Deployment

Work in Progress

This deployment documentation is currently being enhanced and refined. Some sections may be incomplete or subject to change. We're actively working on comprehensive examples and troubleshooting guides for all platforms.

flAPI is designed for deployment flexibility. Available as a single binary or Docker container, it runs on any platform that supports Linux containers or x86-64 binaries.

Quick Start

🚀 Interactive Deployment Configurator

Configure your deployment with config mounting strategy

Platform

Configuration Strategy

Mount config from host filesystem

Region

Memory

CPU

Environment Variables (optional)

Generated Configuration

# 1. Create directory structure on host
mkdir -p ~/flapi/{config/sqls,data}

# 2. Create your flapi.yaml
cat > ~/flapi/config/flapi.yaml <<EOF
project_name: my-api
template:
  path: '/config/sqls'
connections:
  # Your connections here
duckdb:
  db_path: /data/flapi.db
EOF

# 3. Add your SQL templates
# cp your_templates.yaml ~/flapi/config/sqls/

# 4. Create docker-compose.yml
cat > ~/flapi/docker-compose.yml <<EOF
version: '3.8'
services:
  flapi:
    image: ghcr.io/datazoode/flapi:latest
    ports:
      - "8080:8080"
    volumes:
      - ./config:/config:ro
      - ./data:/data
    restart: unless-stopped
    deploy:
      resources:
        limits:
          cpus: '1'
          memory: 2G
EOF

# 5. Deploy
cd ~/flapi && docker-compose up -d

💡 Tip: Your config must include flapi.yaml and SQL templates in /config directory

Requirements

Resource	Minimum	Recommended	Notes
CPU	1 vCPU	2 vCPU	DuckDB is CPU-intensive for aggregations
Memory	1 GB	2-4 GB	Depends on cache size
Storage	1 GB	10 GB+	For DuckDB cache persistence
Port	8080	-	Default HTTP port
Startup	< 100ms	-	Fast cold starts for serverless

Configuration Management

Critical

flAPI requires configuration files to function. The base Docker image (ghcr.io/datazoode/flapi:latest) contains only the binary - you must mount your configuration to run it.

Standard Directory Structure

flAPI expects the following structure:

/config/
├── flapi.yaml           # Main configuration file (required)
└── sqls/                # SQL template directory (required)
    ├── users.yaml       # Endpoint definitions
    ├── products.yaml
    └── orders.yaml

Minimal Example Configuration

Create flapi.yaml:

config/flapi.yaml
project_name: my-api
project_description: My flAPI deployment

template:
  path: '/config/sqls'  # Path to SQL templates

connections:
  postgres:
    connection_string: "postgresql://user:pass@host:5432/db"

duckdb:
  db_path: /data/flapi.db  # Cache database location
  access_mode: READ_WRITE

Create your first endpoint sqls/users.yaml:

config/sqls/users.yaml
url-path: /users
sql: |
  SELECT * FROM users
  WHERE active = true
  LIMIT 100

Configuration Mounting Strategies

Choose the approach that fits your deployment platform:

1️⃣ Local Volume Mount (Docker, VPS, K8s)

Best for: Development, VPS deployment, on-premises

Mount your local config directory directly into the container:

docker run -d \
  -p 8080:8080 \
  -v $(pwd)/config:/config:ro \
  -v $(pwd)/data:/data \
ghcr.io/datazoode/flapi:latest

Advantages:

✅ Simple and direct
✅ Easy to update (edit files, restart container)
✅ Works with any text editor

Disadvantages:

❌ Requires host filesystem access
❌ Not suitable for serverless platforms

2️⃣ Kubernetes ConfigMap (K8s, IONOS, STACKIT)

Best for: Kubernetes deployments, multi-replica setups

Create ConfigMaps from your config files:

# Create ConfigMap for main config
kubectl create configmap flapi-config \
  --from-file=flapi.yaml=./config/flapi.yaml \
  --namespace=flapi

# Create ConfigMap for SQL templates
kubectl create configmap flapi-sqls \
  --from-file=./config/sqls/ \
  --namespace=flapi

Mount in your Deployment:

volumeMounts:
- name: config
  mountPath: /config/flapi.yaml
  subPath: flapi.yaml
- name: sqls
  mountPath: /config/sqls

volumes:
- name: config
  configMap:
    name: flapi-config
- name: sqls
  configMap:
    name: flapi-sqls

Advantages:

✅ Native Kubernetes integration
✅ Version controlled via kubectl
✅ Can be updated without rebuilding images

Disadvantages:

❌ ConfigMap size limit (1MB)
❌ Requires kubectl access to update

tip

For large SQL template collections, use PersistentVolumes instead of ConfigMaps.

3️⃣ Cloud Storage Mount (Cloud Run, Lambda, Azure)

Best for: Serverless platforms, multi-region deployments

Google Cloud Run (GCS Bucket):

# 1. Upload config
gsutil -m cp -r ./config gs://my-bucket/flapi-config/

# 2. Deploy with GCS mount
gcloud run deploy flapi \
  --image ghcr.io/datazoode/flapi:latest \
  --add-volume=name=config,type=cloud-storage,bucket=my-bucket \
  --add-volume-mount=volume=config,mount-path=/config

AWS Lambda (EFS Mount):

# 1. Create EFS file system
aws efs create-file-system --tags Key=Name,Value=flapi-config

# 2. Mount EFS to EC2, upload config to /config

# 3. Create Lambda with EFS mount
aws lambda create-function \
  --function-name flapi \
  --file-system-configs "Arn=arn:aws:elasticfilesystem:...,LocalMountPath=/config"

Advantages:

✅ Works with serverless platforms
✅ Centralized configuration storage
✅ Can be shared across multiple instances

Disadvantages:

❌ Increased cold start time
❌ Additional cost for storage
❌ More complex setup

4️⃣ Baked-In Configuration (Custom Image)

Best for: Immutable deployments, CI/CD pipelines

Create a custom Docker image with config baked in:

Dockerfile
FROM ghcr.io/datazoode/flapi:latest

# Copy configuration into image
COPY config/flapi.yaml /config/flapi.yaml
COPY config/sqls /config/sqls

# Optional: Set environment variables
ENV FLAPI_CONFIG=/config/flapi.yaml

CMD ["/app/flapi", "-c", "/config/flapi.yaml"]

Build and deploy:

docker build -t my-org/flapi:v1.0 .
docker push my-org/flapi:v1.0

Advantages:

✅ Self-contained, portable image
✅ Fastest cold start (no external mounts)
✅ Works on any platform

Disadvantages:

❌ Config changes require image rebuild
❌ Larger image size
❌ Less flexible

Security

Never bake secrets (database passwords, API keys) into images. Use environment variables or secret management instead.

Configuration Update Strategies

Platform	Update Method	Downtime	Rollback
Docker Compose	Edit files → `docker-compose restart`	< 1s	Manual (git revert)
Kubernetes	`kubectl apply configmap` → Rolling update	0s	`kubectl rollout undo`
Cloud Run	Update GCS bucket → Redeploy	~30s	Deploy previous revision
Custom Image	Rebuild → Push → Deploy	~2-5min	Deploy previous tag

Configuration Validation

Before deploying, validate your configuration:

# Run flAPI locally to check for errors
docker run --rm \
  -v $(pwd)/config:/config \
  ghcr.io/datazoode/flapi:latest \
  --dry-run

# Check YAML syntax
yamllint config/flapi.yaml config/sqls/*.yaml

# Test SQL templates
# (flAPI will validate SQL on startup)

Environment Variables

Override config values using environment variables:

# Docker
docker run -e FLAPI_DB_PATH=/data/custom.db ...

# Kubernetes
env:
- name: FLAPI_DB_PATH
  value: /data/custom.db
- name: PG_PASSWORD
  valueFrom:
    secretKeyRef:
      name: db-secrets
      key: password

Common environment variables:

Variable	Purpose	Example
`FLAPI_CONFIG`	Override config file path	`/config/flapi.yaml`
`FLAPI_PORT`	Override HTTP port	`8080`
`FLAPI_LOG_LEVEL`	Set log verbosity	`debug`, `info`, `warn`

Enterprise Cloud Platforms

Google Cloud Run

Best for: Serverless container deployment with auto-scaling to zero

# Deploy to Cloud Run
gcloud run deploy flapi \
  --image ghcr.io/datazoode/flapi:latest \
  --platform managed \
  --region europe-west1 \
  --port 8080 \
  --memory 2Gi \
  --cpu 1 \
  --allow-unauthenticated \
  --set-env-vars="FLAPI_CONFIG=/config/flapi.yaml"

Pricing: Pay per request, scales to zero

Free tier: 2 million requests/month
Cost: ~$0.00002400 per request (beyond free tier)

AWS App Runner

Best for: Fully managed container service with simple deployment

# Create apprunner.yaml
version: 1.0
runtime: python3
build:
  commands:
    image: ghcr.io/datazoode/flapi:latest
run:
  runtime-version: 3.8
  command: /app/flapi -c /config/flapi.yaml
  network:
    port: 8080
  env:
    - name: FLAPI_ENV
      value: production

# Deploy
aws apprunner create-service \
  --service-name flapi \
  --source-configuration file://apprunner.yaml

Pricing: Pay for active time

Cost: ~$0.064/vCPU-hour + $0.007/GB-hour

AWS Lambda

Best for: Sporadic traffic patterns, event-driven workloads

# Package as container image
docker build -t flapi-lambda .

# Push to ECR
aws ecr get-login-password --region us-east-1 | \
  docker login --username AWS --password-stdin ACCOUNT.dkr.ecr.us-east-1.amazonaws.com
docker push ACCOUNT.dkr.ecr.us-east-1.amazonaws.com/flapi:latest

# Create function
aws lambda create-function \
  --function-name flapi \
  --package-type Image \
  --code ImageUri=ACCOUNT.dkr.ecr.us-east-1.amazonaws.com/flapi:latest \
  --role arn:aws:iam::ACCOUNT:role/lambda-flapi \
  --memory-size 2048 \
  --timeout 30 \
  --environment "Variables={FLAPI_CONFIG=/config/flapi.yaml}"

Cache Persistence

Lambda containers are ephemeral. Use EFS for persistent DuckDB cache:

--file-system-config Arn=arn:aws:elasticfilesystem:REGION:ACCOUNT:access-point/ACCESS_POINT

Pricing: Pay per invocation

Free tier: 1M requests + 400,000 GB-seconds/month
Cost: $0.20 per 1M requests + $0.0000166667 per GB-second

Azure Container Apps

Best for: Kubernetes-based microservices without cluster management

az containerapp create \
  --name flapi \
  --resource-group myResourceGroup \
  --image ghcr.io/datazoode/flapi:latest \
  --target-port 8080 \
  --ingress external \
  --min-replicas 1 \
  --max-replicas 10 \
  --cpu 1.0 \
  --memory 2.0Gi \
  --env-vars FLAPI_CONFIG=/config/flapi.yaml

Pricing: Pay for vCPU and memory

Cost: ~$0.000012/vCPU-second + $0.000002/GB-second

European Cloud Providers

IONOS Cloud

Best for: German/European data sovereignty, GDPR compliance

IONOS provides managed Kubernetes and container hosting with data centers in Germany and Spain.

# Install IONOS CLI
curl -sL https://github.com/ionos-cloud/ionosctl/releases/latest/download/ionosctl-linux-amd64.tar.gz | tar -xzv

# Create Kubernetes cluster (if not exists)
ionosctl k8s cluster create \
  --name flapi-cluster \
  --k8s-version 1.28 \
  --datacenter-id DATACENTER_ID

# Deploy flAPI
kubectl apply -f - <<EOF
apiVersion: apps/v1
kind: Deployment
metadata:
  name: flapi
  labels:
    app: flapi
spec:
  replicas: 2
  selector:
    matchLabels:
      app: flapi
  template:
    metadata:
      labels:
        app: flapi
    spec:
      containers:
      - name: flapi
        image: ghcr.io/datazoode/flapi:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "2Gi"
            cpu: "1"
          limits:
            memory: "4Gi"
            cpu: "2"
        volumeMounts:
        - name: config
          mountPath: /config
        - name: data
          mountPath: /data
      volumes:
      - name: config
        persistentVolumeClaim:
          claimName: flapi-config
      - name: data
        persistentVolumeClaim:
          claimName: flapi-data
---
apiVersion: v1
kind: Service
metadata:
  name: flapi
spec:
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: 8080
  selector:
    app: flapi
EOF

Key Features:

Data centers: Frankfurt (de/fra), Berlin (de/txl), Logroño (es/vit)
GDPR-compliant infrastructure
ISO 27001 certified
German support

Pricing: Managed Kubernetes

Cost: ~€0.10/hour per worker node + €0.01/GB storage

STACKIT

Best for: Schwarz Group ecosystem, German cloud sovereignty

# Create STACKIT Kubernetes cluster via portal or CLI
stackit kubernetes cluster create \
  --project-id PROJECT_ID \
  --name flapi-cluster

# Get kubeconfig
stackit kubernetes credentials get \
  --cluster-id CLUSTER_ID \
  --project-id PROJECT_ID

# Deploy flAPI
kubectl apply -f - <<EOF
apiVersion: apps/v1
kind: Deployment
metadata:
  name: flapi
spec:
  replicas: 2
  selector:
    matchLabels:
      app: flapi
  template:
    metadata:
      labels:
        app: flapi
    spec:
      containers:
      - name: flapi
        image: ghcr.io/datazoode/flapi:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "2Gi"
            cpu: "1000m"
---
apiVersion: v1
kind: Service
metadata:
  name: flapi
spec:
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: 8080
  selector:
    app: flapi
EOF

Key Features:

German data centers (operated by Schwarz Digits)
Enterprise SLA
Direct integration with SAP systems
Carbon-neutral operations

Kubernetes

Generic Kubernetes Deployment

Best for: Multi-cloud portability, full control, enterprise scale

Create a complete flAPI deployment with persistent storage and horizontal scaling:

flapi-k8s.yaml
# Namespace
apiVersion: v1
kind: Namespace
metadata:
  name: flapi

---
# ConfigMap for flapi.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: flapi-config
  namespace: flapi
data:
  flapi.yaml: |
    project_name: production-api
    project_description: Production flAPI deployment
    template:
      path: '/config/sqls'
    connections:
      # Your connections here
    duckdb:
      db_path: /data/flapi.db
      access_mode: READ_WRITE

---
# PersistentVolumeClaim for DuckDB cache
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: flapi-data
  namespace: flapi
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 20Gi
  storageClassName: standard

---
# Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: flapi
  namespace: flapi
  labels:
    app: flapi
spec:
  replicas: 3
  selector:
    matchLabels:
      app: flapi
  template:
    metadata:
      labels:
        app: flapi
    spec:
      containers:
      - name: flapi
        image: ghcr.io/datazoode/flapi:latest
        ports:
        - containerPort: 8080
          name: http
        resources:
          requests:
            memory: "2Gi"
            cpu: "1"
          limits:
            memory: "4Gi"
            cpu: "2"
        volumeMounts:
        - name: config
          mountPath: /config
        - name: data
          mountPath: /data
        env:
        - name: FLAPI_ENV
          value: "production"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 10
          periodSeconds: 30
        readinessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 10
      volumes:
      - name: config
        configMap:
          name: flapi-config
      - name: data
        persistentVolumeClaim:
          claimName: flapi-data

---
# Service
apiVersion: v1
kind: Service
metadata:
  name: flapi
  namespace: flapi
spec:
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: 8080
    protocol: TCP
    name: http
  selector:
    app: flapi

---
# HorizontalPodAutoscaler
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: flapi
  namespace: flapi
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: flapi
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80

Deploy:

kubectl apply -f flapi-k8s.yaml

Ingress Configuration

For production deployments, add an Ingress with TLS:

flapi-ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: flapi
  namespace: flapi
  annotations:
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
spec:
  ingressClassName: nginx
  tls:
  - hosts:
    - api.yourdomain.com
    secretName: flapi-tls
  rules:
  - host: api.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: flapi
            port:
              number: 80

Indie Hacker Platforms

Fly.io

Best for: Edge deployment, global distribution, developer experience

# Install flyctl
curl -L https://fly.io/install.sh | sh

# Launch flAPI
fly launch \
  --image ghcr.io/datazoode/flapi:latest \
  --name flapi-app \
  --region fra \
  --vm-size shared-cpu-2x \
  --vm-memory 2048

# Add persistent volume for cache
fly volumes create flapi_data --region fra --size 10

# Update fly.toml for volume
cat > fly.toml <<EOF
app = "flapi-app"

[build]
  image = "ghcr.io/datazoode/flapi:latest"

[[mounts]]
  source = "flapi_data"
  destination = "/data"

[[services]]
  internal_port = 8080
  protocol = "tcp"

  [[services.ports]]
    handlers = ["http"]
    port = 80

  [[services.ports]]
    handlers = ["tls", "http"]
    port = 443
EOF

# Deploy
fly deploy

Pricing: Free tier available

Free: 3 shared-cpu-1x VMs (256MB RAM)
Paid: ~$0.0000022/second for shared-cpu-2x (2GB RAM)

Railway

Best for: Git-based deployment, simple setup, PostgreSQL integration

# Install Railway CLI
npm i -g @railway/cli

# Login
railway login

# Initialize project
railway init

# Deploy from Docker image
railway up --image ghcr.io/datazoode/flapi:latest

# Or use railway.json for configuration
cat > railway.json <<EOF
{
  "build": {
    "dockerImage": "ghcr.io/datazoode/flapi:latest"
  },
  "deploy": {
    "startCommand": "/app/flapi -c /config/flapi.yaml",
    "restartPolicyType": "ON_FAILURE",
    "healthcheckPath": "/health",
    "healthcheckTimeout": 100
  }
}
EOF

Pricing: $5 credit/month on free plan

Free: $5/month credit (covers ~500 hours)
Paid: $0.000231/GB-hour RAM + $0.00463/vCPU-hour

Render

Best for: Free tier for testing, managed services

# Create render.yaml
cat > render.yaml <<EOF
services:
  - type: web
    name: flapi
    env: docker
    image:
      url: ghcr.io/datazoode/flapi:latest
    plan: starter
    healthCheckPath: /health
    envVars:
      - key: FLAPI_ENV
        value: production
    disk:
      name: flapi-data
      mountPath: /data
      sizeGB: 10
EOF

# Deploy via Render Dashboard or CLI
render deploy

Pricing: Free tier available

Free: 750 hours/month, sleeps after inactivity
Starter: $7/month (persistent, no sleep)
Standard: $25/month (2 GB RAM, 1 vCPU)

DigitalOcean App Platform

Best for: Predictable pricing, managed databases, simple scaling

# Create .do/app.yaml
mkdir -p .do
cat > .do/app.yaml <<EOF
name: flapi
services:
- name: api
  image:
    registry_type: GHCR
    repository: datazoode/flapi
    tag: latest
  http_port: 8080
  instance_count: 2
  instance_size_slug: basic-xs
  routes:
  - path: /
  health_check:
    http_path: /health
  envs:
  - key: FLAPI_ENV
    value: production
EOF

# Deploy via doctl
doctl apps create --spec .do/app.yaml

# Or use DigitalOcean Dashboard

Pricing: Predictable monthly cost

Basic (512MB): $5/month
Basic (1GB): $12/month
Professional (2GB): $24/month

Cost-Effective VPS

Hetzner Cloud

Best for: European hosting, best price/performance ratio

# Create server via CLI
hcloud server create \
  --name flapi \
  --type cx21 \
  --image docker-ce \
  --ssh-key my-key

# SSH into server
ssh root@YOUR_SERVER_IP

# Create docker-compose.yml
cat > docker-compose.yml <<EOF
version: '3.8'
services:
  flapi:
    image: ghcr.io/datazoode/flapi:latest
    container_name: flapi
    restart: unless-stopped
    ports:
      - "8080:8080"
    volumes:
      - ./config:/config:ro
      - ./data:/data
      - ./sqls:/sqls:ro
    environment:
      - FLAPI_ENV=production
    deploy:
      resources:
        limits:
          cpus: '2'
          memory: 4G
        reservations:
          cpus: '1'
          memory: 2G
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  # Optional: Caddy for HTTPS
  caddy:
    image: caddy:latest
    container_name: caddy
    restart: unless-stopped
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./Caddyfile:/etc/caddy/Caddyfile:ro
      - caddy_data:/data
      - caddy_config:/config

volumes:
  caddy_data:
  caddy_config:
EOF

# Create Caddyfile for HTTPS
cat > Caddyfile <<EOF
api.yourdomain.com {
    reverse_proxy flapi:8080
    
    # Enable compression
    encode gzip
    
    # Security headers
    header {
        Strict-Transport-Security "max-age=31536000;"
        X-Content-Type-Options "nosniff"
        X-Frame-Options "DENY"
    }
}
EOF

# Start services
docker-compose up -d

# View logs
docker-compose logs -f flapi

Pricing: Excellent value

CX11 (2GB): €4.15/month (~$4.50)
CX21 (4GB): €5.83/month (~$6.35)
CX31 (8GB): €10.59/month (~$11.50)

Self-Hosted

Systemd Service (Linux Binary)

For running flAPI as a native Linux service without Docker:

# Download flAPI binary
curl -L https://github.com/datazoode/flapi/releases/latest/download/flapi \
  -o /usr/local/bin/flapi
chmod +x /usr/local/bin/flapi

# Create flapi user
sudo useradd -r -s /bin/false flapi

# Create directories
sudo mkdir -p /etc/flapi/{sqls,config}
sudo mkdir -p /var/lib/flapi/data
sudo chown -R flapi:flapi /etc/flapi /var/lib/flapi

# Create systemd service
sudo tee /etc/systemd/system/flapi.service > /dev/null <<EOF
[Unit]
Description=flAPI REST API Service
Documentation=https://flapi.io
After=network-online.target
Wants=network-online.target

[Service]
Type=simple
User=flapi
Group=flapi
ExecStart=/usr/local/bin/flapi -c /etc/flapi/flapi.yaml
Restart=always
RestartSec=5
StartLimitInterval=0
StartLimitBurst=5
WorkingDirectory=/var/lib/flapi

# Security hardening
NoNewPrivileges=true
PrivateTmp=true
ProtectSystem=strict
ProtectHome=true
ReadWritePaths=/var/lib/flapi

# Resource limits
LimitNOFILE=65536
MemoryLimit=4G

[Install]
WantedBy=multi-user.target
EOF

# Copy your configuration
sudo cp flapi.yaml /etc/flapi/
sudo cp -r sqls/* /etc/flapi/sqls/
sudo chown -R flapi:flapi /etc/flapi

# Enable and start
sudo systemctl daemon-reload
sudo systemctl enable flapi
sudo systemctl start flapi

# Check status
sudo systemctl status flapi

# View logs
sudo journalctl -u flapi -f

Production Checklist

Before deploying to production, ensure you have:

Security

Enable HTTPS/TLS (Let's Encrypt, Cloudflare, load balancer)
Configure authentication (JWT, API keys)
Set up rate limiting
Whitelist environment variables in config
Review row-level security in SQL templates
Use secrets management (not hardcoded)

Monitoring

Configure health check endpoint (/health)
Set up metrics collection (Prometheus, CloudWatch)
Configure logging (structured JSON logs)
Set up alerting (uptime, error rates, cache hits)
Monitor cache refresh success/failures

Performance

Size memory for your cache needs
Configure cache refresh schedules
Set up horizontal scaling (HPA)
Test under expected load
Configure connection pooling

Backup & Recovery

High Availability

Run multiple replicas (3+ for production)
Use load balancer with health checks
Configure pod/service disruption budgets
Set up multi-region if needed
Test failover scenarios

Troubleshooting

Port Already in Use

# Find process using port 8080
lsof -i :8080
sudo netstat -tulpn | grep 8080

# Kill process or use different port
flapi -c config.yaml --port 8081

Permission Denied (Docker)

# Run with correct user permissions
docker run --user $(id -u):$(id -g) \
  -v $(pwd)/config:/config \
  ghcr.io/datazoode/flapi:latest

Cache Not Persisting

# Ensure volume mount for DuckDB
-v $(pwd)/data:/data

# Check DuckDB path in config
duckdb:
  db_path: /data/flapi.db  # Must be on mounted volume

Memory Issues

# Increase container memory limits
docker run -m 4g ghcr.io/datazoode/flapi:latest

# Or in Kubernetes
resources:
  limits:
    memory: "4Gi"

Configuration Not Found

Error: flapi.yaml not found or Config file missing

# Check if config is mounted
docker exec CONTAINER_ID ls -la /config

# Should show:
# /config/flapi.yaml
# /config/sqls/

# Fix: Ensure volume mount is correct
docker run -v $(pwd)/config:/config:ro ...

# Or check ConfigMap in Kubernetes
kubectl describe configmap flapi-config -n flapi

SQL Templates Not Loading

Error: No endpoints found or Template directory empty

# Verify template path in flapi.yaml
template:
  path: '/config/sqls'  # Must match mounted path

# Check files exist
docker exec CONTAINER_ID ls -la /config/sqls

# Ensure YAML files have correct structure
cat config/sqls/users.yaml
# Must contain:
# url-path: /users
# sql: |
#   SELECT ...

Invalid YAML Syntax

Error: YAML parse error or Invalid configuration

# Validate YAML syntax locally
yamllint config/flapi.yaml

# Common issues:
# - Incorrect indentation (use spaces, not tabs)
# - Missing quotes around special characters
# - Trailing whitespace

# Test configuration before deploying
docker run --rm \
  -v $(pwd)/config:/config \
  ghcr.io/datazoode/flapi:latest \
  --dry-run

Connection Refused / Database Unreachable

Error: Connection refused or Host unreachable

# Inside container, host.docker.internal points to host machine
connections:
  postgres:
    connection_string: "postgresql://user:pass@host.docker.internal:5432/db"

# In Kubernetes, use service DNS
connections:
  postgres:
    connection_string: "postgresql://user:pass@postgres.default.svc.cluster.local:5432/db"

# Test connection from within container
docker exec CONTAINER_ID ping postgres-host

ConfigMap Size Limit Exceeded

Error: ConfigMap too large (> 1MB)

# Solution 1: Split into multiple ConfigMaps
kubectl create configmap flapi-sqls-users --from-file=./config/sqls/users/
kubectl create configmap flapi-sqls-products --from-file=./config/sqls/products/

# Solution 2: Use PersistentVolume instead
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: flapi-config
spec:
  accessModes:
    - ReadOnlyMany
  resources:
    requests:
      storage: 1Gi

# Upload config to PV manually or via init container

Read-Only Filesystem Errors

Error: Read-only file system when writing cache

# Ensure data directory is writable
docker run -v $(pwd)/data:/data ...  # No :ro flag

# In Kubernetes, use ReadWriteOnce PVC for /data
volumes:
- name: data
  persistentVolumeClaim:
    claimName: flapi-data  # Must be RWO, not RO

Environment Variable Not Working

Error: Config value not overridden by env var

# Check environment variables are set
docker exec CONTAINER_ID env | grep FLAPI

# Verify variable names match flAPI conventions
# Use UPPERCASE with underscores
FLAPI_DB_PATH=/data/custom.db  # ✅ Correct
flapi-db-path=/data/custom.db  # ❌ Wrong

# In Kubernetes, check pod env
kubectl describe pod flapi-xxx -n flapi | grep -A5 Environment

Cloud Storage Mount Failing

Google Cloud Run:

# Ensure service account has Storage Object Viewer role
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member=serviceAccount:SERVICE_ACCOUNT \
  --role=roles/storage.objectViewer

# Check bucket permissions
gsutil iam get gs://YOUR_BUCKET

# Verify files are in bucket
gsutil ls gs://YOUR_BUCKET/flapi-config/

AWS Lambda (EFS):

# Check EFS mount target is in same VPC as Lambda
aws efs describe-mount-targets --file-system-id fs-xxx

# Verify Lambda has VPC permissions
# Security groups must allow NFS (port 2049)

# Check EFS access point
aws efs describe-access-points --file-system-id fs-xxx

Startup Crashes / Immediate Exit

Error: Container starts then exits immediately

# Check logs for actual error
docker logs CONTAINER_ID
kubectl logs pod/flapi-xxx -n flapi

# Common causes:
# 1. Missing config file
# 2. Invalid YAML syntax
# 3. Database connection failure
# 4. Port already in use

# Run interactively to debug
docker run -it --rm \
  -v $(pwd)/config:/config \
  ghcr.io/datazoode/flapi:latest \
  sh

# Then manually test:
/app/flapi -c /config/flapi.yaml

Next Steps

Configuration: Learn about flapi.yaml options
Endpoints: Create your first API endpoints
Caching: Optimize performance with caching
Authentication: Secure your APIs

Need help with deployment? Check out our professional services or join the community.

Quick Start​

🚀 Interactive Deployment Configurator

Requirements​

Configuration Management​

Standard Directory Structure​

Minimal Example Configuration​

Configuration Mounting Strategies​

1️⃣ Local Volume Mount (Docker, VPS, K8s)​

2️⃣ Kubernetes ConfigMap (K8s, IONOS, STACKIT)​

3️⃣ Cloud Storage Mount (Cloud Run, Lambda, Azure)​

4️⃣ Baked-In Configuration (Custom Image)​

Configuration Update Strategies​

Configuration Validation​

Environment Variables​

Enterprise Cloud Platforms​

Google Cloud Run​

AWS App Runner​

AWS Lambda​

Azure Container Apps​

European Cloud Providers​

IONOS Cloud​

STACKIT​

Kubernetes​

Generic Kubernetes Deployment​

Ingress Configuration​

Indie Hacker Platforms​

Fly.io​

Railway​

Render​

DigitalOcean App Platform​

Cost-Effective VPS​

Hetzner Cloud​

Self-Hosted​

Systemd Service (Linux Binary)​

Production Checklist​

Security​

Monitoring​

Performance​

Backup & Recovery​

High Availability​

Troubleshooting​

Port Already in Use​

Permission Denied (Docker)​

Cache Not Persisting​

Memory Issues​

Configuration Not Found​

SQL Templates Not Loading​

Invalid YAML Syntax​

Connection Refused / Database Unreachable​

ConfigMap Size Limit Exceeded​

Read-Only Filesystem Errors​

Environment Variable Not Working​

Cloud Storage Mount Failing​

Startup Crashes / Immediate Exit​

Next Steps​

Quick Start

Requirements

Configuration Management

Standard Directory Structure

Minimal Example Configuration

Configuration Mounting Strategies

1️⃣ Local Volume Mount (Docker, VPS, K8s)

2️⃣ Kubernetes ConfigMap (K8s, IONOS, STACKIT)

3️⃣ Cloud Storage Mount (Cloud Run, Lambda, Azure)

4️⃣ Baked-In Configuration (Custom Image)

Configuration Update Strategies

Configuration Validation

Environment Variables

Enterprise Cloud Platforms

Google Cloud Run

AWS App Runner

AWS Lambda

Azure Container Apps

European Cloud Providers

IONOS Cloud

STACKIT

Kubernetes

Generic Kubernetes Deployment

Ingress Configuration

Indie Hacker Platforms

Fly.io

Railway

Render

DigitalOcean App Platform

Cost-Effective VPS

Hetzner Cloud

Self-Hosted

Systemd Service (Linux Binary)

Production Checklist

Security

Monitoring

Performance

Backup & Recovery

High Availability

Troubleshooting

Port Already in Use

Permission Denied (Docker)

Cache Not Persisting

Memory Issues

Configuration Not Found

SQL Templates Not Loading

Invalid YAML Syntax

Connection Refused / Database Unreachable

ConfigMap Size Limit Exceeded

Read-Only Filesystem Errors

Environment Variable Not Working

Cloud Storage Mount Failing

Startup Crashes / Immediate Exit

Next Steps