Custom validation in Terraform is a way to ensure that input variables meet specific conditions or constraints before being applied. It helps in enforcing custom rules and preventing misconfigurations by validating input data. Here’s a comprehensive breakdown of how to use and understand custom validations in Terraform:
1. Overview of Custom Validation in Terraform
- Custom validation allows you to set specific constraints on input variables, ensuring that users provide valid values according to defined rules.
- Terraform uses the
validationblock within avariableblock to enforce these constraints. - This feature helps in reducing errors, especially in complex infrastructure setups, by catching potential misconfigurations early.
2. Basic Structure of Custom Validation
- The
validationblock is defined inside thevariableblock. - A typical
validationblock consists of:
condition: An expression that evaluates totrueorfalse. Iffalse, Terraform will throw an error.
error_message: A custom error message displayed if the condition fails.
Here’s a simple syntax:
CODE
variable "example_variable" {
type = string
validation {
condition = <expression>
error_message = "Your custom error message here."
}
}
3. How condition and error_message Work
condition: This is the core of the custom validation. It contains an expression that evaluates the input.
- If the condition is
true, Terraform accepts the input value. - If
false, Terraform returns the specifiederror_message.
- If the condition is
error_message: Used to guide users when the input value doesn’t meet the specified criteria.
- It’s important to make this message descriptive to inform users what went wrong and possibly how to fix it.
4. Practical Examples of Custom Validation
Example 1: Enforcing a String Length Limit
- Imagine you want to limit an input string to a maximum of 10 characters:
CODE
variable "username" {
type = string
validation {
condition = length(var.username) <= 10
error_message = "The 'username' variable must be 10 characters or less."
}
}
Example 2: Validating Number Ranges
- Let’s say you want to restrict an integer input to a range between 1 and 10:
CODE
variable "instance_count" {
type = number
validation {
condition = var.instance_count >= 1 && var.instance_count <= 10
error_message = "The 'instance_count' must be between 1 and 10."
}
}
Example 3: Restricting String Values to a Set of Options
- If you want to ensure a variable only accepts certain values, use
contains()andlistfunctions:
CODE
variable "environment" {
type = string
validation {
condition = contains(["dev", "stage", "prod"], var.environment)
error_message = "The 'environment' variable must be one of 'dev', 'stage', or 'prod'."
}
}
Example 4: Validating CIDR Format
- Suppose you want to ensure an input is a valid CIDR block:
CODE
variable "subnet_cidr" {
type = string
validation {
condition = can(regex("^([0-9]{1,3}\\.){3}[0-9]{1,3}/[0-9]{1,2}$", var.subnet_cidr))
error_message = "The 'subnet_cidr' must be a valid CIDR block, like '192.168.0.0/16'."
}
}
5. Advanced Validation Techniques
Using can for Error Handling in Validation
- The
can()function helps prevent Terraform from failing due to invalid expressions by testing if an expression can be evaluated without errors. - Example:
CODE
variable "instance_type" {
type = string
validation {
condition = can(length(var.instance_type) > 0)
error_message = "The 'instance_type' must be a non-empty string."
}
}
Combining Multiple Conditions
- You can combine conditions using logical operators (
&&,||) to create complex validations. - Example: Check if a number is either between 1-10 or between 20-30.
CODE
variable "number" {
type = number
validation {
condition = (var.number >= 1 && var.number <= 10) || (var.number >= 20 && var.number <= 30)
error_message = "The 'number' must be between 1-10 or 20-30."
}
}
6. When to Use Custom Validation
- Use custom validation when you need:
- Specific value constraints not achievable with only the
typeattribute. - Rules based on the context of your infrastructure (e.g., only certain regions, specific CIDR formats).
- To avoid common user mistakes in providing input variables.
- Specific value constraints not achievable with only the
7. Limitations of Custom Validation
- Custom validation cannot be used for enforcing relational constraints between two different variables directly. You may need workarounds or consider using Terraform modules if the constraints are too complex.
- It currently only works within the scope of the
variableblock, so custom validations for resources or outputs are not supported.
8. Best Practices for Custom Validation
Use Descriptive Error Messages: Make sure your error messages clearly explain what went wrong and, if possible, suggest how to fix it.
Test Validations: Test each validation thoroughly to ensure it works as expected, especially for complex conditions.
Keep Conditions Simple: Overly complex validation conditions can be harder to understand and maintain.
Consider Usability: Think about how the validation might affect users. For example, don’t enforce overly restrictive rules unless necessary.
9. Real-World Example
Suppose you are setting up a variable for an AWS instance type with specific instance types allowed only in production:
CODE
variable "instance_type" {
type = string
validation {
condition = (
(var.environment == "prod" && contains(["t2.large", "t3.large"], var.instance_type)) ||
(var.environment != "prod" && contains(["t2.micro", "t3.micro"], var.instance_type))
)
error_message = "In 'prod' environment, 'instance_type' must be 't2.large' or 't3.large'. Otherwise, use 't2.micro' or 't3.micro'."
}
}
Summary
Custom validation in Terraform is a powerful feature that enforces specific rules on variables to prevent misconfiguration. By defining condition and error_message in the validation block, you can ensure inputs meet the required constraints, making your infrastructure more robust and resilient.
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