| name | architecture-review |
| description | Architecture evaluation criteria and technology standards for the homelab.
Preloaded into the designer agent to ground design decisions in established
patterns and principles.
Use when: (1) Evaluating a proposed technology addition, (2) Reviewing architecture decisions,
(3) Assessing stack fit for a new component, (4) Comparing implementation approaches.
Triggers: "architecture review", "evaluate technology", "stack fit", "should we use",
"technology comparison", "design review", "architecture decision"
|
| user-invocable | false |
Architecture Evaluation Framework
Current Technology Stack
Current technology stack: see references/technology-decisions.md
Evaluation Criteria
When evaluating any proposed technology addition or architecture change, score against these criteria:
1. Principle Alignment
Score each core principle (Strong/Weak/Neutral):
- Enterprise at Home: Does it reflect production-grade patterns?
- Everything as Code: Can it be fully represented in git?
- Automation is Key: Does it reduce or increase manual toil?
- Learning First: Does it teach valuable enterprise skills?
- DRY and Code Reuse: Does it leverage existing patterns or create duplication?
2. Stack Fit
- Does this overlap with existing tools? (e.g., adding Redis when Dragonfly exists)
- Does it integrate with the GitOps workflow? (Must be Flux-deployable)
- Does it work on bare-metal? (No cloud-only services)
- Does it support the multi-cluster model? (dev → integration → live)
3. Operational Cost
- How is it monitored? (Must integrate with kube-prometheus-stack)
- How is it backed up? (Must have a recovery story)
- How does it handle upgrades? (Must be declarative, ideally via Renovate)
- What's the failure blast radius? (Isolated > cluster-wide)
4. Complexity Budget
- Is the complexity justified by the learning value?
- Could a simpler existing tool solve the same problem?
- What's the maintenance burden over 12 months?
5. Alternative Analysis
- What existing stack components could solve this? (Always check first)
- What are the top 2-3 alternatives in the ecosystem?
- What do other production homelabs use? (kubesearch research)
6. Failure Modes
- What happens when this component is unavailable?
- How does it interact with network policies? (Default deny)
- What's the recovery procedure? (Must be documented in a runbook)
- Can it self-heal? (Strong preference for self-healing)
Anti-Patterns to Challenge
| Anti-Pattern | Why It's Wrong | Correct Approach |
|---|
| "Just run a container" without monitoring | Invisible failures, no alerting | ServiceMonitor + PrometheusRule required |
| Adding a new tool when existing ones suffice | Stack bloat, maintenance burden | Evaluate existing stack first |
| Skipping observability "for now" | Technical debt that never gets paid | Monitoring is day-1, not day-2 |
| Cloud-only services | Vendor lock-in, can't run on bare-metal | Self-hosted alternatives preferred |
| Single-instance without HA story | Single point of failure | At minimum, document recovery procedure |
