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Flowise on Ubuntu 24.04 LTS

Flowise is a visual, drag-and-drop builder for LLM workflows and AI agents — connect models, tools, vector stores and memory without writing glue code. This image gives you a production-ready deployment within minutes of first boot — no dependency wrangling, no manual hardening checklist. Published and maintained by Derek Coleman & Associates Inc: freshly rebuilt against current security advisories and deployable straight from the Azure Marketplace into your own subscription.

Version: Flowise 2.2.7 (Node.js)Platform: Ubuntu 24.04 LTSPorts: 3000 (web UI + API)Category: AI & GPU

What's included

  • Flowise installed from the official upstream source
  • Ubuntu 24.04 LTS base with automatic security updates enabled
  • No shared or default passwords — a unique admin credential is generated on your VM at first boot
  • Trusted Launch support: Secure Boot + vTPM
  • Azure Monitor Agent, Defender for Cloud, and Update Manager install cleanly

Quick start

Known issue on the current image (as of 2026-09-15) — flowise.service crash-loops on the current image (Node.js CommonJS loader error), so http://<VM-IP>:3000/ never answers even though /var/lib/flowise/admin-password is written. Workaround and fix status on the support page.
  1. Deploy from the Azure Marketplace (Get It Now → Create), choosing your SSH key at the Administration step.
  2. Allow inbound SSH (22) for yourself plus the application port(s): 3000 (web UI) — restrict to your own IP where possible. The in-image firewall already allows them; only the Network Security Group (NSG) keeps them closed.
  3. Open http://<VM-IP>:3000/ and sign in as dcaadmin (see First login below).
  4. Add your model provider credentials (Credentials) and build your first chatflow; put TLS in front before real use.

Get your admin password (one time)

ssh <your-username>@<VM-IP>
sudo cat /var/lib/flowise/admin-password

Every image ships without any shared or default password — a unique admin credential is generated for your VM on first boot. Change it after first sign-in.

Common use cases

  • Prototyping LLM chains and agents visually
  • Retrieval-augmented generation (RAG) pipelines
  • Chatbots backed by your own documents
  • Exposing flows as APIs for applications

Why our images

Freshly rebuilt against the latest security advisories, no shared default credentials, Trusted Launch support, and automatic OS security updates — everything runs in your own Azure subscription under your governance.

Deploy Flowise in minutes

Production-ready, hardened, and maintained. Deploy straight from the Azure Marketplace into your subscription.