Deploy anything
TL;DR — Tell
@git-apewhat you want, in plain language. Or hand it a reference architecture link, diagram, or screenshot. Either way, it generates a CAF-compliant ARM template with security, cost, and policy enforced before deployment.
Git-Ape is workload-agnostic. If Azure Resource Manager can deploy it, the agent can generate it — using the live Azure REST API specs at generation time, not last year's module catalogue.
Three ways to describe what you want
| Input | Example prompt |
|---|---|
| Plain intent | @git-ape deploy a .NET web app with SQL Database for the customer portal in dev |
| Reference architecture | @git-ape implement this reference architecture: https://learn.microsoft.com/azure/architecture/reference-architectures/... |
| Diagram or picture | Attach a PNG or markdown with mermaid, then: @git-ape deploy what's in this diagram for the payments-api project |
The agent reads the input, asks clarifying questions only when needed (region, environment, project name), and produces a full deployment plan you can review before approval.
Example 1 — Web app with SQL Database
A common full-stack pattern: App Service with managed identity to SQL Database, secrets in Key Vault.
Prompt:
@git-ape deploy a .NET web app with SQL Database and Key Vault
for the customer-portal project in dev, eastus
What you get:
| Resource | Key settings enforced automatically |
|---|---|
| App Service | HTTPS-only, TLS 1.2, managed identity, FTP disabled |
| SQL Server | azureADOnlyAuthentication: true — no SQL username/password |
| SQL Database | Standard S1, geo-backup enabled |
| Key Vault | RBAC authorization, soft-delete + purge protection |
| RBAC | App Service → SQL DB Contributor, App Service → Key Vault Secrets User |
Example 2 — Container Apps
A containerised microservice with auto-scaling, private registry, and centralised logging.
Prompt:
@git-ape deploy a Container App with Registry and Log Analytics
for the payments-api project in dev, eastus
What you get:
| Resource | Key settings enforced automatically |
|---|---|
| Container App | Min replicas: 0, max: 10, scale on HTTP concurrency |
| Container Apps Environment | Connected to Log Analytics workspace |
| Container Registry | Admin user disabled, managed identity pull only |
| RBAC | Container App → AcrPull on registry |
| Log Analytics | 30-day retention |
Use a reference architecture as the source of truth
The Git-Ape Vision describes a future state where governed documents — reference architectures, ADRs, security baselines — become the ledger that drives deployments. The agent's job is to compile those documents into compliant infrastructure.
You can do this today:
- Point the agent at a published Azure reference architecture URL. The agent fetches it, identifies the resources, and produces an ARM template that matches.
- Attach a diagram or screenshot of an internal architecture pattern. The agent reads the boxes and arrows and proposes a deployment.
- Reference an Architecture Decision Record (ADR) in your repo. The agent treats the ADR as authoritative and validates the generated template against it.
@git-ape deploy this reference architecture for the order-api project, dev:
https://learn.microsoft.com/azure/architecture/reference-architectures/...
Whatever you use as input, the agent produces the same artifacts: a CAF-compliant ARM template, a security analysis, a cost estimate, and a deployment trace under .azure/deployments/ — your auditable evidence of intent → plan → outcome.
What happens after you approve
See the full lifecycle in State Management and CI/CD Pipeline.
Related
- Vision & Manifesto — why agents over modules
- Security Analysis — what the security gate checks
- Cost Estimation — how pricing is computed
- Skills overview — every capability the agent invokes