Requirements

Everything you need before deploying. Read this first, hand the checklist to your infrastructure team, and move on to the Deployment guide once everything is in place.


How the platform is deployed

The RootCause Platform is deployed into your Kubernetes cluster via the RootCause Operator. The operator manages the full lifecycle — install, configure, upgrade — through an Admin UI.

The deployment flow is:

  1. Your infra team installs the operator (one Helm command)

  2. You open the Admin UI and fill in a bootstrap wizard

  3. The operator deploys everything: databases, message queues, identity, LLM proxy, and the platform itself

Once installed, data scientists can check for updates and apply them through the Admin UI without involving the infra team.

What the operator deploys

┌─────────────────────────────────────────────────────┐
│                   Admin UI (:3000)                  │
│  Bootstrap │ Overview │ Secrets │ Users │ Releases  │
└──────────────────────┬──────────────────────────────┘
                       │ writes CR

┌─────────────────────────────────────────────────────┐
│              RootCauseInstallation CR               │
└──────────────────────┬──────────────────────────────┘
                       │ reconciles

┌─────────────────────────────────────────────────────┐
│              Operator Controller                    │
└──────────────────────┬──────────────────────────────┘
                       │ manages
          ┌────────────┼────────────┐
          ▼            ▼            ▼
   Dependencies    Platform     Secrets
   ├ PostgreSQL    ├ Platform   ├ Auth keys
   ├ Redis         ├ Data Svc   ├ DB credentials
   ├ MongoDB       ├ Data Fusion├ Storage credentials
   ├ Temporal      ├ ML Jobs
   ├ LiteLLM       └ Ingresses
   └ FusionAuth

Platform components:

Component
What it does

Platform

UI and backend-for-frontend (Next.js + API)

Data Service

Core backend for data processing, orchestration, and LLM integration (FastAPI)

Data Fusion

Data transformation and aggregation engine

ML Jobs

Headless compute engine for batch and algorithmic workloads

Infrastructure dependencies (deployed by the operator into your cluster):

Dependency
Purpose
Minimum version

PostgreSQL

Relational database for Temporal, FusionAuth, and LiteLLM

15.0+

MongoDB

Document database for application data

8.0+

Redis

Sync layer

7.2.4+

RabbitMQ

Message queue for async processing

3.12.2+

Temporal

Durable workflow execution

1.27.2+

LiteLLM

LLM API proxy and management

Deployed by default

FusionAuth

Identity and access management (optional — see Identity below)

Deployed on request


Infrastructure requirements

Kubernetes and tooling

Requirement
Version

Kubernetes

1.26+ (tested on AKS, EKS, GKE, and kind)

Helm

3.12+

kubectl

Configured with cluster-admin access

Cluster sizing

Minimum — supports datasets up to ~5GB, 50 columns, ~1M rows:

Resource
Spec

Nodes

3-4

CPU per node

8 vCPU

RAM per node

64 GB

Storage

SSD-backed persistent volumes

GPU (optional)

48 GB VRAM (local LLMs only)

Recommended for production — supports datasets up to ~10GB, 100+ columns, ~20M rows:

Resource
Spec

Nodes

4+

CPU per node

64 vCPU

RAM per node

128 GB

Storage

SSD-backed persistent volumes

GPU (optional)

96 GB VRAM (local LLMs only)

All nodes must be amd64 architecture.


Cloud-specific prerequisites

The platform runs on Azure, AWS, and GCP. The core deployment is identical; only the items below differ.

Requirement
Azure
AWS
GCP

Managed Kubernetes

AKS

EKS

GKE

Storage class

managed-csi

gp3

standard or premium-rwo

Object storage

Azure Blob Storage

S3

GCS

Ingress options

Azure Application Gateway (AGIC) or nginx

nginx or ALB Ingress Controller

nginx or GCE Ingress

Identity (OIDC)

Azure EntraID

Okta, Auth0, or any OIDC provider

Google Workspace or any OIDC provider

Note: Azure Application Gateway requires additional ingress annotations and path configuration. The Deployment guide covers this in detail.


What you need to provide

Hand this checklist to your infrastructure team. Everything must be in place before deployment begins.

Cluster and access

Networking

Storage

Registry access

Identity (choose one)

LLM access


What RootCause provides

  • RootCause Operator Helm chart (OCI registry)

  • Platform and dependencies Helm charts (OCI registry, pulled automatically by the operator)

  • Admin UI for configuration, deployment, user management, and upgrades

  • Deployment support via Slack, email, and scheduled check-ins


Decision points

Answer these before starting the Deployment guide. They determine which sections you'll fill in during the bootstrap wizard.

1. Identity provider

Option
When to choose it

External OIDC (recommended)

Your organization has an existing identity provider (EntraID, Okta, Auth0, Google Workspace)

External SAML

Your IdP only supports SAML, or your security team requires it

Managed FusionAuth

POC, eval, or no existing IdP. The operator deploys and configures FusionAuth automatically.

2. Ingress controller

Option
When to choose it

nginx

Most common. Works on all clouds. Simpler configuration.

Azure Application Gateway

Required by your Azure networking team, or you need WAF/DDoS protection at the ingress layer. Requires additional annotations and path config — see Deployment guide.

3. Object storage

Cloud
Service
What you need

Azure

Azure Blob Storage

Storage account name, connection string, account key

AWS

S3

Bucket names, access key, secret key, region

GCP

GCS

Bucket names, service account JSON key


Next step

Once your infrastructure team has checked off the list above, proceed to the Deployment guide.

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