m MarketPulse.main) to verify first in the testing phase; 3) Setup uv pip install -e for production environment . Ensure that the dependencies are complete. For AWS/AliCloud and other platforms, you need to open additional ports required for Bark service.
This answer comes from the articleMarketPulse: a service that pushes AI analytics on financial news in real timeThe
May not be reproduced without permission:AI productivity tools " How to achieve stable operation of MarketPulse in a cloud server environment?
