API Gateway Patterns

A comprehensive skill for implementing production-grade API gateways using Kong and industry best practices. This skill covers advanced routing, authentication, rate limiting, load balancing, traffic management, and observability patterns for microservices architectures.

When to Use This Skill

Use this skill when:

Implementing an API gateway for microservices architectures
Managing traffic routing, load balancing, and service discovery
Implementing authentication and authorization at the gateway level
Enforcing rate limiting, quotas, and traffic policies
Adding observability, logging, and monitoring to API traffic
Implementing request/response transformation and caching
Managing API versioning and deprecation strategies
Setting up circuit breakers and resilience patterns
Configuring multi-environment API deployments
Implementing API security policies (CORS, CSRF, WAF)
Building developer portals and API documentation
Managing API lifecycle from development to production

Core Concepts

API Gateway Architecture

An API gateway acts as a single entry point for client applications, routing requests to appropriate backend services while providing cross-cutting concerns:

Reverse Proxy: Routes client requests to backend services
API Composition: Aggregates multiple service calls into single responses
Protocol Translation: Converts between protocols (HTTP, gRPC, WebSocket)
Cross-Cutting Concerns: Authentication, logging, rate limiting, caching
Traffic Management: Load balancing, circuit breaking, retries
Security: SSL termination, API key validation, OAuth2 flows

Key Gateway Components

Services: Upstream APIs that the gateway proxies to
Routes: Request matching rules that determine service routing
Upstreams: Load balancer configurations for service instances
Plugins: Extensible middleware for features (auth, logging, etc.)
Consumers: API clients with authentication credentials
Certificates: SSL/TLS certificates for secure communication
SNIs: Server Name Indication for multi-domain SSL

Kong Gateway Fundamentals

Kong is a cloud-native, platform-agnostic, scalable API gateway:

Architecture:

Control Plane: Admin API for configuration management
Data Plane: Proxy layer handling runtime traffic
Database: PostgreSQL or Cassandra for config storage (or DB-less mode)
Plugin System: Lua-based extensibility for custom logic

Core Entities:

Service (upstream API)
  └── Routes (request matching)
       └── Plugins (features/policies)

Upstream (load balancer)
  └── Targets (service instances)

Consumer (API client)
  └── Credentials (auth keys/tokens)
       └── Plugins (consumer-specific policies)

Routing Patterns

Pattern 1: Path-Based Routing

Route requests based on URL paths to different backend services.

Use Case: Microservices with distinct URL prefixes (e.g., /users, /orders, /products)

Configuration:

yaml

# Users Service
service:
  name: users-service
  url: http://users-api:8001

routes:
  - name: users-route
    paths:
      - /users
      - /api/users
    strip_path: true
    methods:
      - GET
      - POST
      - PUT
      - DELETE

# Orders Service
service:
  name: orders-service
  url: http://orders-api:8002

routes:
  - name: orders-route
    paths:
      - /orders
      - /api/orders
    strip_path: true

Key Options:

```
strip_path: true
```
- Removes matched path before proxying (e.g., /users/123 → /123)
```
strip_path: false
```
- Preserves full path (e.g., /users/123 → /users/123)
```
preserve_host: true
```
- Forwards original Host header to upstream

Pattern 2: Header-Based Routing

Route based on HTTP headers for A/B testing, canary deployments, or API versioning.

Use Case: Gradual rollout of new API versions or feature flags

Configuration:

yaml

# V1 Service (stable)
service:
  name: api-v1
  url: http://api-v1:8001

routes:
  - name: api-v1-route
    paths:
      - /api
    headers:
      X-API-Version:
        - "1"
        - "1.0"

# V2 Service (beta)
service:
  name: api-v2
  url: http://api-v2:8002

routes:
  - name: api-v2-route
    paths:
      - /api
    headers:
      X-API-Version:
        - "2"
        - "2.0"

# Default route (no version header)
routes:
  - name: api-default
    paths:
      - /api
    # Routes to V1 by default

Advanced Header Routing:

yaml

# Mobile vs Web routing
routes:
  - name: mobile-api
    headers:
      User-Agent:
        - ".*Mobile.*"
        - ".*Android.*"
        - ".*iOS.*"
    service: mobile-optimized-api

  - name: web-api
    headers:
      User-Agent:
        - ".*Chrome.*"
        - ".*Firefox.*"
        - ".*Safari.*"
    service: web-api

Pattern 3: Method-Based Routing

Route different HTTP methods to specialized services.

Use Case: CQRS pattern - separate read and write services

Configuration:

yaml

# Read Service (queries)
service:
  name: query-service
  url: http://read-api:8001

routes:
  - name: read-operations
    paths:
      - /api/resources
    methods:
      - GET
      - HEAD
      - OPTIONS

# Write Service (commands)
service:
  name: command-service
  url: http://write-api:8002

routes:
  - name: write-operations
    paths:
      - /api/resources
    methods:
      - POST
      - PUT
      - PATCH
      - DELETE

Pattern 4: Host-Based Routing

Route based on the requested hostname for multi-tenant applications.

Use Case: Different subdomains for different customers or environments

Configuration:

yaml

# Tenant A
service:
  name: tenant-a-api
  url: http://tenant-a:8001

routes:
  - name: tenant-a-route
    hosts:
      - tenant-a.api.example.com
      - a.api.example.com

# Tenant B
service:
  name: tenant-b-api
  url: http://tenant-b:8002

routes:
  - name: tenant-b-route
    hosts:
      - tenant-b.api.example.com
      - b.api.example.com

# Wildcard for dynamic tenants
routes:
  - name: dynamic-tenant
    hosts:
      - "*.api.example.com"
    service: multi-tenant-api

Pattern 5: Weighted Routing (Canary Deployments)

Gradually shift traffic between service versions.

Implementation:

yaml

# Create two upstreams with weight distribution
upstream:
  name: api-upstream
  algorithm: round-robin

targets:
  - target: api-v1:8001
    weight: 90  # 90% traffic to stable version

  - target: api-v2:8002
    weight: 10  # 10% traffic to canary version

service:
  name: api-service
  host: api-upstream  # Points to upstream

routes:
  - name: api-route
    paths:
      - /api

Gradual Rollout Strategy:

Start: 100% v1, 0% v2
Phase 1: 90% v1, 10% v2 (monitor metrics)
Phase 2: 75% v1, 25% v2
Phase 3: 50% v1, 50% v2
Phase 4: 25% v1, 75% v2
Complete: 0% v1, 100% v2

Rate Limiting Patterns

Pattern 1: Global Rate Limiting

Protect your entire API from abuse with global limits.

Use Case: Prevent DDoS attacks and ensure fair usage

Configuration:

yaml

plugins:
  - name: rate-limiting
    config:
      minute: 1000
      hour: 10000
      day: 100000
      policy: local  # or 'cluster', 'redis'
      fault_tolerant: true
      hide_client_headers: false
      limit_by: ip  # or 'consumer', 'credential', 'service'

Policy Options:

```
local
```
: In-memory, single node (not cluster-safe)
```
cluster
```
: Shared across Kong nodes via database
```
redis
```
: High-performance distributed limiting via Redis

Pattern 2: Consumer-Specific Rate Limiting

Different limits for different API consumers (tiers).

Use Case: Freemium model with tiered pricing

Configuration:

yaml

# Free tier consumer
consumer:
  username: free-user-123

plugins:
  - name: rate-limiting
    consumer: free-user-123
    config:
      minute: 10
      hour: 100
      day: 1000

# Premium tier consumer
consumer:
  username: premium-user-456

plugins:
  - name: rate-limiting
    consumer: premium-user-456
    config:
      minute: 1000
      hour: 10000
      day: 100000

# Enterprise tier (unlimited)
consumer:
  username: enterprise-user-789
# No rate limiting plugin for enterprise

Pattern 3: Endpoint-Specific Rate Limiting

Different limits for different API endpoints.

Use Case: Protect expensive operations while allowing higher rates for cheap ones

Configuration:

yaml

# Expensive search endpoint - strict limits
routes:
  - name: search-route
    paths:
      - /api/search

plugins:
  - name: rate-limiting
    route: search-route
    config:
      minute: 10
      hour: 100

# Regular CRUD endpoints - moderate limits
routes:
  - name: users-route
    paths:
      - /api/users

plugins:
  - name: rate-limiting
    route: users-route
    config:
      minute: 100
      hour: 1000

# Health check - no limits
routes:
  - name: health-route
    paths:
      - /health
# No rate limiting plugin

Pattern 4: Sliding Window Rate Limiting

More accurate rate limiting using sliding windows.

Use Case: Prevent burst attacks that exploit fixed window boundaries

Configuration:

yaml

plugins:
  - name: rate-limiting-advanced  # Kong Enterprise
    config:
      limit:
        - 100  # Limit value
      window_size:
        - 60  # Window in seconds
      window_type: sliding
      retry_after_jitter_max: 1
      sync_rate: 0.5
      namespace: my-api
      strategy: redis
      redis:
        host: redis
        port: 6379
        database: 0

Sliding vs Fixed Windows:

Fixed: 100 requests per minute resets at :00 seconds
Sliding: 100 requests in any 60-second window
Sliding prevents burst exploitation at window boundaries

Pattern 5: Quota Management

Long-term usage quotas (monthly, yearly).

Use Case: Enforce subscription limits based on plan

Configuration:

yaml

plugins:
  - name: request-termination
    enabled: false  # Will be enabled when quota exceeded

plugins:
  - name: acme  # Custom quota tracking plugin
    config:
      quota:
        month: 1000000
      reset_on: first_day
      consumer_groups:
        - name: starter
          quota: 10000
        - name: professional
          quota: 100000
        - name: enterprise
          quota: 1000000

Authentication Patterns

Pattern 1: API Key Authentication

Simple API key validation for basic security.

Use Case: Internal APIs, development environments, simple integrations

Configuration:

yaml

# Enable key-auth plugin
plugins:
  - name: key-auth
    config:
      key_names:
        - apikey
        - api-key
        - X-API-Key
      hide_credentials: true
      anonymous: null  # Require authentication
      run_on_preflight: false

# Create consumer with API key
consumers:
  - username: mobile-app
    custom_id: app-001

# Add key credential
keyauth_credentials:
  - consumer: mobile-app
    key: sk_live_abc123def456ghi789

Usage:

bash

curl -H "apikey: sk_live_abc123def456ghi789" \
  https://api.example.com/users

Best Practices:

Use cryptographically random keys (min 32 chars)
Rotate keys periodically
Different keys for different environments
Never commit keys to version control
Use HTTPS to protect keys in transit

Pattern 2: JWT Authentication

Token-based authentication with payload verification.

Use Case: Modern SPAs, mobile apps, microservices

Configuration:

yaml

plugins:
  - name: jwt
    config:
      uri_param_names:
        - jwt
      cookie_names:
        - jwt_token
      header_names:
        - Authorization
      claims_to_verify:
        - exp
        - nbf
      key_claim_name: iss
      secret_is_base64: false
      anonymous: null
      run_on_preflight: false
      maximum_expiration: 3600  # 1 hour max

# Create consumer with JWT credential
consumers:
  - username: web-app

jwt_secrets:
  - consumer: web-app
    key: myapp-issuer
    algorithm: HS256
    secret: my-secret-key-change-in-production

RS256 (Asymmetric) Configuration:

yaml

jwt_secrets:
  - consumer: mobile-app
    key: mobile-issuer
    algorithm: RS256
    rsa_public_key: |
      -----BEGIN PUBLIC KEY-----
      MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA...
      -----END PUBLIC KEY-----

Token Format:

Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJteWFwcC1pc3N1ZXIiLCJzdWIiOiJ1c2VyMTIzIiwiZXhwIjoxNjQwOTk1MjAwfQ.signature

Pattern 3: OAuth 2.0 Authorization

Full OAuth 2.0 flows for third-party integrations.

Use Case: Public APIs, third-party developer access

Supported Flows:

Authorization Code Flow
Client Credentials Flow
Implicit Flow (deprecated)
Resource Owner Password Flow

Configuration:

yaml

plugins:
  - name: oauth2
    config:
      scopes:
        - read
        - write
        - admin
      mandatory_scope: true
      token_expiration: 3600
      enable_authorization_code: true
      enable_client_credentials: true
      enable_implicit_grant: false
      enable_password_grant: false
      hide_credentials: true
      accept_http_if_already_terminated: false
      refresh_token_ttl: 1209600  # 14 days

# Create OAuth application
oauth2_credentials:
  - consumer: third-party-app
    name: "Partner Integration"
    client_id: client_abc123
    client_secret: secret_xyz789
    redirect_uris:
      - https://partner.com/callback

Authorization Code Flow:

bash

# 1. Get authorization code
GET /oauth2/authorize?
  response_type=code&
  client_id=client_abc123&
  redirect_uri=https://partner.com/callback&
  scope=read write

# 2. Exchange code for token
POST /oauth2/token
  grant_type=authorization_code&
  client_id=client_abc123&
  client_secret=secret_xyz789&
  code=AUTH_CODE&
  redirect_uri=https://partner.com/callback

Pattern 4: OpenID Connect (OIDC)

Enterprise SSO integration with identity providers.

Use Case: Enterprise authentication with Google, Okta, Auth0, Azure AD

Configuration:

yaml

plugins:
  - name: openid-connect
    config:
      issuer: https://accounts.google.com
      client_id: your-client-id.apps.googleusercontent.com
      client_secret: your-client-secret
      redirect_uri:
        - https://api.example.com/callback
      scopes:
        - openid
        - email
        - profile
      auth_methods:
        - authorization_code
      login_redirect_uri: https://app.example.com/login
      logout_redirect_uri: https://app.example.com/logout
      ssl_verify: true
      session_secret: change-this-secret-in-production
      discovery: https://accounts.google.com/.well-known/openid-configuration

Multi-Provider Configuration:

yaml

# Google OIDC
plugins:
  - name: openid-connect
    route: google-login
    config:
      issuer: https://accounts.google.com
      client_id: google-client-id
      client_secret: google-secret

# Azure AD OIDC
plugins:
  - name: openid-connect
    route: azure-login
    config:
      issuer: https://login.microsoftonline.com/tenant-id/v2.0
      client_id: azure-client-id
      client_secret: azure-secret

# Okta OIDC
plugins:
  - name: openid-connect
    route: okta-login
    config:
      issuer: https://dev-123456.okta.com
      client_id: okta-client-id
      client_secret: okta-secret

Pattern 5: mTLS (Mutual TLS) Authentication

Certificate-based authentication for service-to-service security.

Use Case: Microservices mutual authentication, B2B integrations

Configuration:

yaml

# Enable mTLS plugin
plugins:
  - name: mtls-auth
    config:
      ca_certificates:
        - ca-cert-id-1
        - ca-cert-id-2
      skip_consumer_lookup: false
      anonymous: null
      revocation_check_mode: SKIP  # or IGNORE_CA_ERROR, STRICT

# Upload CA certificate
ca_certificates:
  - cert: |
      -----BEGIN CERTIFICATE-----
      MIIDXTCCAkWgAwIBAgIJAKL...
      -----END CERTIFICATE-----

# Create consumer mapped to client certificate
consumers:
  - username: service-a
    custom_id: service-a-001

# Map certificate to consumer
mtls_auth_credentials:
  - consumer: service-a
    subject_name: CN=service-a,O=MyOrg

Load Balancing Patterns

Pattern 1: Round-Robin Load Balancing

Distribute requests evenly across service instances.

Use Case: Stateless services with uniform capacity

Configuration:

yaml

upstreams:
  - name: api-upstream
    algorithm: round-robin
    slots: 10000
    healthchecks:
      active:
        type: http
        http_path: /health
        healthy:
          interval: 5
          successes: 2
        unhealthy:
          interval: 5
          http_failures: 3
          timeouts: 3
      passive:
        healthy:
          successes: 5
        unhealthy:
          http_failures: 5
          timeouts: 2

targets:
  - upstream: api-upstream
    target: api-1.internal:8001
    weight: 100

  - upstream: api-upstream
    target: api-2.internal:8001
    weight: 100

  - upstream: api-upstream
    target: api-3.internal:8001
    weight: 100

Pattern 2: Weighted Load Balancing

Distribute traffic proportionally based on server capacity.

Use Case: Heterogeneous servers with different capacities

Configuration:

yaml

upstreams:
  - name: api-upstream
    algorithm: round-robin

targets:
  # Powerful server - 50% traffic
  - target: api-1.internal:8001
    weight: 500

  # Medium server - 30% traffic
  - target: api-2.internal:8001
    weight: 300

  # Small server - 20% traffic
  - target: api-3.internal:8001
    weight: 200

Weight Distribution:

Total weight: 500 + 300 + 200 = 1000
api-1: 500/1000 = 50% of requests
api-2: 300/1000 = 30% of requests
api-3: 200/1000 = 20% of requests

Pattern 3: Consistent Hashing

Route requests from same client to same backend (session affinity).

Use Case: Stateful services requiring session persistence

Configuration:

yaml

upstreams:
  - name: api-upstream
    algorithm: consistent-hashing
    hash_on: header
    hash_on_header: X-User-ID
    hash_fallback: ip
    hash_fallback_header: X-Forwarded-For

targets:
  - target: api-1.internal:8001
  - target: api-2.internal:8001
  - target: api-3.internal:8001

Hashing Options:

```
hash_on: none
```
- Random distribution
```
hash_on: consumer
```
- Hash by authenticated consumer
```
hash_on: ip
```
- Hash by client IP
```
hash_on: header
```
- Hash by specified header value
```
hash_on: cookie
```
- Hash by cookie value
```
hash_on: path
```
- Hash by request path

Use Cases by Hash Type:

User sessions:
```
hash_on: header
```
(X-User-ID)
Geographic routing:
```
hash_on: ip
```
Tenant isolation:
```
hash_on: header
```
(X-Tenant-ID)
Shopping carts:
```
hash_on: cookie
```
(session_id)

Pattern 4: Least Connections

Route to server with fewest active connections.

Use Case: Long-lived connections (WebSockets, streaming)

Configuration:

yaml

upstreams:
  - name: websocket-upstream
    algorithm: least-connections

targets:
  - target: ws-1.internal:8001
  - target: ws-2.internal:8001
  - target: ws-3.internal:8001

When to Use:

WebSocket servers
Long-polling endpoints
Streaming APIs (SSE, gRPC streaming)
Services with variable request duration

Pattern 5: Active Health Checks

Automatically remove unhealthy targets from rotation.

Use Case: High availability with automatic failover

Configuration:

yaml

upstreams:
  - name: api-upstream
    healthchecks:
      active:
        type: http
        http_path: /health
        https_verify_certificate: true
        concurrency: 10
        timeout: 1
        headers:
          X-Health-Check:
            - gateway
        healthy:
          interval: 5  # Check every 5 seconds
          http_statuses:
            - 200
            - 302
          successes: 2  # 2 successes → healthy
        unhealthy:
          interval: 5
          http_statuses:
            - 429
            - 500
            - 503
          http_failures: 3  # 3 failures → unhealthy
          tcp_failures: 3
          timeouts: 3

      passive:
        type: http
        healthy:
          http_statuses:
            - 200
            - 201
            - 202
            - 203
            - 204
            - 205
            - 206
            - 207
            - 208
            - 226
            - 300
            - 301
            - 302
          successes: 5
        unhealthy:
          http_statuses:
            - 429
            - 500
            - 503
          http_failures: 5
          tcp_failures: 2
          timeouts: 2

Traffic Control Patterns

Pattern 1: Circuit Breaker

Prevent cascading failures by failing fast when downstream is unhealthy.

Use Case: Protect your system when dependencies fail

Configuration:

yaml

plugins:
  - name: proxy-cache-advanced  # Kong Enterprise
    config:
      # Serve stale cache during outages
      cache_control: false

plugins:
  - name: request-termination
    enabled: false  # Enabled programmatically on circuit open

# Custom circuit breaker (via passive health checks)
upstreams:
  - name: api-upstream
    healthchecks:
      passive:
        unhealthy:
          http_failures: 5  # Open circuit after 5 failures
          timeouts: 3
        healthy:
          successes: 3  # Close circuit after 3 successes

Circuit States:

Closed: Normal operation, requests flow through
Open: Failures detected, requests fail immediately
Half-Open: Test if service recovered, allow limited requests

Pattern 2: Request Timeout

Prevent slow requests from tying up resources.

Use Case: Prevent resource exhaustion from slow backends

Configuration:

yaml

services:
  - name: api-service
    url: http://api.internal:8001
    read_timeout: 5000    # 5 seconds
    write_timeout: 5000   # 5 seconds
    connect_timeout: 2000 # 2 seconds

plugins:
  - name: request-timeout  # Additional timeout enforcement
    config:
      http_timeout: 5000
      stream_timeout: 30000

Timeout Strategy:

connect_timeout: 2s   → Connection establishment
write_timeout: 5s     → Writing request to upstream
read_timeout: 5s      → Reading response from upstream
http_timeout: 5s      → Overall HTTP transaction

Pattern 3: Retry Logic

Automatically retry failed requests with exponential backoff.

Use Case: Handle transient failures in distributed systems

Configuration:

yaml

services:
  - name: api-service
    retries: 5  # Maximum retry attempts

plugins:
  - name: proxy-retry  # Custom retry plugin
    config:
      retries: 3
      retry_on:
        - 500
        - 502
        - 503
        - 504
      backoff:
        type: exponential
        base: 2
        max: 30
      jitter: 0.5

Retry Schedule:

Attempt 1: Immediate
Attempt 2: 2s + jitter
Attempt 3: 4s + jitter
Attempt 4: 8s + jitter
Attempt 5: 16s + jitter

Idempotency Considerations:

Retry GET, HEAD, PUT, DELETE (idempotent)
DO NOT retry POST unless idempotency keys used
Check for Idempotency-Key header

Pattern 4: Request Size Limiting

Prevent large payload attacks and memory exhaustion.

Use Case: Protect against oversized request bodies

Configuration:

yaml

plugins:
  - name: request-size-limiting
    config:
      allowed_payload_size: 10  # Megabytes
      size_unit: megabytes
      require_content_length: true

# Different limits per route
plugins:
  - name: request-size-limiting
    route: file-upload
    config:
      allowed_payload_size: 100  # Allow larger files

  - name: request-size-limiting
    route: api-endpoints
    config:
      allowed_payload_size: 1  # Strict limit for APIs

Pattern 5: Traffic Shaping (Throttling)

Control request rate beyond simple rate limiting.

Use Case: Smooth traffic spikes, prevent backend overload

Configuration:

yaml

plugins:
  - name: request-transformer-advanced
    config:
      # Add delay headers for client-side throttling
      add:
        headers:
          - "Retry-After:60"

plugins:
  - name: proxy-cache-advanced
    config:
      # Cache responses to reduce backend load
      cache_ttl: 300
      strategy: memory

# Upstream connection limits
upstreams:
  - name: api-upstream
    slots: 1000  # Limit concurrent connections

Request/Response Transformation

Pattern 1: Request Header Manipulation

Add, modify, or remove request headers before proxying.

Use Case: Add authentication, tracing, or context headers

Configuration:

yaml

plugins:
  - name: request-transformer
    config:
      add:
        headers:
          - "X-Gateway:kong"
          - "X-Request-ID:$(uuid)"
          - "X-Forwarded-Proto:https"
      append:
        headers:
          - "X-Trace-Id:$(uuid)"
      replace:
        headers:
          - "User-Agent:Kong-Gateway/3.0"
      remove:
        headers:
          - "X-Internal-Secret"

Advanced Transformations:

yaml

plugins:
  - name: request-transformer-advanced
    config:
      add:
        headers:
          - "X-Consumer-Username:$(consumer_username)"
          - "X-Consumer-ID:$(consumer_id)"
          - "X-Authenticated-Scope:$(authenticated_credential.scope)"
          - "X-Client-IP:$(remote_addr)"
      rename:
        headers:
          - "Authorization:X-Original-Auth"

Pattern 2: Response Header Manipulation

Modify response headers before returning to client.

Use Case: Add security headers, CORS, caching directives

Configuration:

yaml

plugins:
  - name: response-transformer
    config:
      add:
        headers:
          - "X-Gateway-Response-Time:$(latencies.request)"
          - "X-Server-ID:$(upstream_addr)"
      remove:
        headers:
          - "X-Powered-By"
          - "Server"

# Security headers
plugins:
  - name: response-transformer
    config:
      add:
        headers:
          - "Strict-Transport-Security:max-age=31536000; includeSubDomains"
          - "X-Content-Type-Options:nosniff"
          - "X-Frame-Options:DENY"
          - "X-XSS-Protection:1; mode=block"
          - "Content-Security-Policy:default-src 'self'"

Pattern 3: Request Body Transformation

Modify request payloads before forwarding.

Use Case: Add fields, transform formats, sanitize input

Configuration:

yaml

plugins:
  - name: request-transformer-advanced
    config:
      add:
        body:
          - "gateway_timestamp:$(timestamp)"
          - "request_id:$(uuid)"
      remove:
        body:
          - "internal_field"
      replace:
        body:
          - "api_version:v2"

Pattern 4: GraphQL to REST Translation

Expose REST APIs as GraphQL endpoints.

Use Case: Modernize legacy REST APIs with GraphQL

Configuration:

yaml

plugins:
  - name: graphql-proxy-cache-advanced
    config:
      strategy: memory

# Define GraphQL schema mapping
graphql_schemas:
  - name: users-graphql
    schema: |
      type Query {
        user(id: ID!): User
        users: [User]
      }

      type User {
        id: ID!
        name: String!
        email: String!
      }
    resolvers:
      Query:
        user: http://users-api/users/{id}
        users: http://users-api/users

Pattern 5: Protocol Translation

Convert between HTTP, gRPC, and WebSocket protocols.

Use Case: Expose gRPC services via HTTP/JSON

Configuration:

yaml

# gRPC to HTTP/JSON
plugins:
  - name: grpc-gateway
    config:
      proto: /path/to/service.proto

services:
  - name: grpc-service
    url: grpc://grpc.internal:9000
    protocol: grpc

routes:
  - name: grpc-http-route
    paths:
      - /v1/users
    protocols:
      - http
      - https

Caching Patterns

Pattern 1: Response Caching

Cache upstream responses to reduce backend load.

Use Case: Cache expensive queries, reduce database load

Configuration:

yaml

plugins:
  - name: proxy-cache
    config:
      strategy: memory  # or 'redis'
      content_type:
        - "application/json"
        - "text/html"
      cache_ttl: 300  # 5 minutes
      cache_control: false  # Ignore client cache headers
      storage_ttl: 600  # Backend storage TTL
      memory:
        dictionary_name: kong_cache
      vary_headers:
        - "Accept-Language"
        - "X-User-Tier"

Redis-Based Caching:

yaml

plugins:
  - name: proxy-cache-advanced
    config:
      strategy: redis
      cache_ttl: 3600
      redis:
        host: redis.internal
        port: 6379
        database: 0
        password: redis-password
        timeout: 2000
        sentinel_master: mymaster
        sentinel_addresses:
          - redis-sentinel-1:26379
          - redis-sentinel-2:26379

Pattern 2: Conditional Caching

Cache based on status codes, headers, or request criteria.

Use Case: Cache only successful responses, skip errors

Configuration:

yaml

plugins:
  - name: proxy-cache-advanced
    config:
      response_code:
        - 200
        - 301
        - 302
      request_method:
        - GET
        - HEAD
      vary_headers:
        - "Accept"
        - "Accept-Encoding"
      vary_query_params:
        - "page"
        - "limit"
      ignore_uri_case: true

Pattern 3: Cache Invalidation

Purge cache on-demand or based on events.

Use Case: Update cache when data changes

Configuration:

yaml

# Admin API cache purge
POST /cache/purge

# Purge specific endpoint
POST /cache/purge/users

# TTL-based expiration
plugins:
  - name: proxy-cache
    config:
      cache_ttl: 60  # Short TTL for frequently updated data

# Event-based invalidation (custom plugin)
plugins:
  - name: custom-cache-invalidator
    config:
      invalidate_on:
        - POST
        - PUT
        - PATCH
        - DELETE
      propagate: true  # Clear related caches

Pattern 4: Multi-Tier Caching

Layer caching at gateway and backend.

Use Case: Maximize cache hit rate across layers

Architecture:

Client
  ↓
Kong Gateway Cache (L1)
  ↓
Backend API Cache (L2)
  ↓
Database

Configuration:

yaml

# Gateway cache (L1)
plugins:
  - name: proxy-cache
    config:
      strategy: memory
      cache_ttl: 60  # 1 minute

# Backend passes Cache-Control headers
# Gateway respects them if cache_control: true
plugins:
  - name: proxy-cache
    config:
      cache_control: true  # Respect upstream Cache-Control
      vary_headers:
        - "Cache-Control"

Pattern 5: Surrogate-Key Based Invalidation

Tag caches for granular invalidation.

Use Case: Invalidate related resources efficiently

Configuration:

yaml

# Tag responses with surrogate keys
plugins:
  - name: response-transformer
    config:
      add:
        headers:
          - "Surrogate-Key:user-$(user_id) tenant-$(tenant_id)"

# Invalidate by surrogate key
# Custom plugin or Varnish integration
POST /cache/purge
Headers:
  Surrogate-Key: user-123

Security Patterns

Pattern 1: CORS (Cross-Origin Resource Sharing)

Enable controlled cross-origin requests.

Use Case: Web apps calling APIs from different domains

Configuration:

yaml

plugins:
  - name: cors
    config:
      origins:
        - "https://app.example.com"
        - "https://admin.example.com"
      methods:
        - GET
        - POST
        - PUT
        - PATCH
        - DELETE
        - OPTIONS
      headers:
        - Accept
        - Authorization
        - Content-Type
        - X-Request-ID
      exposed_headers:
        - X-Total-Count
        - X-Page-Number
      credentials: true
      max_age: 3600
      preflight_continue: false

Wildcard CORS (Development Only):

yaml

plugins:
  - name: cors
    config:
      origins:
        - "*"
      methods:
        - "*"
      headers:
        - "*"
      credentials: false  # Must be false with wildcard origins

Pattern 2: IP Restriction

Allow or deny based on IP addresses.

Use Case: Restrict admin APIs to office IPs

Configuration:

yaml

# Whitelist approach
plugins:
  - name: ip-restriction
    config:
      allow:
        - 10.0.0.0/8
        - 192.168.1.100
        - 203.0.113.0/24

# Blacklist approach
plugins:
  - name: ip-restriction
    config:
      deny:
        - 1.2.3.4
        - 5.6.7.0/24

Combined with Authentication:

yaml

# Admin route: IP + Auth
plugins:
  - name: ip-restriction
    route: admin-api
    config:
      allow:
        - 10.0.0.0/8

  - name: key-auth
    route: admin-api

Pattern 3: Bot Detection

Detect and block malicious bots.

Use Case: Prevent scraping, brute force, spam

Configuration:

yaml

plugins:
  - name: bot-detection
    config:
      allow:
        - "googlebot"
        - "bingbot"
        - "slackbot"
      deny:
        - "curl"
        - "wget"
        - "scrapy"
      blacklist_cache_size: 10000
      whitelist_cache_size: 10000

Pattern 4: Request Validation

Validate requests against schemas.

Use Case: Ensure API contract compliance, prevent injection

Configuration:

yaml

plugins:
  - name: request-validator
    config:
      body_schema: |
        {
          "type": "object",
          "properties": {
            "username": {
              "type": "string",
              "minLength": 3,
              "maxLength": 50
            },
            "email": {
              "type": "string",
              "format": "email"
            },
            "age": {
              "type": "integer",
              "minimum": 18,
              "maximum": 120
            }
          },
          "required": ["username", "email"]
        }
      parameter_schema:
        - name: page
          in: query
          required: false
          schema:
            type: integer
            minimum: 1

Pattern 5: WAF (Web Application Firewall)

Protect against OWASP Top 10 vulnerabilities.

Use Case: Block SQL injection, XSS, path traversal

Configuration:

yaml

plugins:
  - name: waf  # Kong Enterprise or ModSecurity plugin
    config:
      rule_sets:
        - owasp_crs
      anomaly_threshold: 5
      paranoia_level: 1
      blocked_status_code: 403

Observability Patterns

Pattern 1: Request Logging

Log all API requests for audit and debugging.

Use Case: Compliance, debugging, analytics

Configuration:

yaml

plugins:
  - name: file-log
    config:
      path: /var/log/kong/requests.log
      reopen: true

# JSON structured logging
plugins:
  - name: http-log
    config:
      http_endpoint: http://logstash:5000
      method: POST
      content_type: application/json
      timeout: 5000
      keepalive: 60000
      custom_fields_by_lua:
        request_id: "return kong.request.get_header('X-Request-ID')"

Log to Multiple Destinations:

yaml

# Elasticsearch
plugins:
  - name: http-log
    config:
      http_endpoint: http://elasticsearch:9200/_bulk

# Splunk
plugins:
  - name: http-log
    config:
      http_endpoint: https://splunk:8088/services/collector
      headers:
        Authorization: "Splunk token"

# Datadog
plugins:
  - name: datadog
    config:
      host: datadog-agent
      port: 8125

Pattern 2: Distributed Tracing

Track requests across microservices.

Use Case: Diagnose latency, understand request flow

Configuration:

yaml

# Zipkin
plugins:
  - name: zipkin
    config:
      http_endpoint: http://zipkin:9411/api/v2/spans
      sample_ratio: 0.1  # Trace 10% of requests
      include_credential: true
      traceid_byte_count: 16
      header_type: preserve  # or 'jaeger', 'b3', 'w3c'

# Jaeger
plugins:
  - name: opentelemetry
    config:
      endpoint: http://jaeger:14268/api/traces
      resource_attributes:
        service.name: api-gateway
        service.version: 1.0.0
      batch_span_processor:
        max_queue_size: 2048
        batch_timeout: 5000

W3C Trace Context:

yaml

plugins:
  - name: opentelemetry
    config:
      propagation:
        default: w3c
      headers:
        - traceparent
        - tracestate

Pattern 3: Metrics Collection

Expose Prometheus metrics for monitoring.

Use Case: Monitor gateway performance, errors, latency

Configuration:

yaml

plugins:
  - name: prometheus
    config:
      per_consumer: true
      status_code_metrics: true
      latency_metrics: true
      bandwidth_metrics: true
      upstream_health_metrics: true

# Expose /metrics endpoint
routes:
  - name: metrics
    paths:
      - /metrics
    service: prometheus-service

Available Metrics:

# Requests
kong_http_requests_total{service,route,code}

# Latency
kong_latency_ms{type,service,route}
kong_request_latency_ms{service,route}
kong_upstream_latency_ms{service,route}

# Bandwidth
kong_bandwidth_bytes{type,service,route}

# Connections
kong_datastore_reachable
kong_nginx_connections_total{state}

Pattern 4: Health Checks

Expose health check endpoints.

Use Case: Kubernetes liveness/readiness probes

Configuration:

yaml

# Gateway health
routes:
  - name: health
    paths:
      - /health
    plugins:
      - name: request-termination
        config:
          status_code: 200
          message: "OK"

# Detailed status
routes:
  - name: status
    paths:
      - /status
    service: kong-status-service

# Upstream health aggregation
plugins:
  - name: upstream-health-check
    config:
      healthy_threshold: 2
      unhealthy_threshold: 3

Pattern 5: Error Tracking

Track and report errors to monitoring systems.

Use Case: Proactive error detection and alerting

Configuration:

yaml

# Sentry integration
plugins:
  - name: sentry
    config:
      dsn: https://key@sentry.io/project
      environment: production
      release: v1.2.3

# Custom error logging
plugins:
  - name: http-log
    config:
      http_endpoint: http://error-tracker:5000
      custom_fields_by_lua:
        error_type: |
          if kong.response.get_status() >= 500 then
            return "server_error"
          elseif kong.response.get_status() >= 400 then
            return "client_error"
          end

Multi-Environment Patterns

Pattern 1: Environment Separation

Separate configurations for dev, staging, production.

Use Case: Consistent deployment across environments

Structure:

config/
  ├── base.yaml          # Shared configuration
  ├── dev.yaml           # Development overrides
  ├── staging.yaml       # Staging overrides
  └── production.yaml    # Production overrides

Configuration:

yaml

# base.yaml
_format_version: "3.0"

services:
  - name: users-api
    url: http://users-service:8001

routes:
  - name: users-route
    service: users-api
    paths:
      - /users

# production.yaml
_format_version: "3.0"

services:
  - name: users-api
    url: https://users-api-prod.internal:8001
    retries: 5
    read_timeout: 5000

plugins:
  - name: rate-limiting
    service: users-api
    config:
      minute: 1000

Pattern 2: Blue-Green Deployments

Zero-downtime deployments with instant rollback.

Use Case: Safe production deployments

Configuration:

yaml

# Blue environment (current production)
upstreams:
  - name: api-blue
    targets:
      - target: api-blue-1:8001
      - target: api-blue-2:8001

# Green environment (new version)
upstreams:
  - name: api-green
    targets:
      - target: api-green-1:8001
      - target: api-green-2:8001

# Route points to active environment
services:
  - name: api-service
    host: api-blue  # Switch to api-green for deployment

# Rollback: Switch service.host back to api-blue

Pattern 3: Canary Releases

Gradual rollout with monitoring.

Use Case: Risk mitigation for new releases

Configuration:

yaml

# Canary routing with header
routes:
  - name: api-canary
    paths:
      - /api
    headers:
      X-Canary:
        - "true"
    service: api-v2

routes:
  - name: api-stable
    paths:
      - /api
    service: api-v1

# Weighted canary (10% traffic)
upstreams:
  - name: api-upstream
    targets:
      - target: api-v1:8001
        weight: 90
      - target: api-v2:8001
        weight: 10

Canary Progression:

Phase 1: 5% canary, monitor errors
Phase 2: 25% canary, check metrics
Phase 3: 50% canary, verify performance
Phase 4: 100% canary, deprecate old version

Pattern 4: Feature Flags

Enable/disable features dynamically.

Use Case: A/B testing, gradual feature rollout

Configuration:

yaml

# Feature flag via header
routes:
  - name: new-feature
    paths:
      - /api/new-feature
    headers:
      X-Feature-Flag:
        - "new-dashboard"
    service: new-feature-service

# Default route (feature disabled)
routes:
  - name: old-feature
    paths:
      - /api/new-feature
    service: old-feature-service

# Consumer-based feature flags
plugins:
  - name: request-transformer
    consumer: beta-users
    config:
      add:
        headers:
          - "X-Feature-Flags:new-dashboard,advanced-search"

Pattern 5: Multi-Region Deployment

Route to nearest region for low latency.

Use Case: Global API with regional failover

Configuration:

yaml

# US region
upstreams:
  - name: api-us
    targets:
      - target: api-us-east:8001
      - target: api-us-west:8001

# EU region
upstreams:
  - name: api-eu
    targets:
      - target: api-eu-west:8001
      - target: api-eu-central:8001

# Geographic routing (via DNS or header)
routes:
  - name: us-traffic
    hosts:
      - us.api.example.com
    service: api-us-service

routes:
  - name: eu-traffic
    hosts:
      - eu.api.example.com
    service: api-eu-service

Best Practices

Architecture Design

Single Responsibility: Gateway handles cross-cutting concerns only
Stateless Design: Keep gateway stateless for horizontal scaling
Declarative Configuration: Use YAML/JSON for version-controlled config
Database-Less Mode: Use DB-less for simpler deployments
Plugin Minimalism: Only enable necessary plugins

Security Best Practices

Defense in Depth: Layer multiple security mechanisms
Least Privilege: Minimal permissions for consumers
Secrets Management: Never hardcode credentials
TLS Everywhere: Encrypt all traffic (client and upstream)
Rate Limiting: Always protect public endpoints
Input Validation: Validate all request data
Regular Updates: Keep Kong and plugins updated

Performance Optimization

Enable Caching: Cache responses aggressively
Connection Pooling: Reuse upstream connections
Load Balancing: Distribute load evenly
Health Checks: Remove unhealthy targets quickly
Timeouts: Set appropriate timeouts to prevent hangs
Monitoring: Track latency, errors, throughput
Resource Limits: Set memory and connection limits

Operational Excellence

Logging: Structured logging for all requests
Monitoring: Comprehensive metrics collection
Alerting: Alert on anomalies and errors
Documentation: Document all routes and plugins
Testing: Test gateway config in staging
Versioning: Version control all configurations
Disaster Recovery: Plan for failover scenarios

Plugin Strategy

Order Matters: Plugins execute in specific order
Scope Appropriately: Global, service, route, or consumer
Test Thoroughly: Test plugin combinations
Monitor Impact: Track plugin performance overhead
Custom Plugins: Write custom plugins for unique needs

Plugin Execution Order:

1. Authentication (key-auth, jwt, oauth2)
2. Security (ip-restriction, bot-detection)
3. Traffic Control (rate-limiting, request-size-limiting)
4. Transformation (request-transformer)
5. Logging (file-log, http-log)
6. Analytics (prometheus, datadog)

Configuration Management

Version Control: Git for all configurations
Environment Parity: Consistent configs across environments
Automated Deployment: CI/CD for configuration changes
Validation: Validate configs before applying
Rollback Plan: Quick rollback on issues
Change Log: Document all configuration changes

Scaling Guidelines

Horizontal Scaling: Add more Kong nodes
Database Scaling: Scale PostgreSQL separately
Cache Offloading: Use Redis for distributed caching
Regional Deployment: Deploy close to users
CDN Integration: Offload static content
Connection Limits: Set per-worker limits

Common Use Cases

Use Case 1: SaaS API Platform

Requirements:

Multi-tenant isolation
Tiered pricing (free, pro, enterprise)
Rate limiting per tier
Analytics per customer
Self-service developer portal

Implementation:

yaml

# Tenant identification
plugins:
  - name: key-auth
    config:
      key_names:
        - X-API-Key

# Tier-based rate limiting
consumers:
  - username: free-tier-customer
    custom_id: customer-123

plugins:
  - name: rate-limiting
    consumer: free-tier-customer
    config:
      minute: 60
      hour: 1000

# Usage analytics
plugins:
  - name: prometheus
    config:
      per_consumer: true

# Request transformation (add tenant context)
plugins:
  - name: request-transformer
    config:
      add:
        headers:
          - "X-Tenant-ID:$(consumer_custom_id)"

Use Case 2: Microservices Gateway

Requirements:

Service discovery
Load balancing
Circuit breaking
Distributed tracing
Centralized authentication

Implementation:

yaml

# Service registry
services:
  - name: users-service
    url: http://users.internal:8001

  - name: orders-service
    url: http://orders.internal:8002

  - name: inventory-service
    url: http://inventory.internal:8003

# Load balancing with health checks
upstreams:
  - name: users-upstream
    healthchecks:
      active:
        http_path: /health
        healthy:
          interval: 5

# Distributed tracing
plugins:
  - name: zipkin
    config:
      http_endpoint: http://zipkin:9411/api/v2/spans

# JWT authentication (single sign-on)
plugins:
  - name: jwt
    config:
      claims_to_verify:
        - exp

Use Case 3: Mobile Backend

Requirements:

Versioned APIs
GraphQL support
Offline caching
Push notifications
Device-based rate limiting

Implementation:

yaml

# API versioning
routes:
  - name: api-v1
    paths:
      - /api/v1
    service: mobile-api-v1

  - name: api-v2
    paths:
      - /api/v2
    service: mobile-api-v2

# GraphQL endpoint
plugins:
  - name: graphql-proxy-cache-advanced
    route: graphql-route

# Aggressive caching for mobile
plugins:
  - name: proxy-cache
    config:
      cache_ttl: 3600
      strategy: redis

# Device-based rate limiting
plugins:
  - name: rate-limiting
    config:
      limit_by: header
      header_name: X-Device-ID
      minute: 100

Use Case 4: Public API

Requirements:

OAuth 2.0
Developer portal
API documentation
Usage analytics
Monetization

Implementation:

yaml

# OAuth 2.0
plugins:
  - name: oauth2
    config:
      scopes:
        - read
        - write
        - admin
      enable_authorization_code: true

# Developer portal
routes:
  - name: developer-docs
    paths:
      - /docs
    service: developer-portal

# Usage tracking
plugins:
  - name: prometheus
    config:
      per_consumer: true

# Billing integration
plugins:
  - name: http-log
    config:
      http_endpoint: http://billing-system:5000

Use Case 5: Legacy Modernization

Requirements:

REST to GraphQL
Protocol translation
Request/response transformation
Gradual migration
Backward compatibility

Implementation:

yaml

# GraphQL facade over REST
plugins:
  - name: graphql-proxy-cache-advanced

# SOAP to REST transformation
plugins:
  - name: request-transformer-advanced
    config:
      # Transform REST to SOAP
      replace:
        headers:
          - "Content-Type:text/xml"

# Version migration (route legacy to new)
upstreams:
  - name: api-upstream
    targets:
      - target: legacy-api:8001
        weight: 20  # 20% legacy
      - target: new-api:8002
        weight: 80  # 80% new

Quick Reference

Essential Commands

bash

# Declarative configuration
deck sync -s kong.yaml

# Database migrations
kong migrations bootstrap
kong migrations up

# Start Kong
kong start

# Reload configuration
kong reload

# Health check
curl http://localhost:8001/status

# List services
curl http://localhost:8001/services

# List routes
curl http://localhost:8001/routes

# List plugins
curl http://localhost:8001/plugins

Configuration Templates

Minimal Service:

yaml

services:
  - name: my-service
    url: http://api.internal:8001

routes:
  - name: my-route
    service: my-service
    paths:
      - /api

Production Service:

yaml

services:
  - name: production-service
    url: http://api.internal:8001
    protocol: http
    retries: 5
    connect_timeout: 5000
    read_timeout: 60000
    write_timeout: 60000

upstreams:
  - name: production-upstream
    algorithm: consistent-hashing
    hash_on: header
    hash_on_header: X-User-ID
    healthchecks:
      active:
        http_path: /health
        healthy:
          interval: 5
          successes: 2
        unhealthy:
          http_failures: 3
          timeouts: 3

targets:
  - upstream: production-upstream
    target: api-1:8001
  - upstream: production-upstream
    target: api-2:8001

routes:
  - name: production-route
    service: production-service
    paths:
      - /api
    protocols:
      - https
    strip_path: true
    preserve_host: false

plugins:
  - name: rate-limiting
    route: production-route
    config:
      minute: 1000
      policy: redis

  - name: jwt
    route: production-route

  - name: cors
    route: production-route

  - name: prometheus
    route: production-route

Resources

Kong Documentation: https://docs.konghq.com/
Kong Gateway: https://konghq.com/kong/
Kong Plugin Hub: https://docs.konghq.com/hub/
Kong Admin API: https://docs.konghq.com/gateway/latest/admin-api/
decK (Declarative Config): https://docs.konghq.com/deck/
Kong Ingress Controller: https://docs.konghq.com/kubernetes-ingress-controller/
Kong Community: https://discuss.konghq.com/

Skill Version: 1.0.0 Last Updated: October 2025 Skill Category: API Gateway, Microservices, Traffic Management Compatible With: Kong Gateway 3.x, Kubernetes, Docker, Cloud Platforms

api-gateway-patterns

NPX Install

Tags

SKILL.md Content

API Gateway Patterns

When to Use This Skill

Core Concepts

API Gateway Architecture

Key Gateway Components

Kong Gateway Fundamentals

Routing Patterns

Pattern 1: Path-Based Routing

Pattern 2: Header-Based Routing

Pattern 3: Method-Based Routing

Pattern 4: Host-Based Routing

Pattern 5: Weighted Routing (Canary Deployments)

Rate Limiting Patterns

Pattern 1: Global Rate Limiting

Pattern 2: Consumer-Specific Rate Limiting

Pattern 3: Endpoint-Specific Rate Limiting

Pattern 4: Sliding Window Rate Limiting

Pattern 5: Quota Management

Authentication Patterns

Pattern 1: API Key Authentication

Pattern 2: JWT Authentication

Pattern 3: OAuth 2.0 Authorization

Pattern 4: OpenID Connect (OIDC)

Pattern 5: mTLS (Mutual TLS) Authentication

Load Balancing Patterns

Pattern 1: Round-Robin Load Balancing

Pattern 2: Weighted Load Balancing

Pattern 3: Consistent Hashing

Pattern 4: Least Connections

Pattern 5: Active Health Checks

Traffic Control Patterns

Pattern 1: Circuit Breaker

Pattern 2: Request Timeout

Pattern 3: Retry Logic

Pattern 4: Request Size Limiting

Pattern 5: Traffic Shaping (Throttling)

Request/Response Transformation

Pattern 1: Request Header Manipulation

Pattern 2: Response Header Manipulation

Pattern 3: Request Body Transformation

Pattern 4: GraphQL to REST Translation

Pattern 5: Protocol Translation

Caching Patterns

Pattern 1: Response Caching

Pattern 2: Conditional Caching

Pattern 3: Cache Invalidation

Pattern 4: Multi-Tier Caching

Pattern 5: Surrogate-Key Based Invalidation

Security Patterns

Pattern 1: CORS (Cross-Origin Resource Sharing)

Pattern 2: IP Restriction

Pattern 3: Bot Detection

Pattern 4: Request Validation

Pattern 5: WAF (Web Application Firewall)

Observability Patterns

Pattern 1: Request Logging

Pattern 2: Distributed Tracing

Pattern 3: Metrics Collection

Pattern 4: Health Checks

Pattern 5: Error Tracking

Multi-Environment Patterns

Pattern 1: Environment Separation

Pattern 2: Blue-Green Deployments

Pattern 3: Canary Releases

Pattern 4: Feature Flags

Pattern 5: Multi-Region Deployment

Best Practices

Architecture Design

Security Best Practices

Performance Optimization

Operational Excellence

Plugin Strategy

Configuration Management

Scaling Guidelines

Common Use Cases

Use Case 1: SaaS API Platform