AWS API Gateway Setup: Terraform, Auth, Monitoring

Developing a microservice on Lambda and getting error 502 — integration timeouts. Or a client complains about response speed while CloudWatch logs show delays up to 10 seconds. Most likely, the issue is with API Gateway configuration: incorrect timeout, missing caching, or wrong authorizer type. Over 5 years of working with AWS, we've configured more than 50 API Gateways — from simple REST proxies to multi-region gateways with Cognito and custom authorizers. Recently, on one project, a wrong timeout configuration caused endpoint failure under peak load. After switching from HTTP to REST API and enabling caching, latency dropped by 40%, and infrastructure costs decreased by 30%. Order a free consultation — we'll help you save up to 30% on your monthly API Gateway expenses.

We solve these problems: incorrect Lambda integration (N+1 DynamoDB queries due to poor design), lack of throttling leading to backend overload, and wrong API type selection — REST instead of HTTP, causing you to pay 3.5 times more. Proper API Gateway configuration can reduce latency by 40% and prevent downtime. Optimal caching setup cuts latency in half.

How to Choose Between REST API and HTTP API?

HTTP API suits simple backend->Lambda proxies. REST API is needed for complex request transformation and throttling by API keys. If you're just starting out, choose HTTP — it's 3.5 times cheaper. A proper choice can save up to 20% of your infrastructure budget.

How to Reduce API Gateway Costs?

Choosing the right API type is just the first step. Enabling caching at the gateway level reduces the number of Lambda invocations, directly impacting cost. Under high load, switching from HTTP to REST with caching can lower costs by 30–50%. Also use Terraform for automation: eliminating manual errors reduces costly incidents. We'll assess your scenario and propose the optimal configuration — contact us for details.

Why Use Terraform for API Gateway?

Terraform allows versioning infrastructure as code, avoiding manual configuration errors and reproducing environments in minutes. Below is a typical REST API configuration with Cognito authorization that we use in every project.

# main.tf
resource "aws_api_gateway_rest_api" "main" {
  name        = "myapp-api"
  description = "Main application API"
  endpoint_configuration {
    types = ["REGIONAL"]
  }
}

resource "aws_api_gateway_resource" "users" {
  rest_api_id = aws_api_gateway_rest_api.main.id
  parent_id   = aws_api_gateway_rest_api.main.root_resource_id
  path_part   = "users"
}

resource "aws_api_gateway_method" "users_get" {
  rest_api_id   = aws_api_gateway_rest_api.main.id
  resource_id   = aws_api_gateway_resource.users.id
  http_method   = "GET"
  authorization = "COGNITO_USER_POOLS"
  authorizer_id = aws_api_gateway_authorizer.cognito.id
  request_parameters = {
    "method.request.querystring.page"  = false
    "method.request.querystring.limit" = false
  }
}

resource "aws_api_gateway_integration" "users_get" {
  rest_api_id             = aws_api_gateway_rest_api.main.id
  resource_id             = aws_api_gateway_resource.users.id
  http_method             = aws_api_gateway_method.users_get.http_method
  integration_http_method = "POST"
  type                    = "AWS_PROXY"
  uri                     = aws_lambda_function.users_handler.invoke_arn
}

Cognito Authorizer

resource "aws_api_gateway_authorizer" "cognito" {
  name            = "cognito-authorizer"
  rest_api_id     = aws_api_gateway_rest_api.main.id
  type            = "COGNITO_USER_POOLS"
  provider_arns   = [aws_cognito_user_pool.main.arn]
  identity_source = "method.request.header.Authorization"
}

Lambda Authorizer (Custom Authentication)

resource "aws_api_gateway_authorizer" "lambda" {
  name                             = "lambda-authorizer"
  rest_api_id                      = aws_api_gateway_rest_api.main.id
  authorizer_uri                   = aws_lambda_function.authorizer.invoke_arn
  authorizer_result_ttl_in_seconds = 300
  type                             = "TOKEN"
  identity_source                  = "method.request.header.Authorization"
}

Usage Plans and API Keys

resource "aws_api_gateway_usage_plan" "standard" {
  name = "standard-plan"
  api_stages {
    api_id = aws_api_gateway_rest_api.main.id
    stage  = aws_api_gateway_stage.prod.stage_name
  }
  throttle_settings {
    burst_limit = 100
    rate_limit  = 50
  }
  quota_settings {
    limit  = 10000
    period = "DAY"
  }
}

resource "aws_api_gateway_api_key" "partner_app" {
  name = "partner-app-key"
}

resource "aws_api_gateway_usage_plan_key" "partner" {
  key_id        = aws_api_gateway_api_key.partner_app.id
  key_type      = "API_KEY"
  usage_plan_id = aws_api_gateway_usage_plan.standard.id
}

Stage, Logging, and Deployment

resource "aws_api_gateway_deployment" "main" {
  rest_api_id = aws_api_gateway_rest_api.main.id
  triggers = {
    redeployment = sha1(jsonencode([
      aws_api_gateway_resource.users.id,
      aws_api_gateway_method.users_get.id,
      aws_api_gateway_integration.users_get.id,
    ]))
  }
  lifecycle {
    create_before_destroy = true
  }
}

resource "aws_api_gateway_stage" "prod" {
  deployment_id = aws_api_gateway_deployment.main.id
  rest_api_id   = aws_api_gateway_rest_api.main.id
  stage_name    = "prod"
  access_log_settings {
    destination_arn = aws_cloudwatch_log_group.api_gateway.arn
    format = jsonencode({
      requestId      = "$context.requestId"
      sourceIp       = "$context.identity.sourceIp"
      requestTime    = "$context.requestTime"
      httpMethod     = "$context.httpMethod"
      routeKey       = "$context.routeKey"
      status         = "$context.status"
      responseLength = "$context.responseLength"
      latency        = "$context.responseLatency"
    })
  }
}

resource "aws_api_gateway_method_settings" "prod" {
  rest_api_id = aws_api_gateway_rest_api.main.id
  stage_name  = aws_api_gateway_stage.prod.stage_name
  method_path = "*/*"
  settings {
    throttling_burst_limit = 500
    throttling_rate_limit  = 200
    logging_level          = "INFO"
    metrics_enabled        = true
  }
}

How to Set Up Monitoring and Alerts?

1. Enable metrics_enabled = true in the stage settings.
2. Define key metrics: 4XXError, 5XXError, Latency, Count.
3. Create CloudWatch Alarms based on thresholds (see table below).
4. Configure SNS notifications for alerts.

This approach allows timely reaction to issues and maintains SLA.

What's Included in the Work

Delivery Timelines

Setting up a REST API with one authorizer and usage plan takes 3–5 business days. If a custom domain or complex transformation is required, up to 7 days. Exact timelines are assessed after a free audit of your project.

End-to-end API Gateway setup can save up to 30% of development costs by using infrastructure as code. Our team of certified AWS engineers has 5+ years of experience and 50+ successful API Gateway projects. Contact us for a free consultation — we'll prepare a custom proposal and calculate your real savings. Get a project assessment today.

API Development with REST, GraphQL, WebSocket, and tRPC

A client comes to us with a Postman collection of 200 endpoints and says: 'Everything works, but the frontend is slow.' We open the Network tab — 47 sequential requests to load one dashboard page. Each one waits for the previous. This is not a server speed issue — it's an API architecture problem. With 10 years on the market, we've redesigned dozens of such integrations, and we guarantee: the right protocol and contract solve the problem at its root.

When REST stops being enough

REST works well for simple CRUD operations. But as soon as a mobile app appears alongside the web interface, over-fetching begins: the mobile app requests /api/users/123 and gets a 4KB object, but only needs name and avatar. Multiply that by a list of 50 users — 200KB traffic instead of 8KB.

GraphQL solves this with selection sets. The client describes exactly the fields it needs, and the server returns only those. On a project with React Native + Next.js, we migrated from REST to Apollo Server: payload size on the main screen dropped from 340KB to 28KB — a 92% traffic savings. Our certified engineers confirm: the typical pain when adopting GraphQL is N+1 query. A resolver for the author field on a post calls SELECT * FROM users WHERE id = ? for each post in the list. On a page with 20 posts — 21 database queries. Solved with DataLoader — it batches queries and turns them into one SELECT * FROM users WHERE id IN (...).

What is tRPC and how is it better than REST/GraphQL?

If the entire stack is TypeScript (Next.js + Node/Bun), tRPC removes a whole layer of problems. You define a procedure on the server — the client gets full type-safety automatically, without code generation and without Swagger. Renamed a field in the Zod schema — TypeScript highlights all places on the frontend where it's used. tRPC reduces code by 2 times compared to REST + Swagger + openapi-typescript: no need to maintain a separate specification and generate types — everything is inferred from runtime validators. However, tRPC is not suitable if the API is consumed by third-party clients or mobile apps in other languages — in such cases we use GraphQL or REST with OpenAPI specification.

WebSocket and real-time: when SSE, when WS?

HTTP polling every 5 seconds is an illusion of real-time with up to 5 seconds delay and useless server load. For chats, live notifications, collaborative editing — WebSocket or Server-Sent Events. SSE is a one-way stream from server to client, works over ordinary HTTP, automatically reconnects. Suitable for notifications, data streaming, progress bars. WebSocket is bidirectional, needed for chats and collaborative features. Experience shows: 80% of 'real-time' tasks are solved with SSE, not WebSocket — fewer infrastructure complexities.

A typical mistake: opening a WebSocket connection for each page component. On one project, the dashboard opened 12 parallel WS connections. The correct approach is one connection manager at the application level, subscriptions through it. In our work results, we always transfer the connection scheme and a ready solution.

Swagger / OpenAPI as a contract

Documentation written after the fact becomes outdated the day after release. We write the OpenAPI 3.1 specification before development starts; it becomes the contract between frontend and backend. The frontend generates types via openapi-typescript, the backend validates incoming data using generated schemas. Contract deviation from implementation is caught on CI, not during review. For Laravel — l5-swagger or dedoc/scramble. For Node.js — @fastify/swagger or Zod + zod-to-openapi.

How to properly authenticate an API?

JWT with long-lived access tokens without rotation is a source of problems when compromised. The correct scheme: access token for 15 minutes, refresh token for 30 days with rotation on each use. Refresh token stored in an httpOnly cookie, access token in memory (not in localStorage). For inter-service communication — API Keys with scope limitations or mTLS. OAuth 2.0 with PKCE for public clients (SPA, mobile).

How to handle versioning and backward compatibility?

Breaking changes in an API without versioning break clients. Three approaches we use in projects:

We guarantee backward compatibility through automated checks (oasdiff) on CI.

How we develop APIs: step-by-step plan

1. Analysis — audit of current integrations, data schema compilation, protocol selection (REST/GraphQL/tRPC/WebSocket).
2. Contract design — OpenAPI or SDL (GraphQL) before the first line of code.
3. Development — implementation per contract, unit tests for each endpoint.
4. Load testing — k6: 500 virtual users, 10 minutes, p95 latency ≤ 200ms.
5. Deployment — CI/CD with backward compatibility check, automatic documentation publication.
6. Team training — handover of Postman collection or Playground, connection instructions.

What is included (deliverables)

• OpenAPI 3.1 specification (or SDL for GraphQL).
• Generated client types for TypeScript / Dart / Kotlin.
• Set of automated tests covering all endpoints (unit + integration).
• Load tests (k6) and report (p50/p95/p99 latency, RPS).
• Documentation in Swagger UI / Redoc / GraphiQL.
• Team training (2–4 hour workshop).
• Support for 30 days after delivery (per contract).

Our experience

• 10+ years in the API development market.
• 200+ completed projects (REST, GraphQL, WebSocket, tRPC).
• 50+ certified engineers (AWS, Kubernetes, API Design).
• Traffic savings averaging 85% when migrating from REST to GraphQL for mobile apps.
• 100% backward compatibility — not a single broken client in the last 3 years.

Timeline

API development for a typical SaaS project with 30–50 endpoints: from 3 to 8 weeks depending on business logic complexity and number of external integrations. Migration of an existing REST API to GraphQL: from 2 to 6 weeks. Adding a WebSocket layer to an existing backend: from 1 to 3 weeks. Cost is calculated individually after an audit. Get a consultation — contact us to discuss your project.