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gofireflyio/aiac

Artificial Intelligence Infrastructure-as-Code Generator. observed · 2026-08-28

github.com/gofireflyio/aiac · Go · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

55/100

  • Activity 73
  • Release rhythm 8
  • Longevity 97
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1365
  • days_rel: 673
  • days_push: 162
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

3786 stars · 295 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

aiac is a command line tool and Go library that uses LLM providers such as OpenAI, Amazon Bedrock, and Ollama to generate Infrastructure-as-Code templates, configuration files, CI/CD pipelines, and policy-as-code from natural language prompts. It composes requests to the selected model backend, saves the generated code to a file or stdout, and supports multiple configurable backends.

Use cases

  • generate terraform code from a text prompt
  • create dockerfile or kubernetes manifests using an llm
  • generate ci/cd pipelines like jenkins or github actions with ai
  • write opa policy as code from a description
  • generate pulumi or cloudformation templates via chatgpt or bedrock
  • use a local llm with ollama to produce infrastructure code
  • build shell scripts or query snippets from natural language

When to choose

  • you want to scaffold terraform, pulumi, or cloudformation templates quickly from plain-english prompts
  • you need to generate dockerfiles, k8s manifests, ci/cd pipelines, or policy-as-code without writing boilerplate by hand
  • you want a scriptable cli that can target multiple llm providers including local models via ollama
  • you prefer storing generated iac to files or piping it into your existing devops workflow

When to avoid

  • you need guaranteed-correct, production-ready infrastructure code without human review, since llm output must be validated
  • you require an interactive ide plugin or gui rather than a command line tool
  • you cannot access any llm provider (cloud or local) due to network or policy restrictions
  • you need deep drift detection or state management for existing infrastructure, which is the job of terraform or pulumi themselves

Facets

cli-tool · maturity active

infrastructure-as-code llm-inference cli infrastructure-as-code cloud-computing artificial-intelligence large-language-models developer-tools cli go cross-platform terraform pulumi cloudformation openai amazon-bedrock ollama iac-generator llm-codegen devops-automation policy-as-code code-generation devops command-line docker

1 source

Member repositories

RepositoryRoleHealth v2
gofireflyio/aiacmain55

For agents

markdown · JSON · MCP: product_card(name="gofireflyio/aiac")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem