Deep Dive into Amazon API Gateway: An “API Front Design” Guide Through Comparison with Cloud Endpoints / API Gateway (GCP) and Azure API Management

Introduction (Key Takeaways)

• In this article, we focus on Amazon API Gateway and organize our thinking about API front design, security, and cost optimization by comparing it with Cloud Endpoints / API Gateway on GCP and Azure API Management (APIM).
• Amazon API Gateway is a service that fully manages the exposure, protection, and scaling of HTTP / REST / WebSocket APIs, acting as the “front tier” for Lambda, ECS / EKS, ALB, and other AWS services.
• On GCP, Cloud Endpoints / API Gateway, and on Azure, Azure API Management, occupy a similar role. In any cloud, they are designed as a single, secure entry point for incoming external traffic.
• Key points for design:
  1. First clarify what kinds of clients (SPA / mobile / server-to-server) call which APIs in what way
  2. Decide how much authentication, authorization, rate limiting, and logging you will offload to the API front
  3. Decide the boundary for what is delegated to the backend (Lambda / ECS / EKS / other services)
  4. Decide simply which to use among REST API / HTTP API / WebSocket API
  5. Design in such a way that the same design principles can be replicated on GCP / Azure
• Intended readers:
  • Backend developers for web / mobile apps
  • Tech leads / architects designing microservice platforms or BFFs (Backend for Frontend)
  • SRE / infrastructure / security engineers interested in API security, governance, and rate limiting
• By the end, the goal is for you to confidently say,
  “For our service, this is the realistic way to use API Gateway / Cloud Endpoints / APIM.”

1. What Is Amazon API Gateway? The “Front Door” in the Cloud Era

1.1 Conceptual Role

Put simply, Amazon API Gateway is:

“A ‘front door’ that receives all HTTP / WebSocket requests from clients (browsers, mobile apps, other systems),
performs authentication, authorization, rate limiting, transformation, and routing,
then forwards them to backends (Lambda / ECS / EKS / other services).”

Its main features include:

• API exposure (providing endpoint URLs, stage management)
• Authentication / authorization (IAM / Cognito / Lambda authorizers / API keys)
• Rate limiting, throttling, quotas
• Request / response transformation (mapping templates, header manipulation, etc.)
• Caching (REST API stage cache)
• Logging / metrics (integration with CloudWatch)
• Backend integrations (Lambda / HTTP / AWS services / VPC endpoints, etc.)

On GCP, Cloud Endpoints / API Gateway, and on Azure, Azure API Management, act as the same “front door.” Even though the terminology and UI differ, they share the same concept of “controlling everything at the entry point.”

1.2 What Backends Can It Work With?

Typical backends you can place behind Amazon API Gateway include:

• AWS Lambda (fully serverless backend)
• Containers on ECS / EKS (via NLB / ALB)
• Application servers on EC2
• Other AWS services (Step Functions / SQS / Kinesis / DynamoDB, etc.)
• On-premises or other cloud HTTP endpoints (via VPC / VPN / Direct Connect)

In other words, the strength of API Gateway is that “it can hide almost anything as long as it speaks HTTP / WebSocket.”

2. Rough Comparison with Equivalent Services on GCP / Azure

Before diving deeper, let’s briefly look at the equivalent services in other clouds.

2.1 GCP: Cloud Endpoints / API Gateway

• Cloud Endpoints
  • A managed API management service based on OpenAPI / gRPC specifications, providing API exposure, authentication, logging, and more.
  • Sits in front of existing GCE / GKE / Cloud Functions / Cloud Run backends.
• GCP API Gateway
  • A newer service that acts as the practical “API Gateway” in front of Cloud Functions / Cloud Run / GCE.
  • Integrated with IAM, API keys, JWT, Cloud Logging / Monitoring, etc.

2.2 Azure: Azure API Management (APIM)

• Azure API Management provides:
  • An API gateway
  • A developer portal
  • Analytics and reporting
  • Policy-based transformation and security
    all bundled into a full-featured API management platform.
• It works as the front tier for any backend—Azure Functions, App Service, AKS, VMs, etc.—and richly supports enterprise-grade subscription management, billing integration, and separation of external vs internal APIs.

Compared to Azure APIM, Amazon API Gateway is better understood as a “lightweight, developer-centric API front gateway,” while Azure APIM is a “full API platform, including governance, developer portals, and contract management.” That mental model helps keep the balance clear.

3. Building Blocks of Amazon API Gateway

3.1 API, Stage, Resource, Method

API Gateway’s basic structure consists of:

• API
  • A logical API unit.
  • Examples: “User API,” “Order API,” “Admin API,” etc.
• Stage
  • Each API can have multiple stages such as dev, stg, and prod.
  • You can vary URLs, logging, caching, and throttling settings per stage.
• Resource
  • A unit corresponding to part of the API path.
  • Examples: /users, /users/{userId}, /orders, /orders/{orderId}, etc.
• Method
  • An HTTP method (GET / POST / PUT / DELETE, etc.) applied to each resource.
  • Each method has its own integration target, auth method, mapping, and more.

On GCP, Cloud Endpoints / API Gateway also define paths and methods in an OpenAPI spec and use that to control gateway behavior. Azure APIM has a similar structure of “API → Operations (methods),” so the mental model is close.

3.2 Types of Integrations

The “Integration” defines how each method is wired to the backend. The main types are:

• Lambda integration (Lambda proxy / non-proxy)
• HTTP integration (external URLs, ALB / NLB, etc.)
• AWS service integration (direct calls to DynamoDB / SQS / Step Functions, etc.)
• Mock integration (returns a fixed response with no backend)

The Lambda proxy integration is especially common:

• Requests are passed through almost as-is to a Lambda function,
• The Lambda function then freely constructs a response and returns it.

This gives you a straightforward, code-centric way to control behavior.

4. Types of APIs: REST API / HTTP API / WebSocket API

Amazon API Gateway has three main types of APIs. They differ in characteristics, so it’s worth understanding them clearly.

4.1 REST API

• The “older” type of API in API Gateway.
• Very feature-rich, with:
  • Stage caching
  • Resource policies
  • Usage plans / API keys
  • Mapping templates (Velocity Template Language)
    and more, allowing very fine-grained control.
• In return, it has many configuration options and is generally more expensive than HTTP API.
• Many existing design guides and books on API Gateway assume REST API, so you also need to consider alignment with existing assets.

4.2 HTTP API

• A newer API type designed to be simple and low cost.
• Characteristics:
  • Focuses on integration with Lambda and HTTP backends
  • Supports OpenID Connect / JWT authentication
  • Has a smaller feature set than REST API, but is simpler to configure
  • Typically cheaper and sometimes lower latency than REST API
• On the flip side:
  • Features like stage caching and very detailed mapping templates
    may require REST API instead.

For new “normal HTTP APIs,” the modern pattern is to consider HTTP API first, and fall back to REST API only when you really need extra features.

4.3 WebSocket API

• Aimed at use cases that need bi-directional communication such as chat, online games, and real-time notifications.
• The client keeps a long-lived connection, and events ($connect, $disconnect, $default, etc.) trigger calls to Lambda or HTTP backends.
• On GCP / Azure, WebSocket handling is usually done more by load balancers or by App Service / Cloud Run directly, rather than by the API gateway itself, so “having WebSocket support in the API Gateway itself” is a distinctive characteristic of AWS.

5. Authentication, Authorization, and Security Design

5.1 What You Can Do on the API Gateway Side

Amazon API Gateway lets you configure per-API or per-method authentication / authorization:

• IAM authorization
  • Controls access based on IAM policies of the caller (IAM users / roles / Cognito-authenticated users, etc.).
  • Best suited for server-to-server protection.
• Cognito authorizer (JWT)
  • API Gateway validates ID tokens / access tokens issued by a Cognito User Pool.
  • Ideal for “user-authenticated clients” such as SPAs and mobile apps.
• Lambda authorizer (custom)
  • A Lambda function performs token validation and permission checks, then returns an IAM policy document.
  • Great for complex custom logic with proprietary JWTs, API keys, IP-based decisions, etc.
• API keys + usage plans
  • API keys can be issued per consumer and linked to quotas and rate limits, supporting billing or partner-facing APIs.

On top of this, you can layer WAF (Web Application Firewall) and Shield (DDoS protection) via CloudFront or ALB to build a multi-layer defense.

5.2 Resource Policies and Private APIs

• With REST API, you can use resource policies to:
  • Allow only specific VPC endpoints
  • Allow only specific IP/CIDR ranges
  • Allow only particular AWS accounts
    This enables fine-grained access control.
• With private APIs, you can create “internal APIs” that are inaccessible from the internet and callable only from within a VPC (or via VPC connectivity).
• GCP’s Private Service Connect and Azure’s VNet integration + private endpoints provide similar ways to build “internal-only APIs”.

6. Performance, Throttling, and Caching

6.1 Rate Limiting and Throttling

API Gateway supports throttling at:

• Account / region level
• Stage level
• Usage plan (API key) level

This allows you to:

• Protect your backend from unexpected traffic spikes
• Set per-partner usage limits
• Implement free and paid tiers with different quotas

In short, it makes “traffic shaping at the front door” easy.
On GCP and Azure, API Gateway / APIM also provide rate limiting and quota features with similar design concepts.

6.2 Caching (REST API)

REST API lets you enable caching per stage:

• Cache keys:
  • Defined by path, query parameters, headers, etc.
• Effects of caching:
  • Reduces load on backends (Lambda / ECS / DB, etc.) and speeds up responses
  • Especially effective for APIs with many reads and infrequent updates

Since caching is charged by capacity, you need to consider division of responsibilities with CloudFront caching and app-side caching.
HTTP API lacks stage caching, so you typically rely on CloudFront and client-side caching for such scenarios.

7. Logging, Monitoring, and Tracing

7.1 CloudWatch Logs / Metrics

API Gateway can send the following to CloudWatch:

• Access logs
  • Request path, query parameters, headers, response codes, latency, etc.
  • Outputting them in JSON makes downstream processing easier.
• Execution logs
  • Internal details like mapping template errors, integration errors, etc.
• Metrics
  • Request counts
  • 4xx / 5xx error counts and rates
  • Latency (average / p99, etc.)
  • Cache hit rate (for REST API)

You can plug these into CloudWatch dashboards and alarms to keep the “health of your APIs” visible at all times.
On GCP, Cloud Logging / Monitoring plays the same role; on Azure, Log Analytics / Azure Monitor / Application Insights do.

7.2 Tracing with X-Ray and Others

• Combined with Lambda / ECS / EKS backends, you can use X-Ray and other distributed tracing tools to:
  • Identify which APIs are slow
  • See which backend components are causing delays
• GCP’s Cloud Trace and Azure’s Application Insights / OpenTelemetry-based tracing provide similar end-to-end observability across APIs and backends.

8. Pricing Model and Cost Optimization Tips

8.1 Rough Pricing Model

You should always check the official pricing page for exact numbers, but roughly speaking, charges are based on:

• API call volume (unit price differs by REST / HTTP / WebSocket)
• Data transfer volumes (across regions / to the internet)
• Cache capacity (for REST API)
• Surrounding services like custom domains, WAF, etc.

HTTP API is priced cheaper than REST API, making it quite attractive for “simple HTTP API” use cases.

8.2 Design Tips for Cost Efficiency

• Prefer HTTP API when possible
  • If your required auth, logging, and routing features fit inside HTTP API, choosing HTTP API alone can often reduce costs.
• Leverage CloudFront and client-side caching
  • APIs that return the same response repeatedly are sometimes more efficiently cached at layers in front of API Gateway.
• Avoid unnecessarily large payloads
  • Returning images or huge JSON bodies directly inflates data transfer costs. Consider redirecting to S3 or using partial retrieval.
• Choose appropriate API granularity
  • Instead of calling 10 APIs per screen, bundling them into 1–2 calls often helps both cost and latency (the BFF pattern).

On GCP / Azure, pricing is also driven by call counts, data transfer, and add-on features (developer portal, policies, etc.), so you can apply similar optimization strategies.

9. Example Architectures and Design Patterns

Let’s go through a few representative patterns.

9.1 Pattern 1: Fully Serverless SPA + Lambda

• Frontend:
  • S3 + CloudFront hosting an SPA (React / Vue, etc.)
• API:
  • Amazon API Gateway (HTTP API)
  • Backend: AWS Lambda (Node.js / Python, etc.)
  • Data stores: DynamoDB / RDS, etc.

Characteristics:

• Almost zero infrastructure operations (serverless)
• Auto scaling; ideal for small to mid-size services, PoCs, and new products.
• On GCP, a similar setup is Cloud Run / Cloud Functions + API Gateway / Cloud Endpoints; on Azure, Functions + APIM.

9.2 Pattern 2: Containers on ECS / EKS + API Gateway

• Backend runs on ECS / EKS with state in RDS / DynamoDB, etc.
• API Gateway → VPC link → NLB / ALB → ECS / EKS using HTTP integration.

Characteristics:

• Ideal for organizations that already have a container platform, yet want a unified, protected front for external APIs via API Gateway.
• IP restrictions, WAF, auth, etc. can be centrally managed in API Gateway, letting backends focus on business logic.
• On GCP, a similar setup is GKE + Cloud Endpoints / API Gateway; on Azure, AKS + APIM / Application Gateway.

9.3 Pattern 3: API Gateway as BFF (Backend for Frontend)

• When you want separate APIs optimized for different clients (mobile apps, multiple SPAs, external partners), you can create APIs like:
  • mobile-api.example.com
  • web-api.example.com
  • partner-api.example.com
    on API Gateway and route them internally to the same backend microservices.

Characteristics:

• For each client type, you can vary:
  • Response formats
  • Auth patterns
  • Rate limits
    giving you a flexible front layer.
• Azure APIM can realize the same pattern with “Products / APIs / Policies,” and on GCP you can similarly combine multiple gateway configs with IAM / API keys.

10. Summary of Comparison with Other Clouds

Based on what we’ve covered, let’s summarize how Amazon API Gateway compares with equivalents on GCP / Azure.

10.1 Feature-Level Comparison

• Amazon API Gateway
  • REST / HTTP / WebSocket APIs
  • Strong integration with Lambda and other AWS services
  • Smooth integration with CloudFront / WAF / Cognito / IAM
  • Developer portal and billing integration are usually implemented via separate services
• GCP Cloud Endpoints / API Gateway
  • API management based on OpenAPI / gRPC
  • Excellent integration with Cloud Run / Functions / GKE
  • Natural integration with Cloud Logging / Monitoring / IAM
• Azure API Management
  • “All-in-one” solution: API gateway + developer portal + analytics + subscription management
  • Powerful policy-based control (transformation, auth integration, caching)
  • Often assumes tight integration with Entra ID (formerly Azure AD), suited for enterprise IT environments

10.2 Rough Guidelines for Choosing

• Mainly on AWS with Lambda / ECS / EKS backends
  → Amazon API Gateway (default to HTTP API)
• Mainly on GCP with Cloud Run / Functions / GKE
  → Cloud Endpoints / API Gateway
• Mainly on Azure, needing integrated AD / API management / external API governance
  → Azure API Management

In multi-cloud setups, a realistic approach is to use each cloud’s API gateway in front of its workloads and design the public-facing entry at the DNS / routing layer.

11. Common Pitfalls and How to Avoid Them

11.1 Timeouts and Cold Starts with Lambda + API Gateway

• A classic issue is trying to run long processes on Lambda so that they exceed API Gateway’s timeout (REST / HTTP max timeout), causing silent timeouts.
• Countermeasures:
  • Offload long-running tasks to Step Functions or queue-based batches (SQS + worker).
  • Keep Lambda focused on “quick front logic / orchestration.”
  • If cold starts are a concern, consider moving some workloads to containers (ECS / EKS).

11.2 Overly Complex API Config That No One Wants to Touch

• Layering REST API + mapping templates + multiple stages + caching + custom authorizers, etc. can create an “API Gateway no one fully understands.”
• Countermeasures:
  • Use HTTP API for new use cases whenever possible.
  • Avoid packing too much transformation logic into the gateway; push it into code (Lambda / backend).
  • As a team, define and document which layer handles what (auth, transformation, logging, etc.).

11.3 Logs Exist but Nobody Looks at Them

• Another common issue is detailed access logs being output, but no one actually checks CloudWatch Logs and metrics.
• Countermeasures:
  • Build CloudWatch dashboards around SLO-related metrics: “p95 latency,” “5xx rate,” “error counts of specific APIs,” etc.
  • Set thresholds and alarms, and send alerts to Slack / email.
  • On GCP / Azure, likewise centralize metrics in Monitoring / Azure Monitor.

12. Who Benefits? Concrete Value by Role

12.1 Backend / Frontend Developers

• You’ll get a much clearer sense of “what should be handled by API Gateway and what should be done by the backend.”
• For SPA / mobile dev teams, it becomes easier to share:
  • Which tokens to send to which endpoints
  • How to handle rate limiting and errors

12.2 SRE / Platform Engineers

• Understanding Amazon API Gateway, GCP API Gateway, and Azure APIM side by side helps when designing a company-wide API front platform, explaining differences by cloud and proposing optimal combinations.
• Once you standardize rate limiting, WAF, logging, metrics, and tracing in a baseline template, adding new teams or products won’t explode operational costs.

12.3 Security / Governance Teams

• With a bird’s-eye view of auth, authorization, IP restrictions, private APIs, WAF, etc., you can decide which security aspects to enforce at which layer.
• Understanding API Gateway / Endpoints / APIM is powerful when creating policies and checklists defining the minimum requirements for externally exposed APIs.

12.4 Startup CTOs / Tech Leads

• When a small team must create many APIs, it’s crucial to decide:
  • How much to consolidate and delegate to API Gateway
  • From which point each product takes responsibility
• Using this article as a base, you can formulate your “standard API guidelines” so that API design quality remains consistent as the team grows.

13. Three Steps You Can Start Today

1. Pick just three existing APIs you operate and draw their entry diagrams.
   • Sketch on paper or a whiteboard:
     Client → DNS / CloudFront → API Gateway (or other entry) → Backend → DB / other services
2. List for each API its “auth method,” “rate limiting,” “logging,” and “monitoring” setup.
   • If everything is inconsistent, ask whether “a common front like API Gateway” could be used to unify them.
3. Try building one small new API using HTTP API + Lambda (or your existing backend).
   • Even a single small API built with HTTP API will give you a feel for the configuration and logs.
   • On GCP / Azure, do the same with API Gateway / APIM as a PoC to compare.

14. Conclusion: The API Front Is Where You Define the “Common Rules at the Door”

Amazon API Gateway is:

• The “front door” that receives all client requests,
• Manages authentication, authorization, rate limiting, logging, and routing in an integrated way.

GCP and Azure offer similar services, and regardless of the cloud, the core principles are:

• “Define common rules at the entry point”
• “Let backends focus on business logic”
• “Continuously visualize API health through logs and metrics”

You can start small:

• Insert API Gateway / Endpoints / APIM in front of an existing API
• Design new APIs with HTTP API or Cloud Run / APIM under the assumption that there is a gateway in front

Step by step, that leads to a scalable, manageable, and observable API platform.

References (Official Docs / Product Pages)

• Amazon API Gateway product page
• Amazon API Gateway Developer Guide
• Build a REST API with AWS Lambda using Amazon API Gateway
• Introduction to Amazon API Gateway HTTP APIs
• Google Cloud Endpoints documentation
• Google Cloud API Gateway documentation
• Azure API Management documentation
• Azure API Management product page