Principle:Datahub project Datahub Docker Prerequisites
| Field | Value |
|---|---|
| Page Type | Principle |
| Workflow | Docker_Quickstart_Deployment |
| Principle Name | Docker_Prerequisites |
| Repository | Datahub_project_Datahub |
| Implemented By | Implementation:Datahub_project_Datahub_Docker_CLI_Check |
| Last Updated | 2026-02-09 17:00 GMT |
Overview
Description
Docker_Prerequisites is the principle of verifying container runtime prerequisites before platform deployment. In the context of DataHub, this means ensuring that the host environment meets all necessary conditions -- Docker Engine availability, Docker Compose compatibility, sufficient memory allocation, and network port availability -- before attempting to orchestrate a multi-service metadata platform stack. Without rigorous pre-condition checks, deployment failures become difficult to diagnose and may leave the system in a partially started, inconsistent state.
Usage
This principle applies whenever an operator or developer prepares to deploy DataHub locally via Docker. Before invoking the quickstart command, the pre-condition validation pattern ensures that:
- The Docker daemon is running and accessible from the CLI.
- Docker Compose v2 is available (either as a standalone binary or as a Docker CLI plugin).
- The host machine has allocated at least 8 GB of memory to the Docker runtime.
- Required network ports (8080 for GMS, 9002 for the frontend) are not already bound by other processes.
By verifying these conditions up front, operators avoid partial deployments, obscure timeout errors, and wasted troubleshooting time.
Theoretical Basis
Pre-condition Validation Pattern
The pre-condition validation pattern originates from the discipline of Design by Contract, formalized by Bertrand Meyer. A pre-condition is a predicate that must hold true before an operation is invoked. If the pre-condition is violated, the operation is not obligated to produce a correct result.
In the context of container orchestration, the "operation" is the deployment of a multi-service stack. The pre-conditions include:
- Runtime availability -- The container engine must be installed and its daemon must be responding to API calls.
- Toolchain compatibility -- The orchestration tooling (Docker Compose) must be present and at a compatible version.
- Resource sufficiency -- Memory, CPU, and disk resources must exceed minimum thresholds for the combined service footprint.
- Port availability -- TCP ports required by the services must be unoccupied so that host-to-container port mappings succeed.
Environment Readiness Checks
Environment readiness checks serve as a fail-fast mechanism. Rather than allowing Docker Compose to begin pulling images, creating networks, and starting containers -- only to fail partway through -- the readiness check surfaces problems immediately and with clear diagnostic messages.
This is analogous to the readiness probe concept in Kubernetes, but applied at the host level before orchestration begins rather than at the container level after startup.
Why This Matters for DataHub
DataHub's quickstart deployment involves at least five interdependent services: a metadata store (MySQL or PostgreSQL), a search index (Elasticsearch or OpenSearch), an event bus (Kafka with Zookeeper), the backend metadata service (GMS), and the frontend application. A failure in any one dependency cascades to downstream services. Validating prerequisites reduces the surface area for these cascading failures.
Related Pages
- Implementation:Datahub_project_Datahub_Docker_CLI_Check -- The concrete CLI command that performs prerequisite verification.
- Principle:Datahub_project_Datahub_Quickstart_Launch -- The deployment principle that depends on prerequisites being satisfied.
- Principle:Datahub_project_Datahub_Service_Health_Monitoring -- Post-deployment health monitoring that complements pre-deployment checks.
- Heuristic:Datahub_project_Datahub_Docker_Memory_Preflight