> Operational traps for Terraform provisioners, multi-environment isolation, and zero-to-deployment reliability. Use when writing null_resource / remote-exec / local-exec / file provisioners, setting up fresh instances with cloud-init, or any IaC code that SSHs into remote hosts; when creating multi-environment Terraform setups (DNS record duplication, snapshot cross-contamination); or when debugging containers that are Restarting/unhealthy after terraform apply. Also when the user mentions terraform plan/apply errors, provisioner failures, infrastructure drift, TLS certificate errors, Cloudflare credential format, or Caddy/gateway / Caddyfile / compose configuration.
npx skills add https://github.com/daymade/claude-code-skills --skill terraform-skill
Failure patterns from real deployments. Every item caused an incident. Organized as: exact error → root cause → copy-paste fix.
docker: not found in remote-execcloud-init still installing Docker when provisioner SSHs in.
provisioner "remote-exec" {
inline = [
"cloud-init status --wait || true",
"which docker || { echo 'FATAL: Docker not ready'; exit 1; }",
]
}
rsync: connection unexpectedly closed in local-execTerraform holds its SSH connection open; local-exec rsync opens a second one that gets rejected. Never use local-exec for file transfer to remote. Use tarball + file provisioner:
provisioner "local-exec" {
command = "tar czf /tmp/src.tar.gz --exclude=node_modules --exclude=.git -C ${path.module}/../../.. myproject"
}
provisioner "file" {
source = "/tmp/src.tar.gz"
destination = "/tmp/src.tar.gz"
}
provisioner "remote-exec" {
inline = ["tar xzf /tmp/src.tar.gz -C /data/ && rm -f /tmp/src.tar.gz"]
}
macOS BSD tar: --exclude must come BEFORE the source argument.
cloud-init status shows "running" foreverapt-get -y does not suppress debconf dialogs. Packages like iptables-persistent block on TTY prompts.
- |
echo iptables-persistent iptables-persistent/autosave_v4 boolean true | debconf-set-selections
echo iptables-persistent iptables-persistent/autosave_v6 boolean true | debconf-set-selections
DEBIAN_FRONTEND=noninteractive apt-get install -y iptables-persistent
Known offenders: iptables-persistent, postfix, mysql-server, wireshark-common.
EACCES: permission denied in container logs, container RestartingHost volume dirs are root-owned; container runs as non-root (uid 1001). Fix before docker compose up:
mkdir -p /data/myapp/data /data/myapp/logs
chown -R 1001:1001 /data/myapp/data /data/myapp/logs
Find UID: grep adduser.*-u or USER in Dockerfile.
set -e exits on first error, hiding subsequent docker logs output. Use set -u without -e, put one verification gate at the end:
provisioner "remote-exec" {
inline = [
"set -u",
"docker compose up -d",
"sleep 15",
"docker logs myapp --tail 20 2>&1 || true",
"docker ps --format 'table {{.Names}}\\t{{.Status}}' || true",
"docker ps --filter name=myapp --format '{{.Status}}' | grep -q healthy || exit 1",
]
}
Restarting — database tables missingDB migrations not in provisioner. PostgreSQL docker-entrypoint-initdb.d only runs on empty data dir. Explicitly create DB + run migrations:
# After postgres healthy:
docker exec pg psql -U postgres -tc "SELECT 1 FROM pg_database WHERE datname='mydb'" | grep -q 1 \
|| docker exec pg psql -U postgres -c "CREATE DATABASE mydb;"
# Idempotent migrations:
for f in migrations/*.sql; do
VER=$(basename $f)
APPLIED=$($PSQL -tAc "SELECT 1 FROM schema_migrations WHERE version='$VER'" | tr -d ' ')
[ "$APPLIED" = "1" ] && continue
{ echo 'BEGIN;'; cat $f; echo 'COMMIT;'; } | $PSQL
$PSQL -tAc "INSERT INTO schema_migrations(version) VALUES ('$VER') ON CONFLICT DO NOTHING"
done
docker compose build ignores env var overrideCompose reads build args from .env file, not shell env. VAR=x docker compose build does NOT work.
# WRONG
DOCKER_WITH_PROXY_MODE=disabled docker compose build
# RIGHT
grep -q DOCKER_WITH_PROXY_MODE .env || echo 'DOCKER_WITH_PROXY_MODE=disabled' >> .env
docker compose build
Invalid format for Authorization headerCaddy DNS-01 ACME needs a Cloudflare API Token (cfut_ prefix, 40+ chars, Bearer auth). A Global API Key (37 hex chars, X-Auth-Key auth) causes HTTP 400 Code:6003. Production may appear to work because it has cached certificates; fresh environments fail on first cert request.
# Verify token format before deploy:
TOKEN=$(grep CLOUDFLARE_API_TOKEN .env | cut -d= -f2)
echo "$TOKEN" | grep -q "^cfut_" || echo "FATAL: needs API Token, not Global Key"
Create scoped token via API:
curl -s "https://api.cloudflare.com/client/v4/user/tokens" -X POST \
-H "X-Auth-Email: $CF_EMAIL" -H "X-Auth-Key: $CF_GLOBAL_KEY" \
-d '{"name":"caddy-dns-acme","policies":[{"effect":"allow",
"resources":{"com.cloudflare.api.account.zone.<ZONE_ID>":"*"},
"permission_groups":[
{"id":"4755a26eedb94da69e1066d98aa820be","name":"DNS Write"},
{"id":"c8fed203ed3043cba015a93ad1616f1f","name":"Zone Read"}]}]}'
Caddyfile or compose has literal domain names. Staging Caddy loads production config, tries to get certs for domains it doesn't own → ACME fails.
Caddyfile: Use {$VAR} — Caddy evaluates env vars at startup.
# WRONG
example.com { tls { dns cloudflare {env.CLOUDFLARE_API_TOKEN} } }
# RIGHT
{$LOBEHUB_DOMAIN} { tls { dns cloudflare {env.CLOUDFLARE_API_TOKEN} } }
Compose: Use ${VAR:?required} — fail-fast if unset.
# WRONG
- APP_URL=https://example.com
# RIGHT
- APP_URL=${APP_URL:?APP_URL is required}
Pass the env var to the gateway container so Caddy can read it:
environment:
- LOBEHUB_DOMAIN=${LOBEHUB_DOMAIN:?LOBEHUB_DOMAIN is required}
- CLOUDFLARE_API_TOKEN=${CLOUDFLARE_API_TOKEN:?required for DNS-01 TLS}
Social sign in failedCasdoor init_data.json contains hardcoded redirect URIs. --createDatabase=true only applies init_data on first-ever DB creation — not on restarts. Fix via SQL in provisioner:
# Replace production domain with staging in existing Casdoor DB
$PSQL -c "UPDATE application SET redirect_uris = REPLACE(redirect_uris,
'example.com', 'staging.example.com')
WHERE name='lobechat'
AND redirect_uris LIKE '%example.com%'
AND redirect_uris NOT LIKE '%staging.example.com%';"
Also check AUTH_CASDOOR_ISSUER — it must match the Casdoor subdomain (auth.staging.example.com), not the app root domain.
Before creating a second environment, grep .tf files for hardcoded names. See references/multi-env-isolation.md for the complete matrix.
Will fail on apply (globally unique):
| Resource | Scope | Fix |
|---|---|---|
| SSH key pair | Region | "${env}-deploy" |
| SLS log project | Account | "${env}-logs" |
| CloudMonitor contact | Account | "${env}-ops" |
DNS duplication trap: Two environments creating A records for the same name in the same Cloudflare zone → two independent record IDs → DNS round-robin → ~50% traffic to wrong instance. Fix: use subdomain isolation (staging.example.com) or separate zones. Remember to create DNS records for ALL subdomains Caddy serves (e.g., auth.staging, minio.staging).
Snapshot cross-contamination: Unfiltered data "alicloud_ecs_snapshots" returns ALL account snapshots. New env inherits old 100GB snapshot, fails creating 40GB disk. Gate with variable:
locals {
latest_snapshot_id = var.enable_snapshot_recovery && length(local.available_snapshots) > 0
? local.available_snapshots[0].snapshot_id : null
}
Do NOT add count to the data source — changes its state address, causes drift.
Run a validation script before terraform apply to catch configuration errors locally. This eliminates the deploy→discover→fix→redeploy cycle.
Key checks (see references/pre-deploy-validation.md):
terraform validate — syntaxLOBEHUB_DOMAIN, CLAUDE4DEV_DOMAIN, CLOUDFLARE_API_TOKEN, APP_URL, etc.)auth.* subdomainIntegrate into Makefile: make pre-deploy ENV=staging before make apply.
Fresh disks expose every implicit dependency. See references/zero-to-deploy-checklist.md.
Key items that break provisioners on fresh instances:
mkdir -p /data/{svc1,svc2} in cloud-init — file provisioner fails if target dir missingCREATE DATABASE — PG init scripts only run on empty data dirschema_migrations table, applied idempotentlydepends_on between resources sharing Docker networks{$VAR} / ${VAR:?required}cfut_), not Global API KeyAssess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take daymade/terraform-skill from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference apt.
Without those the skill loads but fails at the first command.