151 lines
7.0 KiB
Markdown
151 lines
7.0 KiB
Markdown
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---
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name: cloud-deploy-cli
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description: Use when the user asks to deploy a project, create/manage a cloud deployment, roll back a release, tail production logs, or run a cloud command for Railway, Vercel, AWS, Azure, or Google Cloud. Triggers on keywords like "deploy", "railway up", "vercel deploy", "aws cli", "az ", "gcloud", "ship it", "push to prod", "cloud CLI", "rollback". Installs and drives the cloud provider's CLI so the agent can deploy on its own.
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---
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# Cloud deployment CLIs — let the agent deploy on its own
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The agent should run the deploy command itself, not hand the user a link to a web console. Pick the CLI for the user's cloud and run it.
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## Pick the CLI by what the user named
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| Cloud | CLI binary | Install (macOS) | Install (other) |
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|---|---|---|---|
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| Railway | `railway` | `brew install railway` / `npm i -g @railway/cli` | `sh -c "$(curl -fsSL cli.railway.app/install.sh)"` |
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| Vercel | `vercel` | `npm i -g vercel` | same |
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| AWS | `aws` | `brew install awscli` | `pip install awscli` / `winget install Amazon.AWSCLI` |
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| Azure | `az` | `brew install azure-cli` | `winget install Microsoft.AzureCLI` / `curl -sL https://aka.ms/InstallAzureCLIDeb \| sudo bash` |
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| Google Cloud | `gcloud` | `brew install --cask google-cloud-sdk` | `winget install Google.CloudSDK` / install from cloud.google.com/sdk |
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If the user said "deploy" without naming a cloud, ask which one (use the `question` tool) — or infer from repo files: `vercel.json` → Vercel, `railway.toml`/`Railway.json` → Railway, `appspec.yml`/`.ebextensions` → AWS, `azure-pipelines.yml`/`appservice` → Azure, `app.yaml`/`Dockerfile`+GCP files → GCP.
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Verify install: `<cli> --version`. If missing, install it (table above) then continue.
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## Authenticate (one-time per CLI)
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```bash
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railway login # browser login
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vercel login # browser login (vercel link on first deploy in a repo)
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aws configure # prompts for Access Key ID, Secret, region, output
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az login # browser login
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gcloud auth login # browser login; then gcloud config set project <PROJECT_ID>
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```
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For headless/agent runs use env vars instead of interactive login:
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| CLI | Env vars |
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|---|---|
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| Railway | `RAILWAY_TOKEN` (from Railway dashboard → Settings → API Tokens) |
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| Vercel | `VERCEL_TOKEN` (or `VERCEL_ORG_ID` + `VERCEL_PROJECT_ID` after `vercel link`) |
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| AWS | `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_REGION` (or `AWS_PROFILE`) |
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| Azure | `az login --service-principal -u <app-id> -p <cert/password> --tenant <tenant>` |
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| Google | `gcloud auth activate-service-account --key-file=<sa.json>` then `GOOGLE_APPLICATION_CREDENTIALS=<sa.json>` |
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## Railway
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```bash
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railway link # bind cwd to a Railway project/service
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railway up # deploy current directory (detected buildpack or Dockerfile)
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railway up --service api # deploy to a specific service
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railway status # current deployment, URL
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railway logs # tail live logs
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railway variables # view env vars (railway variables set KEY=val to add)
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railway rollback # revert to the previous deployment
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```
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## Vercel
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```bash
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vercel link # bind repo (writes .vercel/ with org + project IDs)
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vercel # preview deploy; prints a *.vercel.app URL
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vercel --prod # production deploy (uses production domain)
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vercel logs <url> # tail function/build logs
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vercel env ls # vercel env add KEY (then vercel --prod to redeploy)
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vercel rm <url> # remove a deployment
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vercel inspect <url> # build/runtime details
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```
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For a fully scripted agent deploy:
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```bash
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vercel --prod --yes --token "$VERCEL_TOKEN"
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# --yes skips all prompts; requires .vercel/ linked (vercel link --yes --token $TOKEN)
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```
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## AWS
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AWS is broad — only use it when the user names a specific AWS service. Common agent tasks:
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```bash
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# S3
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aws s3 sync ./dist s3://<bucket>/ --delete
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aws s3 presign s3://<bucket>/file.zip --expires-in 3600
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# Lambda
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aws lambda update-function-code --function-name <fn> --zip-file fileb://fn.zip
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aws lambda invoke --function-name <fn> --payload fileb://event.json out.json
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# ECS
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aws ecs update-service --cluster <c> --service <s> --force-new-deployment
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aws ecs describe-services --cluster <c> --services <s>
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# Logs (CloudWatch Logs)
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aws logs tail /aws/lambda/<fn> --follow
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aws logs get-log-events --log-group-name <g> --log-stream-name <s>
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# Elastic Beanstalk
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eb deploy # needs `eb` CLI (brew install aws-elasticbeanstalk)
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```
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Always pass `--region <region>` or rely on `aws configure`'s default. For `--query`/`--output text|json` to get parseable results.
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## Azure
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```bash
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az group list -o table
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az webapp up --runtime "NODE:20-lts" --sku F1 -n <app> -g <group> # one-shot deploy from cwd
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az webapp deployment source config --name <app> -g <group> --repo-url <git> --branch main
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az webapp log tail -n <app> -g <group>
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az webapp config appsettings set -n <app> -g <group> --settings KEY=val
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az functionapp deployment source config-zip -g <group> -n <fn> --src ./deploy.zip
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```
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`-o table|json|tsv` controls output; `--query` for JMESPath filtering.
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## Google Cloud
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```bash
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gcloud config set project <PROJECT_ID>
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gcloud app deploy # App Engine
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gcloud run deploy <svc> --source . --region <r> --allow-unauthenticated # Cloud Run
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gcloud run services list
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gcloud run services describe <svc> --region <r>
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gcloud functions deploy <fn> --runtime nodejs20 --trigger-http --allow-unauthenticated
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gcloud app logs tail -s default
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gcloud builds submit --tag gcr.io/<proj>/<img>
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```
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## When to use
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- "Deploy this" / "ship to prod" / "push to staging" with a cloud named or inferable from repo files
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- "Roll back the last deploy" / "tail the logs" / "restart the service"
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- "Set env var KEY=val on the deployed app" then redeploy
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- Any cloud CLI operation where the agent would otherwise say "go to the dashboard"
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## When NOT to use
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- Just running the app locally → use the project's dev server, not a cloud deploy
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- Building a Docker image for local use → `docker build`; only deploy to cloud if the user asks
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- Provisioning infra from scratch (VPCs, databases, IAM) → confirm scope first; these CLIs can do it but the user should explicitly ask before the agent creates billable resources
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## Gotchas
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- Always confirm the **environment** (production vs preview/staging) before `--prod`/production deploys. Prefer a preview deploy first; ask before promoting.
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- `vercel` without `--prod` is a safe preview; `vercel --prod` hits the real domain.
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- Railway/Vercel deploys read the repo's build config — check `package.json` scripts / `Dockerfile` / `vercel.json` / `railway.toml` before deploying so the agent knows what will run.
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- AWS/Azure/GCP commands can create billable resources; only run provisioning when the user explicitly asked for it.
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## Source
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Referenced in https://x.com/heyshruti7/status/2069083108092350823 — "Your cloud's CLI — every cloud ships one so your agent can deploy on its own: Railway, Vercel, AWS, Azure, Google Cloud."
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