Remote Backends#

Every team beyond a single developer needs remote state. The three major backends:

S3 + DynamoDB (AWS):

terraform {
  backend "s3" {
    bucket         = "myorg-tfstate"
    key            = "prod/network/terraform.tfstate"
    region         = "us-east-1"
    dynamodb_table = "terraform-locks"
    encrypt        = true
  }
}

Azure Blob Storage:

terraform {
  backend "azurerm" {
    resource_group_name  = "tfstate-rg"
    storage_account_name = "myorgtfstate"
    container_name       = "tfstate"
    key                  = "prod/network/terraform.tfstate"
  }
}

Google Cloud Storage:

terraform {
  backend "gcs" {
    bucket = "myorg-tfstate"
    prefix = "prod/network"
  }
}

All three support locking natively (DynamoDB for S3, blob leases for Azure, object locking for GCS). Always enable encryption at rest and restrict access with IAM.

IAM: Identity and Access Management#

IAM controls who can do what in your AWS account. Everything in AWS is an API call, and IAM decides which API calls are allowed. There are three concepts an agent must understand: users, roles, and policies.

Users are long-lived identities for humans or service accounts. Roles are temporary identities that can be assumed by users, services, or other AWS accounts. Policies are JSON documents that define permissions. Roles are always preferred over users for programmatic access because they issue short-lived credentials through STS (Security Token Service).

AWS Lambda and Serverless Function Patterns#

Lambda runs your code without you provisioning or managing servers. You upload a function, configure a trigger, and AWS handles scaling, patching, and availability. The execution model is simple: an event arrives, Lambda invokes your handler, your handler returns a response. Everything in between – concurrency, retries, scaling from zero to thousands of instances – is managed for you.

That simplicity hides real complexity. Cold starts, timeout limits, memory-to-CPU coupling, VPC attachment latency, and event source mapping behavior all require deliberate design. This article covers the patterns that matter in practice.

Cloud Vendor Product Matrix#

Choosing between cloud vendors requires mapping equivalent services across providers. AWS has 200+ services. Azure has 200+. GCP has 100+. Cloudflare has 20+ but they are tightly integrated and edge-native. This article maps the services that matter for most applications – compute, serverless, databases, storage, networking, and observability – across all four vendors with pricing, availability, and portability for each.

How to Use This Matrix#

Each section maps equivalent products across vendors, then provides:

Zero-Egress Architecture with Cloudflare R2#

Every major cloud provider charges you to download your own data. AWS S3 charges $0.09/GB. Google Cloud Storage charges $0.12/GB. Azure Blob charges $0.087/GB. These egress fees are the most unpredictable line item on cloud bills – they scale with success. The more users download your data, the more you pay.

Cloudflare R2 charges $0 for egress. Zero. Unlimited. Every download is free, whether it is 1 GB or 100 TB. R2 uses the S3-compatible API, so existing tools and SDKs work without changes. This single pricing difference changes how you architect storage, serving, and cross-cloud data flow.

Why Remote State#

Terraform stores the mapping between your configuration and real infrastructure in a state file. By default this is a local terraform.tfstate file. That breaks the moment a second person or a CI pipeline needs to run terraform apply. Remote state solves three problems: team collaboration (everyone reads the same state), CI/CD access (pipelines need state without copying files), and disaster recovery (your laptop dying should not lose your infrastructure mapping).