<@ULVA73B9P> i have self hosted the prefect on my ...
# marvin-ai
k
@Marvin i have self hosted the prefect on my ec2 instance and the server and the local workpool are running with active instance as daemon processes, i am just using the postgres database instead of the default sqlite database why does the response on the UI to fetch the flows or other objects? often times i get the error in the right bottom that oops there is an error in the prefect API what is wrong here in the setup , how can i make this smooth and better
m
thought for 284.8 seconds
Thanks for the details — that “Oops, there is an error in the Prefect API” toast means the UI’s request to your self‑hosted API is failing intermittently. On EC2 with Postgres, the most common causes are DB connectivity/migrations, connection pool exhaustion, or a reverse proxy misconfig. Here’s a focused checklist to get you to a smooth setup. I’m assuming Prefect 3.x. 1) Verify the API and DB are actually healthy - Health/readiness
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curl -i http://<your-host>:4200/api/health
  curl -i http://<your-host>:4200/api/ready
Expect 200 for /health; /ready returns 200 only if the DB is reachable. - Check server logs for DB or timeout errors
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journalctl -u prefect-server -f
Look for “database unavailable”, timeouts, pool exhaustion, or 5xx traces. 2) Ensure the Postgres URL uses the async driver and run migrations - Your Prefect server must point to Postgres with the async driver:
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export PREFECT_API_DATABASE_CONNECTION_URL="<postgresql+asyncpg://user:pwd@host:5432/prefect>"
  echo $PREFECT_API_DATABASE_CONNECTION_URL
If you see plain postgresql:// (sync), switch to postgresql+asyncpg:// and restart. - Apply migrations (this fixes schema/index issues that can cause slow or failing queries):
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prefect server database upgrade -y
If your DB is large, set a higher timeout:
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export PREFECT_API_DATABASE_TIMEOUT=600
  prefect server database upgrade -y
3) Right‑size the DB connection pool for production If the pool is too small, API calls will hang/timeout and you’ll see that UI toast. - Start with:
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export PREFECT_SERVER_DATABASE_SQLALCHEMY_POOL_SIZE=20
  export PREFECT_SERVER_DATABASE_SQLALCHEMY_MAX_OVERFLOW=40
  export PREFECT_SERVER_DATABASE_SQLALCHEMY_POOL_TIMEOUT=30
  export PREFECT_SERVER_DATABASE_SQLALCHEMY_POOL_RECYCLE=3600
- Restart the server after setting these. - Watch active connections to confirm you’re not exhausting the pool:
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psql -c "SELECT count(*) FROM pg_stat_activity WHERE datname='prefect';"
4) If you’re behind a reverse proxy/ALB, verify routing and headers - The UI expects the API at /api. Ensure your proxy forwards: - All /api/* to the Prefect server - WebSockets upgrade headers - X-Forwarded-For / X-Forwarded-Proto / Host - A misrouted /api path is a frequent cause of intermittent UI API errors. 5) Confirm the server picked up your env vars when running as a daemon When using systemd/daemon, environment may not match your shell. Put env in the unit or an EnvironmentFile and restart: - Minimal example:
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[Service]
  Environment="PREFECT_API_DATABASE_CONNECTION_URL=<postgresql+asyncpg://user:pwd@localhost:5432/prefect>"
  Environment="PREFECT_SERVER_DATABASE_SQLALCHEMY_POOL_SIZE=20"
  ExecStart=/usr/local/bin/prefect server start --no-services
  Restart=always
- Validate at runtime:
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prefect config view | grep -i database
6) Quick diagnostics to share back (will pinpoint the issue fast) - Output of:
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prefect version
  prefect server database current
  prefect config view | grep -E 'PREFECT_API_URL|DATABASE|POOL'
  echo $PREFECT_API_DATABASE_CONNECTION_URL
  curl -sS http://<host>:4200/api/health
  curl -sS http://<host>:4200/api/ready
- Any reverse proxy/ALB config if applicable. - Relevant lines from
journalctl -u prefect-server -f
around failures. If you want a reference setup to compare against (single EC2, Postgres, Redis, server as a service), these guides are handy: - Server CLI (self-hosted): Server CLI - Docker Compose example (even if not using Docker, it shows working env): Docker Compose setup - Advanced self-hosted/production notes: Scaling self-hosted - Settings reference (DB and pool env vars): Settings reference
- Running as services (daemonizing): Daemonize processes If you can share the outputs above (especially your DB URL, health/readiness responses, and a snippet of server logs), I can help pinpoint exactly which of the items (driver, migrations, pool, or proxy) is causing the intermittent API errors.