Extensions
Extensions are optional add-ons for organisations with specific needs. They are not required for core Fawkes functionality.
What Is Core vs Extension?
Core Fawkes provides everything needed to run a production-grade Internal Developer Platform out of the box:
- GitOps delivery with ArgoCD
- Developer portal with Backstage
- CI/CD pipelines with Jenkins
- Observability (Prometheus, Grafana, OpenSearch, Tempo)
- Security scanning (SonarQube, Trivy, Vault)
- Collaboration (Mattermost, Focalboard)
- DORA metrics collection and dashboards
- Dojo learning environment
Extensions add advanced capabilities that come with meaningful operational overhead. They are designed for organisations that have already stabilised the core platform and have a specific need.
Available Extensions
Data Platform
Directory:
extensions/data-platform/
Adds data cataloging, lineage tracking, and data quality validation.
| Component | Purpose |
|---|---|
| DataHub | Enterprise data catalog — discover, document, and track lineage across datasets |
| Great Expectations | Data quality validation with Prometheus metrics export |
When to add: Your organisation manages multiple data sources and needs a catalog, or you have data quality requirements that need automated validation.
Resource cost: 4–8 GB RAM, 4 vCPU additional. Requires OpenSearch (Tier 2).
the Data Platform Extension (available in the repository under extensions/data-platform/)
AI
Directory:
extensions/ai/
Adds a vector database and Retrieval-Augmented Generation (RAG) service for semantic search and LLM-powered tooling.
| Component | Purpose |
|---|---|
| Weaviate | Vector database for storing and querying AI embeddings |
| RAG Service | FastAPI service providing semantic search over platform knowledge |
When to add: You are building LLM-powered developer tooling, need semantic search over internal documentation, or want to experiment with AI-assisted platform capabilities.
Resource cost: 2–4 GB RAM, 2 vCPU additional.
the AI Extension (available in the repository under extensions/ai/)
Deployment Pattern
Extensions are self-contained ArgoCD Application manifests in the extensions/
directory. They are not included in the core platform/apps/ bootstrap, so
they will not be deployed unless explicitly applied.
# Example: deploy the AI extension
kubectl apply -f extensions/ai/weaviate-application.yaml -n fawkes
kubectl apply -f extensions/ai/rag-service-application.yaml -n fawkes
Extension Design Principles
- Opt-in: Extensions are never deployed by
make dev-upor the core bootstrap. - Self-contained: Each extension directory includes all manifests, Helm values, and documentation needed to deploy it independently.
- Documented trade-offs: Every extension README lists resource costs, prerequisites, and operational considerations.
See Also
- Core Architecture — overview of what is included in the core platform
- AI Documentation — AI usage policy, Copilot setup, and more
- Data Platform Documentation — DataHub and data quality guides