Using The Terraform ‘merge’ Function

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One of the core strengths of Terraform is its rich set of built-in functions, which empower users to create flexible and reusable configurations. Among these functions, the Terraform merge function is particularly powerful, enabling the seamless combination of multiple maps or objects into a single, cohesive unit. This chapter delves into the nuances of the merge function, exploring its syntax, use cases, and practical applications.

As infrastructure grows in complexity, managing configurations can become a daunting task. Different environments (development, staging, production) often require slightly different configurations. Instead of duplicating code and manually updating each environment’s configuration, the merge function allows you to maintain base configurations and apply environment-specific overrides. This not only reduces redundancy but also minimizes the risk of inconsistencies and errors.

Imagine you’re working on a project that involves deploying a set of resources across multiple environments. Each environment might need specific configurations, such as different instance sizes, tags, or network settings. Manually maintaining these configurations can lead to errors and increased maintenance overhead. The merge function simplifies this process by allowing you to define base configurations and selectively override or extend them as needed.

Basic Syntax and Functionality

The merge function’s basic syntax is straightforward and intuitive:

merge(map1, map2, ...)

This function accepts an arbitrary number of maps or objects as arguments and returns a single map or object containing all the elements from the input arguments. If a key appears in multiple maps, the value from the last map with that key is used. This behavior is particularly useful for overriding default configurations with environment-specific settings.

For example, consider the following simple use case:

locals {
  map1 = { a = "apple", b = "banana" }
  map2 = { b = "blueberry", c = "cherry" }

  merged_map = merge(local.map1, local.map2)
}

output "merged_map" {
  value = local.merged_map
}

In this example, the resulting merged_map combines the elements from map1 and map2, with map2‘s value for the key b overriding map1‘s value.

Simple Map Merging

Simple map merging with the merge function is a fundamental technique in Terraform that enables you to combine multiple maps into a single map. This functionality is particularly useful when you need to consolidate configuration settings or manage overrides. Let’s look at how map merging works, including practical examples and key considerations.

Merging Two Maps

Consider the following example where we merge two maps:

locals {
  map1 = { a = "apple", b = "banana" }
  map2 = { b = "blueberry", c = "cherry" }

  merged_map = merge(local.map1, local.map2)
}

output "merged_map" {
  value = local.merged_map
}

In this example:

  • map1 contains { a = "apple", b = "banana" }
  • map2 contains { b = "blueberry", c = "cherry" }

The resulting merged_map will be:

{
  a = "apple"
  b = "blueberry"
  c = "cherry"
}

Here, the value of b from map2 overrides the value from map1.

Detailed Walkthrough

  1. Define the Local Maps:
    First, we define two local maps, map1 and map2. Each map has key-value pairs that represent different configuration settings.
  2. Merge the Maps:
    Using the merge function, we combine map1 and map2. The function processes each map in the order they are provided, combining their key-value pairs into a single map.
  3. Handle Conflicts:
    If there is a conflict (i.e., the same key appears in multiple maps), the value from the last map with that key is used. In our example, the key b appears in both maps. Since map2 is the last map provided, its value for b ("blueberry") overrides the value from map1 ("banana").
  4. Output the Result:
    Finally, we use the output block to display the merged_map. This helps verify that the merge function worked as expected and that the resulting map contains the correct values.

Merging Multiple Maps

The merge function can handle more than two maps. Here’s an example with three maps:

locals {
  map1 = { a = "apple", b = "banana" }
  map2 = { b = "blueberry", c = "cherry" }
  map3 = { c = "citrus", d = "date" }

  merged_map = merge(local.map1, local.map2, local.map3)
}

output "merged_map" {
  value = local.merged_map
}

In this example:

  • map1 contains { a = "apple", b = "banana" }
  • map2 contains { b = "blueberry", c = "cherry" }
  • map3 contains { c = "citrus", d = "date" }

The resulting merged_map will be:

{
  a = "apple"
  b = "blueberry"
  c = "citrus"
  d = "date"
}

Here, the value of c from map3 overrides the value from map2, which in turn had already overridden any potential previous values.

Simple map merging with the merge function is a powerful technique in Terraform. It helps in consolidating configurations, managing overrides, and maintaining consistency across different environments. By understanding and effectively utilizing the merge function, you can enhance the flexibility and maintainability of your Terraform configurations, making your infrastructure management more efficient and less error-prone.

Merging Lists of Objects

Terraform doesn’t directly support merging lists of objects using the merge function, but there are effective workarounds to achieve this. By using a combination of functions such as concat, for, and flatten, you can merge lists of objects dynamically and efficiently. Let’s delve deeper into how this can be accomplished with practical examples.

Combining Lists with concat and for Loops

While Terraform’s merge function works well with maps, you need a different approach to merge lists of objects. The concat function can combine multiple lists into one, and a for loop can then iterate through the combined list to create the final merged list.

Suppose you have two lists of objects that you want to merge. Here’s how you can do it:

locals {
  list1 = [
    { key = "luke", value = "jedi" },
    { key = "yoda", value = "jedi" }
  ]

  list2 = [
    { key = "darth", value = "sith" },
    { key = "palpatine", value = "sith" }
  ]

  merged_list = merge({ for elem in concat(local.list1, local.list2) : elem.key => elem })
}

output "merged_list" {
  value = local.merged_list
}

In this example:

  • list1 contains objects representing two Jedi.
  • list2 contains objects representing two Sith.

The concat function combines list1 and list2 into a single list. The for loop then iterates through this combined list, creating a map where each key is derived from the key attribute of the objects, effectively merging them.

Flattening and Merging Nested Lists

When dealing with nested lists, the flatten function can help simplify the structure before merging. This is particularly useful when your lists contain sub-lists that need to be combined into a single list.

locals {
  nested_list = [
    [
      { key = "luke", value = "jedi" },
      { key = "yoda", value = "jedi" }
    ],
    [
      { key = "darth", value = "sith" },
      { key = "palpatine", value = "sith" }
    ]
  ]

  flattened_list = flatten(local.nested_list)

  merged_list = merge({ for elem in local.flattened_list : elem.key => elem })
}

output "flattened_list" {
  value = local.flattened_list
}

output "merged_list" {
  value = local.merged_list
}

In this setup:

  • nested_list contains two sub-lists, each with objects representing Jedi and Sith.
  • The flatten function combines these sub-lists into a single list.
  • The for loop then merges the flattened list into a map using the key attribute.

Practical Considerations

  1. Key Uniqueness:
    Ensure that the keys used in the merged list are unique. Duplicate keys can lead to unexpected results, as only the last value for a given key will be retained.
  2. Order of Merging:
    The order in which lists are concatenated and processed can affect the final merged result. Always concatenate and merge in the order that aligns with your desired precedence of values.
  3. Type Consistency:
    Maintain consistent data types across your lists. Mixing types within the same attribute can lead to errors and make debugging difficult.

Real-World Example: Merging Resource Configurations

Consider a scenario where you need to merge lists of configuration objects for Azure resources, such as virtual machines and network interfaces. This can be particularly useful when you have different sets of configurations for different environments or teams.

locals {
  base_vms = [
    { name = "vm1", size = "Standard_DS1_v2", location = "East US" },
    { name = "vm2", size = "Standard_DS1_v2", location = "West US" }
  ]

  additional_vms = [
    { name = "vm3", size = "Standard_DS2_v2", location = "East US" },
    { name = "vm4", size = "Standard_DS2_v2", location = "West US" }
  ]

  merged_vms = concat(local.base_vms, local.additional_vms)
}

output "merged_vms" {
  value = local.merged_vms
}

In this example:

  • base_vms contains a list of base virtual machine configurations.
  • additional_vms contains additional virtual machine configurations.
  • The concat function merges these two lists into merged_vms, providing a comprehensive list of VM configurations.

Handling Complex Merges with Conditional Logic

In more complex scenarios, you might need to conditionally include or exclude certain objects based on specific criteria. This can be achieved using Terraform’s conditional expressions within the for loop.

variable "environment" {
  description = "The deployment environment"
  type        = string
}

locals {
  base_configs = [
    { name = "config1", enabled = true },
    { name = "config2", enabled = true }
  ]

  env_specific_configs = {
    production = [
      { name = "config3", enabled = true }
    ]
    development = [
      { name = "config4", enabled = false }
    ]
  }

  merged_configs = concat(local.base_configs, lookup(local.env_specific_configs, var.environment, []))
}

output "merged_configs" {
  value = local.merged_configs
}

In this setup:

  • base_configs contains common configurations.
  • env_specific_configs contains environment-specific configurations.
  • The lookup function retrieves the appropriate environment-specific configurations based on the environment variable.
  • The concat function merges the base and environment-specific configurations into merged_configs.

Merging lists of objects in Terraform requires a combination of functions and careful handling of data structures. By using concat, flatten, and for loops, you can effectively manage complex configurations and ensure your infrastructure definitions are both flexible and maintainable. Whether you’re combining resource configurations or dynamically adjusting settings based on environment variables, these techniques provide a robust framework for managing your Terraform code.

Merging Tags for Cloud Resources

Tagging is a critical practice in managing cloud resources. Tags are key-value pairs that help categorize and manage resources, making it easier to allocate costs, enforce policies, and automate tasks. In Terraform, the merge function can be particularly useful for combining different sets of tags into a comprehensive list. This approach ensures that your resources are consistently tagged across various environments and configurations.

Merging Tags for Azure Resources

Consider a scenario where you have a set of default tags that should apply to all resources, along with additional tags specific to certain environments or projects. By using the merge function, you can combine these tags seamlessly.

Base and Additional Tags Example:

locals {
  default_tags = {
    Environment = "Production"
    Project     = "MyProject"
  }

  additional_tags = {
    CostCenter = "12345"
    Department = "Engineering"
  }

  merged_tags = merge(local.default_tags, local.additional_tags)
}

resource "azurerm_virtual_machine" "example" {
  name                  = "example-vm"
  location              = "West US"
  resource_group_name   = "example-resources"
  network_interface_ids = [
    azurerm_network_interface.example.id,
  ]
  vm_size               = "Standard_DS1_v2"

  tags = local.merged_tags
}

In this example:

  • default_tags contains tags that are applicable to all resources, such as the environment and project name.
  • additional_tags includes tags that might be specific to financial tracking or departmental ownership.
  • The merge function combines these sets of tags into merged_tags, which are then applied to the Azure virtual machine.

Dynamic Tag Merging with Environment-Specific Overrides

Often, different environments like development, staging, and production require specific tags. Terraform allows you to dynamically adjust tags based on the environment.

Dynamic Tags Example:

variable "environment" {
  description = "The deployment environment"
  type        = string
}

locals {
  common_tags = {
    Project = "MyProject"
  }

  env_tags = {
    production = {
      Environment = "Production"
      Department  = "Ops"
    }
    development = {
      Environment = "Development"
      Department  = "Dev"
    }
  }

  merged_tags = merge(local.common_tags, lookup(local.env_tags, var.environment, {}))
}

resource "azurerm_virtual_machine" "example" {
  name                  = "example-vm"
  location              = "West US"
  resource_group_name   = "example-resources"
  network_interface_ids = [
    azurerm_network_interface.example.id,
  ]
  vm_size               = "Standard_DS1_v2"

  tags = local.merged_tags
}

In this setup:

  • common_tags are tags that apply to all environments.
  • env_tags are environment-specific tags that vary between production and development.
  • The lookup function retrieves the correct set of environment-specific tags based on the value of the environment variable.
  • The merge function combines these tags into merged_tags, ensuring that each environment has the appropriate tags applied.

Practical Considerations

  1. Consistency and Standardization:
    Ensure that your tagging strategy is consistent and standardized across your organization. This makes it easier to manage resources and automate processes based on tags.
  2. Avoiding Conflicts:
    When merging tags, be mindful of potential conflicts. Ensure that keys in your default_tags and additional_tags do not unintentionally overwrite each other unless intended. Clear documentation and intentional design can help mitigate this risk.
  3. Automating Tag Management:
    Use Terraform modules to encapsulate tagging logic. This makes it easier to reuse and maintain consistent tagging practices across multiple projects and teams.

Example Module for Tagging

# modules/tags/main.tf
variable "environment" {
  description = "The deployment environment"
  type        = string
}

locals {
  default_tags = {
    Project = "MyProject"
  }

  env_tags = {
    production = {
      Environment = "Production"
      Department  = "Ops"
    }
    development = {
      Environment = "Development"
      Department  = "Dev"
    }
  }

  merged_tags = merge(local.default_tags, lookup(local.env_tags, var.environment, {}))
}

output "tags" {
  value = local.merged_tags
}

# main configuration
module "tags" {
  source      = "./modules/tags"
  environment = var.environment
}

resource "azurerm_virtual_machine" "example" {
  name                  = "example-vm"
  location              = "West US"
  resource_group_name   = "example-resources"
  network_interface_ids = [
    azurerm_network_interface.example.id,
  ]
  vm_size               = "Standard_DS1_v2"

  tags = module.tags.tags
}

This approach modularizes the tagging process, making it easy to apply consistent tags across different resources and environments.

The ability to merge tags in Terraform using the merge function offers significant flexibility and ensures consistent resource management across different environments. By adopting a structured tagging strategy and leveraging Terraform’s capabilities, you can streamline your cloud resource management, enhance automation, and improve operational efficiency.

Handling Nested Maps

When working with complex infrastructure configurations, nested maps are often necessary to represent hierarchical data structures. However, merging nested maps requires careful handling to avoid conflicts and ensure that the final configuration accurately reflects the intended structure. In Terraform, the merge function can help manage these nested structures, but it’s essential to understand its behavior and limitations.

Merging Nested Maps

Let’s consider a scenario where we have two maps, each containing nested structures, and we need to merge them.

Example Configuration:

locals {
  map1 = {
    app = {
      name = "myApp"
      version = "1.0"
    }
    config = {
      port = 80
      protocols = ["http"]
    }
  }

  map2 = {
    app = {
      version = "2.0"
      description = "Updated app"
    }
    config = {
      port = 8080
      protocols = ["https"]
    }
  }

  merged_map = merge(local.map1, local.map2)
}

output "merged_map" {
  value = local.merged_map
}

In this example:

  • map1 contains nested structures for app and config.
  • map2 also contains nested structures for app and config, with some overlapping keys.

The resulting merged_map will be:

{
  app = {
    version = "2.0"
    description = "Updated app"
  }
  config = {
    port = 8080
    protocols = ["https"]
  }
}

Here, the values from map2 overwrite the entire nested structures of map1 where keys overlap.

Deep Merging with Nested Structures

By default, the merge function does not perform a deep merge. Instead, it replaces the entire nested structure if there is a key overlap. If you need to perform a deep merge, where individual nested keys are merged rather than replaced, you will need to implement custom logic.

Custom Deep Merge Example:

To achieve a deep merge, you can use a combination of Terraform functions and custom logic. Here’s an example approach:

locals {
  base_config = {
    app = {
      name = "myApp"
      version = "1.0"
      settings = {
        theme = "light"
        mode = "standard"
      }
    }
    config = {
      port = 80
      protocols = ["http"]
    }
  }

  override_config = {
    app = {
      version = "2.0"
      settings = {
        mode = "advanced"
      }
    }
    config = {
      port = 8080
      protocols = ["https"]
    }
  }

  merged_app_settings = merge(local.base_config.app.settings, local.override_config.app.settings)
  merged_app = merge(local.base_config.app, local.override_config.app, { settings = local.merged_app_settings })
  merged_config = merge(local.base_config.config, local.override_config.config)

  final_merged_config = {
    app = local.merged_app
    config = local.merged_config
  }
}

output "final_merged_config" {
  value = local.final_merged_config
}

In this example:

  • We define base_config and override_config with nested structures.
  • We perform individual merges for deeply nested structures (app.settings).
  • We combine these intermediate results into the final merged structure.

The resulting final_merged_config will be:

{
  app = {
    name = "myApp"
    version = "2.0"
    settings = {
      theme = "light"
      mode = "advanced"
    }
  }
  config = {
    port = 8080
    protocols = ["https"]
  }
}

Here, the nested settings within app are merged individually, ensuring that only specific keys are overridden.

Practical Considerations

  1. Complexity Management:
    Deep merging increases the complexity of your Terraform configurations. Ensure that the added complexity is justified by the need for precise control over nested configurations.
  2. Documentation:
    Clearly document your merge logic, especially when handling nested structures. This helps other team members understand the intended configuration and reduces the risk of errors.
  3. Modularity:
    Consider breaking down complex nested structures into smaller, more manageable modules. This approach can simplify the merging logic and improve maintainability.

Example Modular Approach

# modules/app/main.tf
variable "base_settings" {
  type = map(string)
  default = {}
}

variable "override_settings" {
  type = map(string)
  default = {}
}

locals {
  settings = merge(var.base_settings, var.override_settings)
}

output "settings" {
  value = local.settings
}

# main configuration
module "app" {
  source = "./modules/app"
  base_settings = {
    theme = "light"
    mode = "standard"
  }
  override_settings = {
    mode = "advanced"
  }
}

output "final_settings" {
  value = module.app.settings
}

This modular approach allows you to handle specific parts of the configuration in isolated modules, simplifying the overall structure.

Handling nested maps in Terraform requires a good understanding of the merge function and careful planning to avoid unintended overrides. By leveraging custom logic for deep merges and adopting modular design principles, you can manage complex configurations effectively. Proper documentation and thoughtful structure are key to maintaining clarity and reducing the risk of errors in your Terraform configurations.

Using the Expansion Symbol (...)

The expansion symbol (...) in Terraform is a powerful feature that allows for more dynamic and flexible configurations. When used with functions like merge, it enables you to pass a variable number of arguments to the function, making it particularly useful when dealing with lists of maps or objects that need to be merged dynamically. This section explores how to effectively use the expansion symbol to manage complex configurations.

Basics of the Expansion Symbol

The expansion symbol is used to “expand” a list into individual arguments. This means that instead of passing a list as a single argument, the elements of the list are passed as separate arguments.

Consider a scenario where you have a list of maps that you want to merge into a single map. Using the expansion symbol, you can achieve this easily.

locals {
  list_of_maps = [
    { a = "alpha" },
    { b = "beta" },
    { c = "gamma" }
  ]

  merged_map = merge(local.list_of_maps...)
}

output "merged_map" {
  value = local.merged_map
}

In this example:

  • list_of_maps contains three maps.
  • The merge function, combined with the expansion symbol, merges these maps into a single map.

The resulting merged_map will be:

{
  a = "alpha"
  b = "beta"
  c = "gamma"
}

Dynamic Merging with Expansion Symbol

Using the expansion symbol allows you to handle dynamic and variable-length lists. This is particularly useful in scenarios where the number of elements to be merged is not known in advance or can change based on other inputs.

Here’s an example of Dynamic Merging Based on Variable Input:

variable "additional_maps" {
  description = "A list of additional maps to merge"
  type        = list(map(string))
  default     = []
}

locals {
  base_map = {
    a = "apple"
    b = "banana"
  }

  merged_map = merge(local.base_map, var.additional_maps...)
}

output "merged_map" {
  value = local.merged_map
}

In this setup:

  • base_map is a predefined map.
  • additional_maps is a variable that can accept a list of maps.
  • The merge function combines base_map with any additional maps provided through the variable, dynamically adjusting to the number of maps passed.

Handling Nested Structures with Expansion Symbol

When dealing with nested structures, the expansion symbol can be particularly helpful in ensuring that all elements are merged correctly without manually specifying each argument.

locals {
  nested_maps = [
    {
      app = {
        name = "app1"
        version = "1.0"
      }
    },
    {
      app = {
        version = "2.0"
        description = "Updated app"
      }
    }
  ]

  merged_nested_map = merge(local.nested_maps...)
}

output "merged_nested_map" {
  value = local.merged_nested_map
}

In this example:

  • nested_maps contains maps with nested structures.
  • The merge function, using the expansion symbol, combines these nested maps into a single map.

The resulting merged_nested_map will be:

{
  app = {
    name = "app1"
    version = "2.0"
    description = "Updated app"
  }
}

Practical Considerations

  1. Ensuring Key Uniqueness:
    When merging maps, ensure that keys are unique across all maps being merged to avoid unintended overrides. This is especially important when dynamically merging lists where the contents may vary.
  2. Debugging and Validation:
    Use Terraform’s output blocks to validate the merged results and ensure that the configuration behaves as expected. Debugging merged outputs can help catch errors early.
  3. Modularity and Reusability:
    Encapsulate complex merging logic within modules to promote reusability and maintainability. Modules can accept lists of maps as inputs and perform dynamic merges internally.

Example Module for Dynamic Merging

# modules/dynamic_merge/main.tf
variable "base_map" {
  type    = map(string)
  default = {}
}

variable "additional_maps" {
  type    = list(map(string))
  default = []
}

locals {
  merged_map = merge(var.base_map, var.additional_maps...)
}

output "merged_map" {
  value = local.merged_map
}

# Main configuration
module "dynamic_merge" {
  source          = "./modules/dynamic_merge"
  base_map        = { a = "apple", b = "banana" }
  additional_maps = [
    { c = "cherry" },
    { d = "date" }
  ]
}

output "final_merged_map" {
  value = module.dynamic_merge.merged_map
}

In this modular approach:

  • The dynamic_merge module accepts a base map and a list of additional maps.
  • It uses the expansion symbol to merge all maps dynamically.
  • The main configuration utilizes this module to perform the merge and outputs the final result.

The expansion symbol (...) in Terraform is a versatile tool for dynamically managing and merging lists of maps or objects. By understanding and leveraging this feature, you can create more flexible, maintainable, and dynamic infrastructure configurations. Whether you are dealing with static configurations or need to accommodate varying inputs, the expansion symbol combined with the merge function provides a robust solution for handling complex merging scenarios.

Practical Tips for Using the merge Function

Leveraging the merge function in Terraform can greatly enhance the flexibility and maintainability of your configurations. Here are some practical tips to help you effectively use this function:

Handling Conflicts

When working with the merge function, conflicts can arise if multiple maps contain the same key but different values. The way you handle these conflicts can significantly impact the outcome and maintainability of your configurations.

  1. Order of Precedence:
    The merge function resolves conflicts by prioritizing the value from the last map in the argument list. This means the order in which you pass the maps to the function matters. Always place the most specific or critical configurations last. Example:
   locals {
     default_config = {
       app     = "myApp"
       version = "1.0"
     }

     override_config = {
       version = "2.0"
     }

     final_config = merge(local.default_config, local.override_config)
   }

   output "final_config" {
     value = local.final_config
   }

In this example, version will be "2.0" because override_config is passed after default_config.

  1. Specific Maps for Overrides:
    Use dedicated maps for overrides to keep your configurations clear. This approach makes it easy to identify and manage overrides without accidentally modifying the base configurations. Example:
   locals {
     base_tags = {
       Environment = "Production"
       Team        = "DevOps"
     }

     override_tags = {
       Team = "QA"
     }

     tags = merge(local.base_tags, local.override_tags)
   }

   output "tags" {
     value = local.tags
   }

Here, Team will be "QA" because override_tags is intended to specifically override base_tags.

  1. Dynamic Overrides with Conditional Logic:
    Use conditional logic and variables to dynamically determine which configurations to apply. This technique allows for flexible and adaptive configurations based on different conditions. Example:
   variable "environment" {
     description = "The deployment environment"
     type        = string
   }

   locals {
     common_config = {
       app     = "myApp"
       version = "1.0"
     }

     env_config = {
       production = {
         version = "2.0"
       }
       development = {
         debug = true
       }
     }

     final_config = merge(local.common_config, lookup(local.env_config, var.environment, {}))
   }

   output "final_config" {
     value = local.final_config
   }

This setup dynamically merges environment-specific configurations based on the value of the environment variable.

  1. Avoiding Unintended Overrides:
    Prevent unintended overrides by clearly documenting the purpose of each map and the expected outcomes. Explicit documentation helps ensure that overrides are intentional and well-understood. Example:
   locals {
     // Base configuration applicable to all environments
     base_config = {
       app     = "myApp"
       version = "1.0"
     }

     // Production-specific overrides
     prod_overrides = {
       version = "2.0"
     }

     // Final configuration merging base and production-specific settings
     final_config = merge(local.base_config, local.prod_overrides)
   }

   output "final_config" {
     value = local.final_config
   }

By adding comments, you clarify the role of each map and the reason behind the merge.

Dynamic Merging

Dynamic merging allows for flexible configurations that adapt to different scenarios. This is particularly useful when dealing with user inputs or external data sources.

  1. Using the Expansion Symbol:
    The expansion symbol (...) enables you to pass a variable number of maps to the merge function, making your configurations more flexible. Example:
   locals {
     list_of_maps = [
       { a = "alpha" },
       { b = "beta" },
       { c = "gamma" }
     ]

     merged_map = merge(local.list_of_maps...)
   }

   output "merged_map" {
     value = local.merged_map
   }

This will produce:

   {
     a = "alpha"
     b = "beta"
     c = "gamma"
   }
  1. Combining Default and Environment-Specific Configurations:
    Combine default configurations with environment-specific overrides to maintain a consistent yet flexible setup across multiple environments. Example:
   locals {
     default_config = {
       app         = "myApp"
       environment = "production"
     }

     dev_config = {
       environment = "development"
       debug       = true
     }

     final_config = merge(local.default_config, local.dev_config)
   }

   output "final_config" {
     value = local.final_config
   }

Here, final_config will contain both default and development-specific settings.

Avoiding Common Pitfalls

  1. Type Consistency:
    Ensure that all maps have consistent types for their values. Mixing types can lead to errors that are difficult to debug. For example, avoid combining a map with string values with another map that has integer values for the same keys.
  2. Testing Configurations:
    Regularly test your merged configurations in different environments to ensure they behave as expected. This practice helps catch any issues early and ensures that your configurations are robust and reliable.
  3. Modularize Configurations:
    Break down your configurations into reusable modules, each with its own set of defaults and overrides. Modular configurations enhance maintainability and make it easier to manage complex setups. Example:
   module "base" {
     source = "./modules/base"
   }

   module "overrides" {
     source = "./modules/overrides"
   }

   locals {
     final_config = merge(module.base.config, module.overrides.config)
   }

   output "final_config" {
     value = local.final_config
   }

This approach modularizes the configuration, making it easier to manage and extend.

Combining Default and Environment-Specific Configurations

Managing infrastructure across multiple environments is a common challenge in DevOps. Each environment—be it development, staging, or production—often requires a unique set of configurations. However, many configuration settings remain consistent across environments, such as application names, base resource configurations, or network settings. The ability to merge these default configurations with environment-specific overrides ensures consistency while allowing for necessary customization.

Consider a scenario where you are deploying an application across multiple environments. The application name and some basic settings are the same in all environments, but each environment needs specific configurations for things like debugging options, instance sizes, or region-specific settings. Instead of maintaining separate, nearly identical configuration files for each environment, you can use the merge function to dynamically create the necessary configurations based on the environment.

The merge function’s ability to prioritize the last value for conflicting keys is particularly useful here. You can define a set of default values and then override or extend these defaults with environment-specific values. This approach not only streamlines the configuration management process but also makes it easier to introduce new environments or modify existing ones without extensive code changes.

locals {
  default_config = {
    app = "myApp"
    environment = "production"
  }

  dev_config = {
    environment = "development"
    debug = true
  }

  final_config = merge(local.default_config, local.dev_config)
}

output "final_config" {
  value = local.final_config
}

Here, final_config will be:

{
  app = "myApp"
  environment = "development"
  debug = true
}

Conclusion

The merge function in Terraform is a cornerstone for creating flexible, modular, and maintainable infrastructure as code. It allows for the seamless integration of various configuration sources, enabling you to craft precise and dynamic infrastructure setups. By mastering the merge function, you unlock the potential to streamline your configuration management and enhance the efficiency of your deployment processes.

The journey to mastering Terraform and its functions like merge is ongoing. Each project presents new challenges and opportunities to refine your skills. Embrace these challenges as learning experiences, and continue to build your expertise in crafting efficient, reliable, and scalable infrastructure as code.

In conclusion, the merge function is a testament to Terraform’s flexibility and power. By integrating it into your workflow, you not only streamline your configurations but also enhance your ability to respond to the dynamic needs of modern infrastructure.

Happy Terraforming!

Original Article Source: Using the Terraform ‘merge’ Function by Chris Pietschmann (If you’re reading this somewhere other than Build5Nines.com, it was republished without permission.)