For native workload automation features (dependency management, SLA tracking, visual pipelines), you would typically wrap FileCatalyst commands into a dedicated workload automation platform like , using FileCatalyst as the file movement plugin.

def run_fta(local, remote, server, user, pw): cmd = ["fta-cli", "--server", server, "--username", user, "--password", pw, "--put", local, "--target", remote] result = subprocess.run(cmd, capture_output=True) return result.returncode == 0

success = run_fta(f, "/incoming/", "fc-server.company.com", "auto", "secret") if success: logging.info(f"Success: f") # Post-processing: log to database subprocess.run(["psql", "-c", f"INSERT INTO transfers VALUES('f', 'original_hash')"]) else: logging.error(f"Failed: f") time.sleep(30) # Backoff before retry if == " main ": main() Summary Table: Choosing an Automation Method | Requirement | Recommended Method | |-------------|--------------------| | Simple directory watching | Hotfolder | | Scripted, scheduled transfers | CLI + cron/systemd timer | | Complex workflow with multiple steps | CLI + Bash/Python logic | | Integration with Airflow/Jenkins | REST API or BashOperator | | Central management of many transfers | REST API + custom dashboard |

# PowerShell example $md5 = (Get-FileHash "data.bin" -Algorithm MD5).Hash if ($md5 -eq "expected_hash") fta-cli --put data.bin --target /secure/ else Write-EventLog -LogName Application -Source FileCatalyst -EntryType Error -EventId 100 -Message "Hash mismatch"

Use a script that scrapes API and exposes metrics: