This error occurs when a Terraform function receives an argument with an invalid value or type. Learn how to identify the problematic parameter and fix type mismatches, null values, and invalid function calls.
The "Invalid function argument" error indicates that a Terraform function has received a parameter value that does not match its expected type or validation rules. This error is triggered by Terraform's function validation system when a custom function parameter's value fails validation checks. Each Terraform function has specific requirements for its parameters. For example, the `length()` function expects a list, map, or string, while `lookup()` expects a map as its first argument. When you pass a value that doesn't match these expectations—such as passing a string to a function expecting a list, or providing a null value to a function that doesn't accept nulls—Terraform will raise this validation error. This error is especially common when working with custom provider functions or when dealing with values from dynamic sources like remote state or local variables where the actual type at runtime differs from what the function expects.
The error message will specify which parameter is invalid. For example:
Error: Invalid value for 'path' parameter: no file exists at [path]Note the parameter name in quotes. This tells you exactly which argument is causing the issue. Check your function call in the configuration file mentioned in the error output.
Visit the Terraform documentation or provider docs to verify what types each parameter should accept. For built-in functions, check the official Terraform language documentation. For custom provider functions, consult the provider's documentation.
Look specifically at:
- Required vs optional parameters
- Expected data type (string, number, list, map, bool, etc.)
- Any validation constraints (e.g., file must exist, value must be in a range)
In your Terraform configuration, identify the function call and check the argument type:
# WRONG: Passing string to length() which expects list
length("not-a-list")
# CORRECT: length() accepts lists, maps, or strings (but string semantics differ)
length(["item1", "item2"])
length(local.my_map)
length("string-value") # Returns string length
# WRONG: Passing a non-map to lookup()
lookup("not-a-map", "key", "default")
# CORRECT: First argument must be a map
lookup(local.my_map, "key", "default")
lookup(var.settings, "key", "default")If the types don't match, modify your argument to match what the function expects.
If you're passing a value that might be null, use conditional expressions or coalesce() to provide a default:
# WRONG: value might be null
some_function(var.optional_value)
# CORRECT: Provide default or check for null
some_function(coalesce(var.optional_value, "default-value"))
# CORRECT: Use conditional expression
some_function(var.optional_value != null ? var.optional_value : "default")This ensures that null values are replaced with valid arguments before being passed to the function.
Use the Terraform console to interactively test your expressions and verify types before including them in your configuration:
terraform console
> length(["a", "b", "c"])
3
> lookup({"key": "value"}, "key", "default")
"value"
> type(var.my_variable)
"string"This helps you understand what type your expression evaluates to and whether it matches the function's requirements.
When using variables or data source outputs, ensure they provide values of the expected type:
variable "config_map" {
type = map(string) # Explicitly declare type as map
}
# When passing to a function expecting a map, this is safe
lookup(var.config_map, "key", "default")
# If type is dynamic or missing, add explicit type validation
variable "unclear_value" {
type = any # Avoid! Specify actual type
}Add explicit type constraints to variables to catch type errors earlier.
For developers creating custom provider functions, Terraform uses the ValidateableParameter interface to enable parameter validation. When implementing custom functions, you can define validation logic that returns meaningful error messages to practitioners using your provider.
The framework provides utilities like NewArgumentFuncError() and ConcatFuncErrors() to associate errors with specific function arguments and provide context about which configuration lines are affected.
When working with type constraints, remember that Terraform's type system includes complex nested types (objects, tuples) and dynamic values. Ensure your function parameters and variable definitions declare explicit types rather than using any, as this helps catch type mismatches during validation rather than at runtime.
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