CircleCI Code deploy orb cannot find file located in S3 bucket? - amazon-web-services

I am implementing a Blue/Green deployment using aws-code-deploy orb. My infrastructure is being implemented using terraform which consists of the following resources.
S3 bucket → stores the appspec.yml which is used to create the deployment.
VPC for networking ( It was easier to spin mine up for this demo. Too lazy to navigate the Legitscript networking lol )
An application Load balancer, 2 Listener Groups and 2 Target Groups. On initial deployment of infrastructure, go to EC2 → Target groups and you will see TG1 will have a healthy target associated with it but TG2 will not. It will change once we implement the Blue green deployment.
ECS → A cluster, service and task definition will be available.
CodeDeploy → CodeDeploy application and deployment group.
This is my terraform file for S3 resource :-
resource "aws_s3_bucket" "bucket" {
bucket = "blue-green-cd-ls"
}
resource "aws_s3_object" "appspec" {
bucket = aws_s3_bucket.bucket.id
key = "appspec.yaml"
content = templatefile("${path.module}/appspec.yaml.tpl", {
task_definition_arn = var.task_definition_arn
})
}
Which successfuly creates the S3 bucket with the appspec.yml file in it. I am trying to create a deployment using CircleCI and my config.yml looks like this :-
version: 2.1
orbs:
aws-cli: circleci/aws-cli#3.1.3
aws-code-deploy: circleci/aws-code-deploy#2.0.0
jobs:
deploy:
executor: aws-cli/default
steps:
- checkout
- aws-cli/setup
- aws-code-deploy/deploy-bundle:
application-name: "blue-green"
bundle-bucket: "blue-green-cd-ls"
bundle-key: "appspec.yaml"
deployment-group: "blue-green-ls"
bundle-type: "YAML"
deployment-config: "CodeDeployDefault.ECSAllAtOnce"
workflows:
build-and-deploy:
jobs:
- deploy
But my deployment keeps on failing with the following error :-
Deployment failed!
{
"deploymentInfo": {
"applicationName": "blue-green",
"deploymentGroupName": "*************",
"deploymentConfigName": "CodeDeployDefault.ECSAllAtOnce",
"deploymentId": "d-85LKXCPMJ",
"revision": {
"revisionType": "S3",
"s3Location": {
"bucket": "blue-green-cd-ls",
"key": "appspec.yaml.YAML",
"bundleType": "YAML"
}
},
"status": "Failed",
"errorInformation": {
"code": "INVALID_REVISION",
"message": "The AppSpec file cannot be located in the specified S3 bucket. Verify your AppSpec file is present and that the name and key value pair specified for your S3 bucket are correct. The S3 bucket must be in your current region"
I double checked and the S3 bucket is definitely in the right region i.e. us-east-1. Anyone has any ideas what might be wrong? Thank you.

Related

Bucket query permission denied in GCP despite service-account having the Owner role

I am trying to make a GCP VM through Terraform. I made a service account on Google that has the Project Owner role. Through Terraform I am trying to make a bucket to store Terraform's state. The .json for credentials is in a Gitlab variable.
Problem is that despite the service-account having Owner role, I get a 403 error saying that my service-account does not have access and is forbidden.
Things I've tried:
I've given the service-account different roles including Project Editor, Storage Admin, and Storage Object Admin.
I've deleted it and remade it (and updated the Gitlab variable).
I've made the bucket on google through the UI instead of Terraform incase that was the problem, but didn't change anything.
Gitlab's yml:
image:
name: hashicorp/terraform:light
entrypoint:
- '/usr/bin/env'
- 'PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin'
before_script:
- rm -rf .terraform
- terraform --version
- mkdir -p ./creds
- echo $SERVICEACCOUNT | base64 -d > ./creds/serviceaccount.json
- terraform init
stages:
- validate
- plan
- apply
validate:
stage: validate
script:
- terraform validate
plan:
stage: plan
script:
- terraform plan -out "planfile"
dependencies:
- validate
artifacts:
paths:
- planfile
apply:
stage: apply
script:
- terraform apply -input=false "planfile"
dependencies:
- plan
when: manual
My main.tf:
provider "google" {
project = "project-id-name"
credentials = "./creds/serviceaccount.json"
region = "europe-west1"
}
# make bucket to store terraform state into
resource "google_storage_bucket" "terraform_state" {
name = "terraform-up-and-running-state"
region = "europe-west1"
}
# config terraform to store onto cloud in bucket above
terraform {
backend "gcs" {
bucket = "terraform-up-and-running-state"
credentials = "./creds/serviceaccount.json"
}
}
# rest
resource "google_compute_instance" "vm_instance" {
name = "my-test-vm"
machine_type = "f1-micro"
boot_disk {
initialize_params {
image = "debian-cloud/debian-9"
}
}
network_interface {
# A default network is created for all GCP projects
network = "${google_compute_network.vpc_network.self_link}"
access_config {
}
}
}
resource "google_compute_network" "vpc_network" {
name = "my-test-network"
auto_create_subnetworks = "true"
}
Goal is to initialize a Google VM and everything I need for it through solely Terraform.
This is what Gitlab's validate phase shows:
Running with gitlab-runner 12.3.0 (a8a019e0)
on docker-auto-scale 72989761
Using Docker executor with image hashicorp/terraform:light ...
Pulling docker image hashicorp/terraform:light ...
Using docker image sha256:e42a20110eb49783e5f0e1594c67c8d45663fbf84303c395540b8dc94558d448 for hashicorp/terraform:light ...
Running on runner-72989761-project-14591382-concurrent-0 via runner-72989761-srm-1570020185-504ac9cf...
Fetching changes with git depth set to 50...
Initialized empty Git repository in /builds/my-project/playground-webscraper/.git/
Created fresh repository.
From https://gitlab.com/my-project/playground-webscraper
* [new branch] master -> origin/master
Checking out c183697f as master...
Skipping Git submodules setup
$ rm -rf .terraform
$ terraform --version
Terraform v0.12.9
$ mkdir -p ./creds
$ echo $SERVICEACCOUNT | base64 -d > ./creds/serviceaccount.json
$ terraform init
Initializing the backend...
Successfully configured the backend "gcs"! Terraform will automatically
use this backend unless the backend configuration changes.
Error: Failed to get existing workspaces: querying Cloud Storage failed: googleapi: Error 403: terraform#kims-playground-webscraper.iam.gserviceaccount.com does not have storage.objects.list access to terraform-up-and-running-state., forbidden
ERROR: Job failed: exit code 1
The Google Cloud Storage Bucket namespace is global, and terraform-up-and-running-state is already used by another bucket somewhere in the world, and you are trying to access their bucket and getting denied. It looks like there are a number of tutorials on the web that make reference to this bucket name. Make sure your bucket name is unique.
I'm guessing this is not your bucket: http://terraform-up-and-running-state.storage.googleapis.com/
See:
https://cloud.google.com/storage/docs/best-practices#naming
https://cloud.google.com/storage/docs/naming#requirements

Terraform init fails for remote backend S3 when creating the state bucket

I was trying to create a remote backend for my S3 bucket.
provider "aws" {
version = "1.36.0"
profile = "tasdik"
region = "ap-south-1"
}
terraform {
backend "s3" {
bucket = "ops-bucket"
key = "aws/ap-south-1/homelab/s3/terraform.tfstate"
region = "ap-south-1"
}
}
resource "aws_s3_bucket" "ops-bucket" {
bucket = "ops-bucket"
acl = "private"
versioning {
enabled = true
}
lifecycle {
prevent_destroy = true
}
tags {
Name = "ops-bucket"
Environmet = "devel"
}
}
I haven't applied anything yet, the bucket is not present as of now. So, terraform asks me to do an init. But when I try to do so, I get a
$ terraform init
Initializing the backend...
Successfully configured the backend "s3"! Terraform will automatically
use this backend unless the backend configuration changes.
Error loading state: BucketRegionError: incorrect region, the bucket is not in 'ap-south-1' region
status code: 301, request id: , host id:
Terraform will initialise any state configuration before any other actions such as a plan or apply. Thus you can't have the creation of the S3 bucket for your state to be stored in be defined at the same time as you defining the state backend.
Terraform also won't create an S3 bucket for you to put your state in, you must create this ahead of time.
You can either do this outside of Terraform such as with the AWS CLI:
aws s3api create-bucket --bucket "${BUCKET_NAME}" --region "${BUCKET_REGION}" \
--create-bucket-configuration LocationConstraint="${BUCKET_REGION}"
or you could create it via Terraform as you are trying to do so but use local state for creating the bucket on the first apply and then add the state configuration and re-init to get Terraform to migrate the state to your new S3 bucket.
As for the error message, S3 bucket names are globally unique across all regions and all AWS accounts. The error message is telling you that it ran the GetBucketLocation call but couldn't find a bucket in ap-south-1. When creating your buckets I recommend making sure they are likely to be unique by doing something such as concatenating the account ID and possibly the region name into the bucket name.

Initial setup of terraform backend using terraform

I'm just getting started with terraform and I'd like to be able to use AWS S3 as my backend for storing the state of my projects.
terraform {
backend "s3" {
bucket = "tfstate"
key = "app-state"
region = "us-east-1"
}
}
I feel like it is sensible to setup my S3 bucket, IAM groups and polices for the backend storage infrastructure with terraform as well.
If I setup my backend state before I apply my initial terraform infrastructure, it reasonably complains that the backend bucket is not yet created. So, my question becomes, how do I setup my terraform backend with terraform, while keeping my state for the backend tracked by terraform. Seems like a nested dolls problem.
I have some thoughts about how to script around this, for example, checking to see if the bucket exists or some state has been set, then bootstrapping terraform and finally copying the terraform tfstate up to s3 from the local file system after the first run. But before going down this laborious path, I thought I'd make sure I wasn't missing something obvious.
To set this up using terraform remote state, I usually have a separate folder called remote-state within my dev and prod terraform folder.
The following main.tf file will set up your remote state for what you posted:
provider "aws" {
region = "us-east-1"
}
resource "aws_s3_bucket" "terraform_state" {
bucket = "tfstate"
lifecycle {
prevent_destroy = true
}
}
resource "aws_s3_bucket_versioning" "terraform_state" {
bucket = aws_s3_bucket.terraform_state.id
versioning_configuration {
status = "Enabled"
}
}
resource "aws_dynamodb_table" "terraform_state_lock" {
name = "app-state"
read_capacity = 1
write_capacity = 1
hash_key = "LockID"
attribute {
name = "LockID"
type = "S"
}
}
Then get into this folder using cd remote-state, and run terraform init && terraform apply - this should only need to be run once. You might add something to bucket and dynamodb table name to separate your different environments.
Building on the great contribution from Austin Davis, here is a variation that I use which includes a requirement for data encryption:
provider "aws" {
region = "us-east-1"
}
resource "aws_s3_bucket" "terraform_state" {
bucket = "tfstate"
versioning {
enabled = true
}
lifecycle {
prevent_destroy = true
}
}
resource "aws_dynamodb_table" "terraform_state_lock" {
name = "app-state"
read_capacity = 1
write_capacity = 1
hash_key = "LockID"
attribute {
name = "LockID"
type = "S"
}
}
resource "aws_s3_bucket_policy" "terraform_state" {
bucket = "${aws_s3_bucket.terraform_state.id}"
policy =<<EOF
{
"Version": "2012-10-17",
"Id": "RequireEncryption",
"Statement": [
{
"Sid": "RequireEncryptedTransport",
"Effect": "Deny",
"Action": ["s3:*"],
"Resource": ["arn:aws:s3:::${aws_s3_bucket.terraform_state.bucket}/*"],
"Condition": {
"Bool": {
"aws:SecureTransport": "false"
}
},
"Principal": "*"
},
{
"Sid": "RequireEncryptedStorage",
"Effect": "Deny",
"Action": ["s3:PutObject"],
"Resource": ["arn:aws:s3:::${aws_s3_bucket.terraform_state.bucket}/*"],
"Condition": {
"StringNotEquals": {
"s3:x-amz-server-side-encryption": "AES256"
}
},
"Principal": "*"
}
]
}
EOF
}
As you've discovered, you can't use terraform to build the components terraform needs in the first place.
While I understand the inclination to have terraform "track everything", it is very difficult, and more headache than it's worth.
I generally handle this situation by creating a simple bootstrap shell script. It creates things like:
The s3 bucket for state storage
Adds versioning to said bucket
a terraform IAM user and group with certain policies I'll need for terraform builds
While you should only need to run this once (technically), I find that when I'm developing a new system, I spin up and tear things down repeatedly. So having those steps in one script makes that a lot simpler.
I generally build the script to be idempotent. This way, you can run it multiple times without concern that you're creating duplicate buckets, users, etc
I created a terraform module with a few bootstrap commands/instructions to solve this:
https://github.com/samstav/terraform-aws-backend
There are detailed instructions in the README, but the gist is:
# conf.tf
module "backend" {
source = "github.com/samstav/terraform-aws-backend"
backend_bucket = "terraform-state-bucket"
}
Then, in your shell (make sure you haven't written your terraform {} block yet):
terraform get -update
terraform init -backend=false
terraform plan -out=backend.plan -target=module.backend
terraform apply backend.plan
Now write your terraform {} block:
# conf.tf
terraform {
backend "s3" {
bucket = "terraform-state-bucket"
key = "states/terraform.tfstate"
dynamodb_table = "terraform-lock"
}
}
And then you can re-init:
terraform init -reconfigure
What I usually do is start without remote backend for creating initial infrastructure as you said , S3 , IAM roles and other essential stuff. Once I have that I just add backend configuration and run terraform init to migrate to S3.
It's not the best case but in most cases I don't rebuild my entire environment everyday so this semi automated approach is good enough.
I also separate next "layers" (VPC, Subnets, IGW, NAT ,etc) of infrastructure to different states.
Setting up a Terraform backend leveraging an AWS s3 bucket is relatively easy.
First, create a bucket in the region of your choice (eu-west-1 for the example), named terraform-backend-store (remember to choose a unique name.)
To do so, open your terminal and run the following command, assuming that you have properly set up the AWS CLI (otherwise, follow the instructions at the official documentation):
aws s3api create-bucket --bucket terraform-backend-store \
--region eu-west-1 \
--create-bucket-configuration \
LocationConstraint=eu-west-1
# Output:
{
"Location": "http://terraform-backend-store.s3.amazonaws.com/"
}
The command should be self-explanatory; to learn more check the documentation here.
Once the bucket is in place, it needs a proper configuration for security and reliability.
For a bucket that holds the Terraform state, it’s common-sense enabling the server-side encryption. Keeping it simple, try first AES256 method (although I recommend to use KMS and implement a proper key rotation):
aws s3api put-bucket-encryption \
--bucket terraform-backend-store \
--server-side-encryption-configuration={\"Rules\":[{\"ApplyServerSideEncryptionByDefault\":{\"SSEAlgorithm\":\"AES256\"}}]}
# Output: expect none when the command is executed successfully
Next, it’s crucial restricting the access to the bucket; create an unprivileged IAM user as follows:
aws iam create-user --user-name terraform-deployer
# Output:
{
"User": {
"UserName": "terraform-deployer",
"Path": "/",
"CreateDate": "2019-01-27T03:20:41.270Z",
"UserId": "AIDAIOSFODNN7EXAMPLE",
"Arn": "arn:aws:iam::123456789012:user/terraform-deployer"
}
}
Take note of the Arn from the command’s output (it looks like: “Arn”: “arn:aws:iam::123456789012:user/terraform-deployer”).
To correctly interact with the s3 service and DynamoDB at a later stage to implement the locking, our IAM user must hold a sufficient set of permissions.
It is recommended to have severe restrictions in place for production environments, though, for the sake of simplicity, start assigning AmazonS3FullAccess and AmazonDynamoDBFullAccess:
aws iam attach-user-policy --policy-arn arn:aws:iam::aws:policy/AmazonS3FullAccess --user-name terraform-deployer
# Output: expect none when the command execution is successful
aws iam attach-user-policy --policy-arn arn:aws:iam::aws:policy/AmazonDynamoDBFullAccess --user-name terraform-deployer
# Output: expect none when the command execution is successful
The freshly created IAM user must be enabled to execute the required actions against your s3 bucket. You can do this by creating and applying the right policy, as follows:
cat <<-EOF >> policy.json
{
"Statement": [
{
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam::123456789012:user/terraform-deployer"
},
"Action": "s3:*",
"Resource": "arn:aws:s3:::terraform-remote-store"
}
]
}
EOF
This basic policy file grants the principal with arn “arn:aws:iam::123456789012:user/terraform-deployer”, to execute all the available actions (“Action”: “s3:*") against the bucket with arn “arn:aws:s3:::terraform-remote-store”.
Again, in production is desired to force way stricter policies. For reference, have a look at the AWS Policy Generator.
Back to the terminal and run the command as shown below, to enforce the policy in your bucket:
aws s3api put-bucket-policy --bucket terraform-remote-store --policy file://policy.json
# Output: none
As the last step, enable the bucket’s versioning:
aws s3api put-bucket-versioning --bucket terraform-remote-store --versioning-configuration Status=Enabled
It allows saving different versions of the infrastructure’s state and rollback easily to a previous stage without struggling.
The AWS s3 bucket is ready, time to integrate it with Terraform. Listed below, is the minimal configuration required to set up this remote backend:
# terraform.tf
provider "aws" {
region = "${var.aws_region}"
shared_credentials_file = "~/.aws/credentials"
profile = "default"
}
terraform {
backend "s3" {
bucket = "terraform-remote-store"
encrypt = true
key = "terraform.tfstate"
region = "eu-west-1"
}
}
# the rest of your configuration and resources to deploy
Once in place, terraform must be initialized (again).
terraform init
The remote backend is ready for a ride, test it.
What about locking?
Storing the state remotely brings a pitfall, especially when working in scenarios where several tasks, jobs, and team members have access to it. Under these circumstances, the risk of multiple concurrent attempts to make changes to the state is high. Here comes to help the lock, a feature that prevents opening the state file while already in use.
You can implement the lock creating an AWS DynamoDB Table, used by terraform to set and unset the locks.
Provision the resource using terraform itself:
# create-dynamodb-lock-table.tf
resource "aws_dynamodb_table" "dynamodb-terraform-state-lock" {
name = "terraform-state-lock-dynamo"
hash_key = "LockID"
read_capacity = 20
write_capacity = 20
attribute {
name = "LockID"
type = "S"
}
tags {
Name = "DynamoDB Terraform State Lock Table"
}
}
and deploy it as shown:
terraform plan -out "planfile" && terraform apply -input=false -auto-approve "planfile"
Once the command execution is completed, the locking mechanism must be added to your backend configuration as follow:
# terraform.tf
provider "aws" {
region = "${var.aws_region}"
shared_credentials_file = "~/.aws/credentials"
profile = "default"
}
terraform {
backend "s3" {
bucket = "terraform-remote-store"
encrypt = true
key = "terraform.tfstate"
region = "eu-west-1"
dynamodb_table = "terraform-state-lock-dynamo"
}
}
# the rest of your configuration and resources to deploy
All done. Remember to run again terraform init and enjoy your remote backend.
What I have been doing to address this is that, You can comment out the "backend" block for the initial run, and do a selected terraform apply on only the state bucket and any related resources(like bucket policies).
# backend "s3" {
# bucket = "foo-bar-state-bucket"
# key = "core-terraform.tfstate"
# region = "eu-west-1"
# }
#}
provider "aws" {
region = "eu-west-1"
profile = "terraform-iam-user"
shared_credentials_file = "~/.aws/credentials"
}
terraform apply --target aws_s3_bucket.foobar-terraform --target aws_s3_bucket_policy.foobar-terraform
This will provision your s3 state bucket, and will store .tfstate file locally in your working directory.
Later, Uncomment the "backend" block and reconfigure the backend terraform init --reconfigure
, which will prompt you to copy your locally present .tfstate file, (tracking state of your backend s3 bucket) to the remote backend which is now available to be used by terraform for any subsequent runs.
Prompt for copying exisitng state to remote backend
There are some great answers here & I'd like to offer an alternative to managing your back end state;
Set up a Terraform Cloud Account (it's free for up to 5 users).
Create a workspace for your organization (Version control workflow is typical)
Select your VCS such as github or bitbucket (where you store your terraform plans and modules)
Terraform Cloud will give you the instructions needed for your new OAuth Connection
Once that's setup you'll have the option to set up an SSH keypair which is typically not needed & you can click the Skip & Finish button
Once your terraform cloud account is set up & connected to your VCS repos where you store your terraform plans & modules...
Add your terraform module repos in terraform cloud, by clicking on the Registry tab. You will need to ensure that your terraform modules are versioned / tagged & follow proper naming convention. If you have a terraform module that creates a load balancer in AWS, you would name the terraform module repository (in github for example), like this: terraform-aws-loadbalancer. As long as it starts with terraform-aws- you're good. Then you add a version tag to it such as 1.0.0
So let's say you create a terraform plan that points to that load balancer module, this is how you point your backend config to terraform cloud & to the load balancer module:
backend-state.tf contents:
terraform {
backend "remote" {
hostname = "app.terraform.io"
organization = "YOUR-TERRAFORM-CLOUD-ORG"
workspaces {
# name = "" ## For single workspace jobs
# prefix = "" ## for multiple workspaces
# you can use name instead of prefix
prefix = "terraform-plan-name-"
}
}
}
terraform plan main.tf contents;
module "aws_alb" {
source = "app.terraform.io/YOUR-TERRAFORM-CLOUD-ORG/loadbalancer/aws"
version = "1.0.0"
name = "load-balancer-test"
security_groups = [module.aws_sg.id]
load_balancer_type = "application"
internal = false
subnets = [data.aws_subnet.public.id]
idle_timeout = 1200
# access_logs_enabled = true
# access_logs_s3bucket = "BUCKET-NAME"
tags = local.tags
}
Locally from your terminal (using Mac OSX as an example);
terraform init
# if you're using name instead of prefix in your backend set
# up, no need to run terraform workspace cmd
terraform workspace new test
terraform plan
terraform apply
You'll see the apply happening in terraform cloud under your workspaces with this name: terraform-plan-name-test
"test" is appended to your workspace prefix name which is defined in your backend-state.tf above. You end up with a GUI / Console full of your terraform plans within your workspace, the same way you can see your Cloudformation Stacks in AWS. I find devops that are used to Cloudformation and transitioning to Terraform, like this set up.
One advantage is, within Terraform Cloud you can easily set it up so that a plan (stack build) is triggered with a git commit or merge to the master branch.
1 reference:
https://www.terraform.io/docs/language/settings/backends/remote.html#basic-configuration
I would Highly recommend using Terragrunt to keep your Terraform code manageable and DRY (the Don't repeat yourself principle).
Terragrunt has many capabilities - for your specific case I would suggest following the Keep your remote state configuration DRY section.
I'll add a short and simplified summary below.
Problems with managing remote state with Terraform
Let's say you have the following Terraform infrastructure:
├── backend-app
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
├── frontend-app
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
├── mysql
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
└── mongo
├── main.tf
└── other_resources.tf
└── variables.tf
Each app is a terraform module that you'll want to store its Terraform state in a remote backend.
Without Terragrunt you'll have to write the backend configuration block for each application in order to save the current state in a remote state storage:
terraform {
backend "s3" {
bucket = "my-terraform-state"
key = "frontend-app/terraform.tfstate"
region = "us-east-1"
encrypt = true
dynamodb_table = "my-lock-table"
}
}
Managing a few modules like in the above example its not a burden to add this file for each one of them - but it won't last for real world scenarious.
Wouldn't it be better if we could do some kind of inheritance (like in Object oriented programming)?
This is made easy with Terragrunt.
Terragrunt to the rescue
Back to the modules structure.
With Terragrunt we just need add add a root terragrunt.hcl with all the configurations and for each module you add a child terragrunt.hcl which contains only on statement:
├── terragrunt.hcl #<---- Root
├── backend-app
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
│ └── terragrunt.hcl #<---- Child
├── frontend-app
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
│ └── terragrunt.hcl #<---- Child
├── mysql
│ ├── main.tf
│ └── other_resources.tf
│ └── variables.tf
│ └── terragrunt.hcl #<---- Child
└── mongo
├── main.tf
└── other_resources.tf
└── variables.tf
└── terragrunt.hcl. #<---- Child
The root terragrunt.hcl will keep your remote state configuration and the children will only have the following statement:
include {
path = find_in_parent_folders()
}
This include block tells Terragrunt to use the exact same Terragrunt configuration from the root terragrunt.hcl file specified via the path parameter.
The next time you run terragrunt, it will automatically configure all the settings in the remote_state.config block, if they aren’t configured already, by calling terraform init.
The backend.tf file will be created automatically for you.
Summary
You can have hundreds of modules with nested hierarchy (for example divided into regions,tenants, applications etc') and still be able to maintain only one configuration of the remote state.
The way I have overcome this issue is by creating the project remote state in the first init plan apply cycle and initializing the remote state in the second init plan apply cycle.
# first init plan apply cycle
# Configure the AWS Provider
# https://www.terraform.io/docs/providers/aws/index.html
provider "aws" {
version = "~> 2.0"
region = "us-east-1"
}
resource "aws_s3_bucket" "terraform_remote_state" {
bucket = "terraform-remote-state"
acl = "private"
tags = {
Name = "terraform-remote-state"
Environment = "Dev"
}
}
# add this sniped and execute the
# the second init plan apply cycle
# https://www.terraform.io/docs/backends/types/s3.html
terraform {
backend "s3" {
bucket = "terraform-remote-state"
key = "path/to/my/key"
region = "us-east-1"
}
}
Managing terraform state bucket with terraform is kind of chicken and egg problem. One of the way we can address is:
Create terraform state bucket with terraform with local backend and then migrate the state to newly create state bucket.
It can be a bit tricky if you are trying to achieve this with a CI/CD pipeline and trying to make the job idempotent in nature.
Modularise backend configuration in a separate file.
terraform.tf
terraform {
required_version = "~> 1.3.6"
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 4.48.0"
}
}
}
provider "aws" {
region = "us-east-1"
}
main.tf
module "remote_state" {
# you can write your own module or use any community module which
# creates a S3 bucket and dynamoDB table (ideally with replication and versioning)
source = "../modules/module-for-s3-bucket-and-ddtable"
bucket_name = "terraform-state-bucket-name"
dynamodb_table_name = "terraform-state-lock"
}
backend.tf
terraform {
backend "s3" {
bucket = "terraform-state-bucket-name"
key = "state.tfstate"
region = "us-east-1"
dynamodb_table = "terraform-state-lock"
}
}
With following steps we can manage and create state S3 bucket in the same state.
function configure_state() {
# Disable S3 bucket backend
mv backend.tf backend.tf.backup
# Since S3 config is not present terraform local state will be initialized
# Or copied from s3 bucket if it already existed
terraform init -migrate-state -auto-approve
# Terraform apply will create the S3 bucket backend and save the state in local state
terraform apply -target module.remote_state
# It will re-enable S3 backend configuration for storing state
mv backend.tf.backup backend.tf
#It will migrate the state from local to S3 bucket
terraform init -migrate-state -auto-approve
}
there is a version issue here within terraform, for me it is working for the mentioned version. also, it is good to have the terraform state on the bucket.
terraform {
required_version = "~> 0.12.12"
backend "gcs" {
bucket = "bbucket-name"
prefix = "terraform/state"
}
}
As a word of caution, I would not create a terraform statefile with terraform in case someone inadvertently deletes it. So use scripts like aws-cli or boto3 which do not maintain state and keep those scripts limited to a variable for s3 bucket name. You will not really change the script for terraform state bucket in the long run except for creating additional folders inside the bucket which can be done outside terraform in the resource level.
All of the answers provided are very good. I just want to emphasize the "key" attribute. When you get into advanced applications of Terraform, you will eventually need to reference these S3 keys in order to pull remote state into a current project, or to leverage 'terraform move'.
It really helps to use intelligent key names when you plan your "terraform" stanza to define your backend.
I recommend the following as a base key name:
account_name/{development:production}/region/module_name/terraform.tfstate
Revise to fit your needs, but going back and fixing all my key names as I expanded my use of Terraform across many accounts and regions was not fun at all.
You can just simply use terraform cloud and configure your backend as follows:
terraform {
backend "remote" {
hostname = "app.terraform.io"
organization = "your-tf-organization-name"
workspaces {
name = "your-workspace-name"
}
}
}
Assuming that you are running terraform locally and not on some virtual server and that you want to store terraform state in S3 bucket that doesn't exist. This is how I would approach it,
Create terraform script, that provisions S3 bucket
Create terraform script that provisions your infrastructure
At the end of your terraform script to provision bucket to be used by second terraform script for storing state files, include code to provision null resource.
In the code block for the null resource using local-exec provisioner run command to go into the directory where your second terraform script exist followed by usual terraform init to initialize the backend then terraform plan, then terraform apply
I've made a script according to that answer. Keep in mind you'll need to import DynamoDB to your tf state as it is created through aws cli.

How does s3 URL created for codedeploy and how to find with commit ID aws

I have been trying to figure out, how to find s3 URL or s3 object name which is created after the codedeploy deployment with new commit ID.
Here is the aws-cli way to list application revisions and their s3 Location:
aws deploy list-application-revisions --application <your application name>
Example output:
{ "revisionType": "S3",
"s3Location": {
"bucket:" "mybucket",
"key": "mys3objectname",
"bundleType": "zip",
"eTag": "ff1e77d70adaedfd14cecba209811a94"
}
}
To construct an s3 url from this, use:
https://s3-<region>.amazonaws.com/<bucket>/<key>
If you need to find your application name, use:
aws deploy list-applications

AWS CodePipeline Build error

I created an AWS CodePipeline pipeline to pull from Github, build with Jenkins, and deploy to an ElasticBeanstalk project. I can deploy the war to beanStack directly and validate.
When i try to do the same from CodePipeLine i see the below error in AWS CodePipeline Polling Log of Jenkins -
ERROR: Failed to record SCM polling for hudson.model.FreeStyleProject#ae44565e6[AppPortal]
com.amazonaws.services.codepipeline.model.ActionTypeNotFoundException: ActionType (Category: 'Build', Owner: 'Custom', Provider: 'MPiplelineProvider', Version: '1') is not available (Service: AWSCodePipeline; Status Code: 400; Error Code: ActionTypeNotFoundException; Request ID: e35456561d-999f-56e7-3rgf-75985675533b3)
at com.amazonaws.http.AmazonHttpClient.handleErrorResponse(AmazonHttpClient.java:1401)
at com.amazonaws.http.AmazonHttpClient.executeOneRequest(AmazonHttpClient.java:945)
at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:723)
at com.amazonaws.http.AmazonHttpClient.doExecute(AmazonHttpClient.java:475)
at com.amazonaws.http.AmazonHttpClient.executeWithTimer(AmazonHttpClient.java:437)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:386)
at com.amazonaws.services.codepipeline.AWSCodePipelineClient.doInvoke(AWSCodePipelineClient.java:2078)
I have set the SCM poll to * * * * * for testing purpose.
Post-build Actions - AWS CodePipeline publisher - Location - target/AppPortal
I installed only AWS Codepipeline pulgin in jenkins.
Can you let me know what I'm missing.
Thanks
Did you register the Jenkins custom action type in CodePipeline, in the same region you're polling?
Check your Jenkins job configuration for:
AWS Region
Category
Provider
Version
From your error message:
ActionType (Category: 'Build', Owner: 'Custom', Provider: 'MPiplelineProvider', Version: '1')
Then use the AWS CLI to list your custom action types, in that region, and make sure the Category, Provider, and Version match:
aws codepipeline list-action-types --action-owner-filter Custom --region us-west-2
If you created the Jenkins action type through the AWS Console, it should have these values:
ActionType (Category: 'Build', Owner: 'Custom', Provider: 'Jenkins', Version: '1')
If that's the case, updating your Jenkins job Provider from MPiplelineProvider to Jenkins should fix your problem.
In our scenario:
Trigger: moving the Jenkins master (ec2) behind a Load Balancer.
Symptom: we started getting the same error (as above) after updating all security group setting so that load balancer does not get in the way.
Resolution:
On the Jenkins (ec2) box, we deleted the "project" and re-creating it with the exact same setting (including name) as before. This allowed Jenkins to reconnect with Code Pipeline and job started working again.
Here is the codepipeline stage action settings:
{
"inputArtifacts": [],
"name": "foobar-test",
"region": "us-west-2",
"actionTypeId": {
"category": "Test",
"owner": "Custom",
"version": "1",
"provider": "foobar-provider"
},
"outputArtifacts": [],
"configuration": {
"ProjectName": "foobar-api-qa-aws_trigger"
},
"runOrder": 1