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John Ajera
John Ajera

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Unlocking the Power of Terraform Loops: Patterns & Examples

#terraform #devops #loop #pattern

Mastering Terraform Loops with Examples

Terraform supports powerful loops for data transformation, resource creation, and simplifying configurations. Here’s a concise guide with sample inputs and outputs.

Table of Contents

  1. For Expression Loops
  2. Count Loops
  3. For_each Loops
  4. Dynamic Blocks
  5. Nested Loops
  6. Flattening Loops
  7. Conditional Loops
  8. Nested Object Processing
  9. Key Filtering (Map Transformation)
  10. Tuple Expansion (Zip Lists)
  11. Reverse Lookup (Key Search)
  12. Data Grouping (Grouping by Keys)
  13. Combining Lists with Conditional Filters
  14. Map Flattening (Nested Map Expansion)
  15. Filtering and Mapping (Conditional Map Processing)
  16. Index Looping (Manual Index Tracking)
  17. Combining Multiple Maps (Merge Maps)
  18. Counting Specific Values (Data Aggregation)
  19. Transform List to Map (Zipping)
  20. List Unpacking (Using Dynamic Values)
  21. List Expansion with Conditions
  22. Key-Value Reverse Lookup (Find by Value)
  23. List Reduction (Combining Data)
  24. Generating Sequential Values (Custom Index Range)
  25. Unique Value Extraction (Distinct)
  26. Filtering with Multiple Conditions
  27. Map with Custom Keys
  28. Nested Loops with Conditions
  29. Flattening Nested Maps
  30. Conditional Key Assignment
  31. Nested Maps with Dynamic Keys
  32. Data Aggregation by Groups
  33. Data Aggregation with Nested Loops

1. For Expression Loops

Transform lists or maps into new collections.

Example:

variable "nz_national_parks" { default = ["Tongariro", "Fiordland", "Abel Tasman"] } locals { park_messages = [for park in var.nz_national_parks : "${park} National Park is a must-visit in New Zealand."] } output "nz_park_messages" { value = local.park_messages }
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Output:

[ "Tongariro National Park is a must-visit in New Zealand.", "Fiordland National Park is a must-visit in New Zealand.", "Abel Tasman National Park is a must-visit in New Zealand." ]
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2. Count Loops

Create multiple instances of a resource using count.

variable "nz_cities" { default = ["Auckland", "Wellington", "Christchurch"] } locals { city_details = [ for i in range(length(var.nz_cities)) : { index = i name = var.nz_cities[i] } ] } output "created_cities" { value = local.city_details }
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Output:

[ { "index": 0, "name": "Auckland" }, { "index": 1, "name": "Wellington" }, { "index": 2, "name": "Christchurch" } ]
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3. For_each Loops

Create dynamic resources, maps, or sets.

Example:

variable "wellington_places" { default = { "Te Papa Museum" = "Museum of New Zealand" "Mount Victoria" = "Scenic Lookout" "Cuba Street" = "Shopping & Dining Hub" "Wellington Cable Car" = "Historic Transport" } } locals { famous_places = { for place, description in var.wellington_places : place => { name = place description = description } } } output "famous_places_in_wellington" { value = local.famous_places }
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Output:

{ "Te Papa Museum": { "name": "Te Papa Museum", "description": "Museum of New Zealand" }, "Mount Victoria": { "name": "Mount Victoria", "description": "Scenic Lookout" }, "Cuba Street": { "name": "Cuba Street", "description": "Shopping & Dining Hub" }, "Wellington Cable Car": { "name": "Wellington Cable Car", "description": "Historic Transport" } }
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4. Dynamic Blocks

Generate nested blocks inside resources.

Example:

variable "nz_volcanoes" { default = [ "Mount Ruapehu", "Mount Taranaki", "White Island" ] } locals { volcano_locations = { country = "New Zealand" volcanoes = [ for volcano in var.nz_volcanoes : { name = volcano location = "${volcano == "Mount Ruapehu" ? "Tongariro National Park" : volcano == "Mount Taranaki" ? "Egmont National Park" : "Bay of Plenty"}" } ] } } output "nz_volcano_locations" { value = local.volcano_locations }
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Output:

{ "country": "New Zealand", "volcanoes": [ { "name": "Mount Ruapehu", "location": "Tongariro National Park" }, { "name": "Mount Taranaki", "location": "Egmont National Park" }, { "name": "White Island", "location": "Bay of Plenty" } ] }
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5. Nested Loops

Create combinations or nested outputs.

Example:

variable "countries" { default = [ { name = "New Zealand", cities = ["Auckland", "Wellington"] }, { name = "Singapore", cities = ["Singapore City"] }, { name = "Philippines", cities = ["Manila", "Capiz"] } ] } locals { country_city_pairs = [ for country in var.countries : [for city in country.cities : "${country.name}: ${city}"] ] } output "country_city_pairs" { value = local.country_city_pairs }
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Output:

[ ["New Zealand: Auckland", "New Zealand: Wellington"], ["Singapore: Singapore City"], ["Philippines: Manila", "Philippines: Capiz"] ]
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6. Flattening Loops

Merge lists of lists into a single list.

Example:

variable "nz_regions" { default = [ ["Auckland", "Wellington"], ["Christchurch", "Queenstown"], ["Dunedin", "Hamilton"] ] } locals { flattened_regions = flatten(var.nz_regions) } output "flattened_nz_regions" { value = local.flattened_regions }
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Output:

[ "Auckland", "Wellington", "Christchurch", "Queenstown", "Dunedin", "Hamilton" ]
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7. Conditional Loops

Filter data with conditions.

Example:

variable "numbers" { default = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] } locals { even_numbers = [for num in var.numbers : num if num % 2 == 0] } output "even_numbers" { value = local.even_numbers }
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Output:

[ 2, 4, 6, 8, 10 ]
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8. Nested Object Processing

Process nested lists of New Zealand landmarks into structured outputs.

Example:

variable "nz_landmarks" { default = [ { region = "North Island" landmarks = ["Sky Tower", "Te Papa Museum"] }, { region = "South Island" landmarks = ["Milford Sound", "Mount Cook"] } ] } locals { nested_landmarks = [ for landmark_data in var.nz_landmarks : [ for landmark in landmark_data.landmarks : { region = landmark_data.region landmark = landmark } ] ] } output "nested_nz_landmarks" { value = local.nested_landmarks }
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Output:

[ [ { "region": "North Island", "landmark": "Sky Tower" }, { "region": "North Island", "landmark": "Te Papa Museum" } ], [ { "region": "South Island", "landmark": "Milford Sound" }, { "region": "South Island", "landmark": "Mount Cook" } ] ]
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9. Key Filtering (Map Transformation)

Filter maps based on specific keys.

Example:

variable "nz_heritage_sites" { default = { "Waitangi Treaty Grounds" = "Historic" "Tongariro National Park" = "Natural" "Old Government Buildings" = "Architectural" "Milford Sound" = "Natural" } } locals { natural_sites = { for site, type in var.nz_heritage_sites : site => type if type == "Natural" } } output "filtered_heritage_sites" { value = local.natural_sites }
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Output:

{ "Tongariro National Park": "Natural", "Milford Sound": "Natural" }
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10. Tuple Expansion (Zip Lists)

Combine two lists into a structured output.

Example:

variable "nz_fruits" { default = ["Kiwi", "Feijoa", "Tamarillo"] } variable "nz_fruit_colors" { default = ["Green", "Brown", "Red"] } locals { fruit_details = zipmap(var.nz_fruits, var.nz_fruit_colors) } output "fruit_color_map" { value = local.fruit_details }
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Output:

{ "Kiwi": "Green", "Feijoa": "Brown", "Tamarillo": "Red" }
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11. Reverse Lookup (Key Search)

Find a key in a map based on its value.

Example:

variable "nz_wonders" { default = { "Mount Cook" = "Highest Mountain" "Milford Sound" = "Fjord" "Franz Josef Glacier" = "Glacier" } } locals { highest_mountain = tomap(var.nz_wonders) wonder_found = [for key, value in local.highest_mountain : key if value == "Highest Mountain"] } output "nz_highest_mountain" { value = local.wonder_found[0] }
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Output:

"Mount Cook"
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12. Data Grouping (Grouping by Keys)

Group data into categorized lists.

Example:

variable "nz_animals" { default = { "Kakapo" = "Bird" "Kiwi" = "Bird" "Weta" = "Insect" "Tuataras" = "Reptile" "Tuatara" = "Reptile" } } locals { # Correctly group animals by their type animal_groups = { for type in distinct(values(var.nz_animals)) : type => [ for key, value in var.nz_animals : key if value == type ] } } output "grouped_animals" { value = local.animal_groups }
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Output:

{ "Bird": ["Kakapo", "Kiwi"], "Insect": ["Weta"], "Reptile": ["Tuataras", "Tuatara"] }
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13. Combining Lists with Conditional Filters

Conditionally filter and combine two lists into one.

Example:

variable "nz_scenic_spots" { default = ["Mount Cook", "Milford Sound", "Abel Tasman"] } variable "popular_spots" { default = ["Milford Sound", "Sky Tower"] } locals { combined_spots = [ for spot in concat(var.nz_scenic_spots, var.popular_spots) : spot if !contains(var.nz_scenic_spots, spot) || !contains(var.popular_spots, spot) ] } output "unique_spots" { value = local.combined_spots }
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Output:

[ "Mount Cook", "Abel Tasman", "Sky Tower" ]
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14. Map Flattening (Nested Map Expansion)

Expand a nested map into a list of key-value pairs.

Example:

variable "nested_map" { default = { "New Zealand" = { "City" = "Wellington" "Region" = "North Island" } "Australia" = { "City" = "Sydney" "Region" = "New South Wales" } } } locals { flattened_map = [ for country, details in var.nested_map : { country = country city = details["City"] region = details["Region"] } ] } output "flattened_map" { value = local.flattened_map }
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Output:

flattened_map = [ { "city" = "Sydney" "country" = "Australia" "region" = "New South Wales" }, { "city" = "Wellington" "country" = "New Zealand" "region" = "North Island" }, ]
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15. Filtering and Mapping (Conditional Map Processing)

Filter and modify a map's values based on a condition.

Example:

variable "city_populations" { default = { "Auckland" = 1500000 "Wellington" = 500000 "Dunedin" = 100000 "Hamilton" = 200000 } } locals { large_cities = { for city, population in var.city_populations : city => population if population > 400000 } } output "large_cities" { value = local.large_cities }
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Output:

large_cities = { "Auckland" = 1500000 "Wellington" = 500000 }
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16. Index Looping (Manual Index Tracking)

Track list indices without using built-in Terraform functions.

Example:

variable "nz_beaches" { default = ["Piha", "Cathedral Cove", "Hot Water Beach"] } locals { indexed_beaches = [ for idx in range(length(var.nz_beaches)) : { index = idx beach = var.nz_beaches[idx] } ] } output "indexed_beaches" { value = local.indexed_beaches }
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Output:

indexed_beaches = [ { "beach" = "Piha" "index" = 0 }, { "beach" = "Cathedral Cove" "index" = 1 }, { "beach" = "Hot Water Beach" "index" = 2 }, ]
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17. Combining Multiple Maps (Merge Maps)

Merge multiple maps into a single map.

Example:

variable "map_one" { default = { "Auckland" = "North Island" "Wellington" = "North Island" } } variable "map_two" { default = { "Christchurch" = "South Island" "Dunedin" = "South Island" } } locals { merged_maps = merge(var.map_one, var.map_two) } output "merged_maps" { value = local.merged_maps }
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Output:

merged_maps = { "Auckland" = "North Island" "Christchurch" = "South Island" "Dunedin" = "South Island" "Wellington" = "North Island" }
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18. Counting Specific Values (Data Aggregation)

Count specific occurrences within a list.

Example:

variable "nz_islands" { default = ["North Island", "South Island", "North Island", "South Island", "North Island"] } locals { island_counts = { "North Island" = length([for i in var.nz_islands : i if i == "North Island"]) "South Island" = length([for i in var.nz_islands : i if i == "South Island"]) } } output "island_counts" { value = local.island_counts }
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Output:

island_counts = { "North Island" = 3 "South Island" = 2 }
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19. Transform List to Map (Zipping)

Convert two lists into a single map.

Example:

variable "nz_cities" { default = ["Auckland", "Wellington", "Christchurch"] } variable "nz_regions" { default = ["North Island", "North Island", "South Island"] } locals { city_region_map = zipmap(var.nz_cities, var.nz_regions) } output "city_region_map" { value = local.city_region_map }
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Output:

city_region_map = { "Auckland" = "North Island" "Christchurch" = "South Island" "Wellington" = "North Island" }
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20. List Unpacking (Using Dynamic Values)

Unpack values from a list using index references.

Example:

variable "nz_lakes" { default = ["Lake Taupo", "Lake Wanaka", "Lake Tekapo"] } locals { first_lake = var.nz_lakes[0] second_lake = var.nz_lakes[1] third_lake = var.nz_lakes[2] } output "unpacked_lakes" { value = { "First" = local.first_lake "Second" = local.second_lake "Third" = local.third_lake } }
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Output:

unpacked_lakes = { "First" = "Lake Taupo" "Second" = "Lake Wanaka" "Third" = "Lake Tekapo" }
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21. List Expansion with Conditions

Expand lists conditionally.

Example:

variable "nz_hiking_tracks" { default = ["Routeburn", "Milford", "Abel Tasman"] } locals { expanded_tracks = [ for track in var.nz_hiking_tracks : { name = track length = "${track == "Milford" ? "53km" : "Unknown"}" } ] } output "expanded_tracks" { value = local.expanded_tracks }
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Output:

expanded_tracks = [ { "length" = "Unknown" "name" = "Routeburn" }, { "length" = "53km" "name" = "Milford" }, { "length" = "Unknown" "name" = "Abel Tasman" }, ]
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22. Key-Value Reverse Lookup (Find by Value)

Find a key using a map’s value.

Example:

variable "nz_capitals" { default = { "Wellington" = "New Zealand" "Canberra" = "Australia" } } locals { country_lookup = [for city, country in var.nz_capitals : city if country == "New Zealand"] } output "nz_capital" { value = local.country_lookup[0] }
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Output:

nz_capital = "Wellington"
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23. List Reduction (Combining Data)

Find a key using a map’s value.

Example:

variable "nz_mountains" { default = ["Mount Cook", "Mount Ruapehu", "Mount Taranaki"] } locals { mountain_list = join(", ", var.nz_mountains) } output "combined_mountains" { value = local.mountain_list }
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Output:

combined_mountains = "Mount Cook, Mount Ruapehu, Mount Taranaki"
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24. Generating Sequential Values (Custom Index Range)

Create a list of sequential values with a custom range.

Example:

variable "start_index" { default = 5 } variable "end_index" { default = 10 } locals { index_list = [for idx in range(var.start_index, var.end_index) : idx] } output "generated_indices" { value = local.index_list }
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Output:

generated_indices = [ 5, 6, 7, 8, 9, ]
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25. Unique Value Extraction (Distinct)

Remove duplicates from a list.

Example:

variable "nz_fruits" { default = ["Kiwi", "Feijoa", "Kiwi", "Tamarillo", "Feijoa"] } locals { unique_fruits = distinct(var.nz_fruits) } output "distinct_fruits" { value = local.unique_fruits }
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Output:

distinct_fruits = tolist([ "Kiwi", "Feijoa", "Tamarillo", ])
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26. Filtering with Multiple Conditions

Filter a list based on multiple conditions.

Example:

variable "nz_lakes" { default = ["Lake Taupo", "Lake Tekapo", "Lake Wanaka", "Lake Rotoiti"] } locals { filtered_lakes = [for lake in var.nz_lakes : lake if lake != "Lake Tekapo" && lake != "Lake Rotoiti"] } output "filtered_lakes" { value = local.filtered_lakes }
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Output:

filtered_lakes = [ "Lake Taupo", "Lake Wanaka", ]
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27. Map with Custom Keys

Create a custom map with formatted keys.

Example:

variable "nz_islands" { default = ["North Island", "South Island"] } locals { island_map = { for idx, island in var.nz_islands : "Island_${idx}" => island } } output "formatted_island_map" { value = local.island_map }
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Output:

formatted_island_map = { "Island_0" = "North Island" "Island_1" = "South Island" }
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28. Nested Loops with Conditions

Create nested combinations with a filtering condition.

Example:

variable "countries" { default = ["New Zealand", "Australia"] } variable "cities" { default = ["Auckland", "Sydney", "Wellington"] } locals { country_city_pairs = [ for country in var.countries : [ for city in var.cities : "${country}-${city}" if city != "Sydney" ] ] } output "country_city_combinations" { value = local.country_city_pairs }
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Output:

country_city_combinations = [ [ "New Zealand-Auckland", "New Zealand-Wellington", ], [ "Australia-Auckland", "Australia-Wellington", ], ]
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29. Flattening Nested Maps

Flatten a nested map structure into key-value pairs.

Example:

variable "country_details" { default = { "New Zealand" = { "Capital" = "Wellington" "Largest City" = "Auckland" } "Australia" = { "Capital" = "Canberra" "Largest City" = "Sydney" } } } locals { flat_country_details = [ for country, details in var.country_details : { country = country capital = details["Capital"] largest_city = details["Largest City"] } ] } output "flattened_country_details" { value = local.flat_country_details }
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Output:

flattened_country_details = [ { "capital" = "Canberra" "country" = "Australia" "largest_city" = "Sydney" }, { "capital" = "Wellington" "country" = "New Zealand" "largest_city" = "Auckland" }, ]
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30. Conditional Key Assignment

Assign keys in a map conditionally.

Example:

variable "nz_regions" { default = ["Northland", "Canterbury", "Otago"] } locals { region_assignments = { for region in var.nz_regions : region => "${region == "Canterbury" ? "South Island" : "Other Region"}" } } output "conditional_region_map" { value = local.region_assignments }
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Output:

conditional_region_map = { "Canterbury" = "South Island" "Northland" = "Other Region" "Otago" = "Other Region" }
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31. Nested Maps with Dynamic Keys

Create dynamic keys inside a map.

Example:

variable "city_data" { default = { "Auckland" = "North Island" "Wellington" = "North Island" "Christchurch" = "South Island" } } locals { dynamic_city_map = { for city, island in var.city_data : "City_${city}" => { name = city island = island } } } output "dynamic_city_map" { value = local.dynamic_city_map }
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Output:

dynamic_city_map = { "City_Auckland" = { "island" = "North Island" "name" = "Auckland" } "City_Christchurch" = { "island" = "South Island" "name" = "Christchurch" } "City_Wellington" = { "island" = "North Island" "name" = "Wellington" } }
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32. Data Aggregation by Groups

Group elements into lists based on a common key.

Example:

variable "nz_landmarks" { default = { "Sky Tower" = "Auckland" "Te Papa" = "Wellington" "Milford Sound" = "Fiordland" "Mount Cook" = "Canterbury" } } locals { landmark_groups = { for location in distinct(values(var.nz_landmarks)) : location => [for landmark, place in var.nz_landmarks : landmark if place == location] } } output "grouped_landmarks" { value = local.landmark_groups }
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Output:

grouped_landmarks = { "Auckland" = [ "Sky Tower", ] "Canterbury" = [ "Mount Cook", ] "Fiordland" = [ "Milford Sound", ] "Wellington" = [ "Te Papa", ] }
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33. Data Aggregation with Nested Loops

Aggregate items using nested loops for complex data structures.

Example:

variable "nz_fish_species" { default = { "Trout" = { habitats = [ "Lake Taupo", "Waikato River", ] }, "Snapper" = { habitats = [ "Hauraki Gulf", "Bay of Islands", ] } } } locals { fish_habitats = flatten([ for fish, details in var.nz_fish_species : [ for habitat in details.habitats : { species = fish habitat = habitat } ] ]) } output "grouped_fish_habitats" { value = local.fish_habitats }
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Output:

grouped_fish_habitats = [ { "habitat" = "Hauraki Gulf" "species" = "Snapper" }, { "habitat" = "Bay of Islands" "species" = "Snapper" }, { "habitat" = "Lake Taupo" "species" = "Trout" }, { "habitat" = "Waikato River" "species" = "Trout" }, ]
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Conclusion

These examples showcase various Terraform loop patterns, highlighting dynamic map creation, list manipulation, conditional logic, and data aggregation.

Let me know if you'd like additional patterns! 🚀

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