The order matters
When you’re working with Terraform to provision cloud infrastructure, understanding how to manage resource dependencies effectively can make the difference between a smooth deployment and hours of troubleshooting. Whether you’re deploying infrastructure in New York, London, Tokyo, or anywhere else globally, proper dependency management ensures your resources are created, updated, and destroyed in the correct order.
Understanding resource dependencies in Terraform
Resource dependencies in Terraform define the relationships between different infrastructure components. Think of it like building a house – you can’t install the roof before laying the foundation. Similarly, in Terraform, certain resources must exist before others can be created. For instance, you need a virtual network before you can deploy virtual machines within it.
Terraform handles dependencies in two primary ways: implicit dependencies and explicit dependencies. The beauty of Terraform lies in its ability to automatically detect most dependencies through resource references, but sometimes you need to take control and explicitly define these relationships yourself.
Implicit dependencies: letting Terraform do the heavy lifting
Implicit dependencies are the most common type you’ll encounter in your Terraform configurations. These occur naturally when one resource references attributes from another resource. Terraform’s dependency graph automatically identifies these relationships and determines the correct order for resource creation.
Let me show you a practical example. When you create an AWS EC2 instance that references a security group, Terraform automatically understands that the security group must be created first:
resource "aws_security_group" "web_sg" {
name = "web-security-group"
description = "Security group for web servers"
vpc_id = aws_vpc.main.id
ingress {
from_port = 80
to_port = 80
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
}
}
resource "aws_instance" "web_server" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro"
# This reference creates an implicit dependency
vpc_security_group_ids = [aws_security_group.web_sg.id]
tags = {
Name = "Web Server"
}
}In this configuration, the EC2 instance references the security group’s ID. Terraform recognizes this reference and ensures the security group is created before attempting to launch the EC2 instance. This automatic detection saves you from manually specifying dependencies in most cases.
Explicit dependencies with depends_on
While implicit dependencies handle most scenarios, there are situations where Terraform cannot automatically detect the relationship between resources. This is where the depends_on meta-argument comes into play. You’ll typically need explicit dependencies when dealing with resources that don’t directly reference each other but still have a logical dependency.
Consider a scenario where you’re setting up a database and need to ensure certain IAM roles and policies are in place before creating database users:
resource "aws_iam_role" "db_access_role" {
name = "database-access-role"
assume_role_policy = jsonencode({
Version = "2012-10-17"
Statement = [
{
Action = "sts:AssumeRole"
Effect = "Allow"
Principal = {
Service = "rds.amazonaws.com"
}
}
]
})
}
resource "aws_iam_role_policy_attachment" "db_policy" {
role = aws_iam_role.db_access_role.name
policy_arn = "arn:aws:iam::aws:policy/AmazonRDSEnhancedMonitoringRole"
}
resource "aws_db_instance" "database" {
allocated_storage = 20
engine = "postgres"
engine_version = "13.7"
instance_class = "db.t3.micro"
name = "myapp"
username = "dbadmin"
password = var.db_password
# Explicit dependency ensures IAM resources are ready
depends_on = [
aws_iam_role_policy_attachment.db_policy
]
}Working with data sources and dependencies
Data sources in Terraform add another layer to dependency management. They allow you to fetch information about existing resources, but you need to ensure these resources exist before querying them. This is particularly important when working with resources created outside of your current Terraform configuration.
Here’s an example that demonstrates proper dependency management with data sources:
resource "aws_vpc" "main" {
cidr_block = "10.0.0.0/16"
tags = {
Name = "Main VPC"
}
}
# This data source depends on the VPC being created first
data "aws_subnets" "available" {
filter {
name = "vpc-id"
values = [aws_vpc.main.id]
}
# Wait for subnets to be created
depends_on = [aws_subnet.public, aws_subnet.private]
}
resource "aws_subnet" "public" {
vpc_id = aws_vpc.main.id
cidr_block = "10.0.1.0/24"
tags = {
Name = "Public Subnet"
}
}
resource "aws_subnet" "private" {
vpc_id = aws_vpc.main.id
cidr_block = "10.0.2.0/24"
tags = {
Name = "Private Subnet"
}
}Module dependencies and complex scenarios
When you start using Terraform modules, dependency management becomes more sophisticated. Modules encapsulate resources, and you often need to manage dependencies between different modules. The key is to design your modules with clear inputs and outputs that facilitate proper dependency chains.
Consider this example of module dependencies:
module "network" {
source = "./modules/network"
vpc_cidr = "10.0.0.0/16"
region = "us-west-2"
}
module "security" {
source = "./modules/security"
vpc_id = module.network.vpc_id
# This creates an implicit dependency on the network module
}
module "compute" {
source = "./modules/compute"
subnet_ids = module.network.subnet_ids
security_group_ids = module.security.security_group_ids
# Both implicit dependencies are established through references
}Best practices for managing dependencies
Over the years, I’ve learned that following certain best practices can save you from dependency-related headaches. First, always prefer implicit dependencies over explicit ones when possible. They’re easier to maintain and less prone to errors as your infrastructure evolves.
When you must use depends_on, be specific about why you’re using it. Add comments explaining the dependency relationship, especially for non-obvious cases. This helps your team members (and future you) understand the reasoning behind explicit dependencies.
Avoid creating circular dependencies at all costs. These occur when Resource A depends on Resource B, which in turn depends on Resource A. Terraform will detect these and throw an error, but it’s better to design your infrastructure to prevent them from occurring in the first place.
Keep your dependency chains as short as possible. Long chains of dependencies can slow down your Terraform operations and make troubleshooting more difficult. If you find yourself with extremely long dependency chains, consider refactoring your infrastructure design.
Visualizing and debugging dependencies
Terraform provides excellent tools for understanding your dependency graph. The terraform graph command generates a visual representation of your resources and their relationships. You can pipe this output to visualization tools like Graphviz to create diagrams that help you understand complex dependency relationships.
terraform graph | dot -Tpng > dependencies.pngWhen debugging dependency issues, the terraform plan command with the -target flag can help you understand specific resource dependencies:
terraform plan -target=aws_instance.web_serverThis command shows you not only the targeted resource but also all the resources it depends on, helping you trace dependency chains effectively.
Handling dependency failures gracefully
Sometimes dependencies fail, and you need to handle these situations gracefully. Terraform’s create_before_destroy lifecycle rule can help manage resources that need to be replaced without downtime:
resource "aws_instance" "web" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro"
lifecycle {
create_before_destroy = true
}
}For resources with complex dependency relationships, consider using the ignore_changes lifecycle rule to prevent unnecessary updates that might cascade through your dependency chain:
resource "aws_launch_configuration" "example" {
image_id = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro"
lifecycle {
ignore_changes = [image_id]
}
}Conclusion
Managing resource dependencies in Terraform is a fundamental skill that becomes second nature with practice. By understanding the difference between implicit and explicit dependencies, leveraging Terraform’s automatic dependency detection, and following best practices, you can create robust and maintainable infrastructure configurations. Remember that proper dependency management not only ensures resources are created in the correct order but also makes your infrastructure code more readable and easier to troubleshoot. As you continue working with Terraform, you’ll develop an intuition for dependency relationships that will help you design better infrastructure architectures from the start.
FAQs
What happens if I create circular dependencies in Terraform?
Terraform will detect circular dependencies during the planning phase and return an error message indicating which resources are involved in the cycle. You’ll need to restructure your configuration to eliminate the circular reference before Terraform can proceed with any operations.
Can I use depends_on with modules in Terraform?
Yes, starting from Terraform 0.13, you can use depends_on with modules. This allows you to explicitly define dependencies between entire modules, which is useful when module resources don’t have direct references to each other but still need to be created in a specific order.
How do I handle dependencies when using count or for_each?
When using count or for_each, Terraform treats each instance as a separate resource with its own dependencies. You can reference specific instances using index notation for count (e.g., resource.example[0]) or key notation for for_each (e.g., resource.example["key"]). The dependencies work the same way as with single resources.
Is there a performance impact when using explicit dependencies?
Explicit dependencies themselves don’t significantly impact performance, but they can prevent Terraform from parallelizing resource operations. Terraform creates resources in parallel when possible, but explicit dependencies force sequential execution. Use them judiciously to maintain optimal performance.
How can I troubleshoot complex dependency issues in large Terraform configurations?
Start by using terraform graph to visualize your dependency tree. Break down your configuration into smaller, targeted plans using the -target flag. Enable debug logging with TF_LOG=DEBUG to see detailed information about dependency resolution. Consider refactoring complex configurations into smaller, more manageable modules with clear interfaces.
