Install on Linux with Docker

Install CAST Imaging on Linux using Docker - choose your deployment scenario and topology

Overview

This section covers new installations of CAST Imaging on Linux using Docker. Choose your deployment scenario and topology below to get a dedicated, step-by-step installation guide with no conditional branching.

For updates to existing installations, see In-place component update.

Step 1 - Choose your deployment scenario

A scenario defines which CAST Imaging components you install. All scenarios include imaging-services and require access to a database instance.

Scenario Analysis Viewer Dashboards Use when…
S1 - All Components Full CAST Imaging: analysis, Viewer and Dashboards
S2 - Viewer Only Read-only Viewer access - analysis runs on a separate installation
S3 - Viewer + Analysis Run analysis and view results; no Dashboards component
S4 - Dashboards Only Read-only Dashboards access - analysis runs on a separate installation
S5 - Dashboards + Analysis Run analysis and view aggregated Dashboard results; no Viewer component

Advanced topology - Neo4j on a dedicated machine

Available in ≥ 3.6.4-funcrel

For scenarios that include the Viewer (S1, S2, S3), you can run Neo4j on its own dedicated machine, separate from the Viewer services - useful for performance isolation and to update CAST Imaging independently of Neo4j. This deployment uses a tailored non-standard installation process, described in Neo4j on a dedicated machine.

Step 2 - Choose your deployment topology

A topology defines how components are distributed across machines:

  • Single machine - all selected components on one host. Suitable for POC, testing, demo, or small production environments.
  • Multi-machine - components distributed across dedicated hosts (or a mixed allocation). Recommended for production.

Step 3 - Go to your guide

All selected components on one host. Suitable for POC, testing, demo, or small production environments.

Components distributed across dedicated hosts. Recommended for production.

Reference

The following pages apply across all Docker deployment scenarios: