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Before launching an ECS Fargate service, make its task count, compute model, network access, IAM roles, secret handling, and deployment behavior deliberate. The Terraform AWS Provider documents several defaults that can produce a service different from the one an operator expects: desired_count defaults to 0, launch_type to EC2, and wait_for_steady_state to false. Treat this as a production review checklist, not a universal module recipe: capacity, health checks, egress, and rollout settings depend on the application and its availability requirements.
Will Terraform create the running Fargate service you expect?
Start with the service resource. The Terraform AWS Provider documents desired_count as 0 by default. If you expect tasks to start immediately, set an explicit initial count. If autoscaling is responsible for task count, make that relationship clear and confirm it is configured to establish the capacity you intend.
The provider documents launch_type as defaulting to EC2. For Fargate, explicitly select the intended Fargate launch behavior or configure the capacity-provider strategy you mean to use. The provider documents a conflict between launch_type and capacity_provider_strategy, so choose the intended mechanism rather than configuring both.
wait_for_steady_state defaults to false. Decide whether a Terraform apply should wait for ECS to report the service stable, and set the option accordingly. Waiting can make an apply reflect service convergence more directly; it does not replace deployment monitoring or application-level checks.
Does the task definition meet Fargate and application needs?
Fargate tasks require the awsvpc network mode and explicit task CPU and memory. Choose CPU and memory using measured workload needs and a valid Fargate combination for the selected operating system and platform. Do not treat sample values as production sizing guidance.
Keep the two task-definition roles separate:
execution_role_arn: permissions used by ECS agent operations, such as the task operations the execution role is assigned to support.task_role_arn: permissions available to application code running in the container.
Scope each role to its actual duties. Giving the application only its own required access limits what it can do if the workload is compromised; agent permissions belong on the execution role, not in the application role by default.
Can tasks reach only the network resources they need?
With awsvpc, each task receives an elastic network interface. The ECS service therefore needs subnets and security groups, and its traffic design should be explicit rather than inherited from an example.
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Choose deliberately how tasks receive outbound access. In private subnets, image pulls need an outbound route such as NAT unless the image path is served through appropriate ECR interface endpoints. Public IP assignment, NAT, and VPC endpoints are architecture choices, not interchangeable universal defaults. Where policy requires service calls to stay on private network paths, evaluate VPC endpoints for the services the workload uses.
Can secrets reach Terraform state or plan artifacts?
Secrets Manager can store and rotate credentials, but using it does not by itself keep a secret out of Terraform state. If Terraform reads a secret and passes its value into a managed resource, that value can be recorded in state. A data lookup is not a guarantee that downstream use remains absent from state.
- Do not put plaintext credentials in Terraform source.
- Restrict and encrypt remote state, and limit access to plan artifacts as well as state.
- Where the application design allows it, prefer runtime retrieval so Terraform does not need to pass the secret value into a managed resource.
- If Terraform must handle secret values, treat access to state and plans as access to credentials and account for that exposure in rotation planning.
What should happen when a deployment fails?
For a service using the ECS deployment controller, evaluate the deployment circuit breaker and configure its required enable and rollback values intentionally. Enabling rollback allows ECS to return to the last successful deployment when a deployment fails. It is a recovery safeguard, not a substitute for realistic health checks or active rollout monitoring.
Set health-check grace period, minimum and maximum healthy percentages, and task capacity to fit the application’s startup behavior and availability needs. These values are workload-specific; a generic setting cannot establish that a service will start reliably or remain available during replacement.
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What production controls belong around the Terraform deployment?
AWS manages parts of the underlying infrastructure, but responsibility for the workload remains shared. The application owner still needs to make decisions about workload data, networking, runtime security, logging, and monitoring. Review those responsibilities alongside the Terraform rather than assuming that using Fargate covers them.
Before applying production changes, review the Terraform plan for the intended task count, launch or capacity-provider choice, network exposure, IAM scope, secret handling, and deployment behavior. Protect the state and plan access paths, and ensure the operational team can observe service health and respond to a failed rollout. These checks make the configuration and its operational consequences visible before the service depends on them.
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