Result:

🚀 Starting SLD deployment...

✓ Checking prerequisites...
✓ Creating Kind cluster...
✓ Deploying SLD services...
✓ Initializing admin user...

#################################################
#  Now, you can play with SLD 🕹️                #
#################################################
API: http://localhost:8000/docs
DASHBOARD: http://localhost:5000/
---------------------------------------------
username: admin
password: Password08@
---------------------------------------------

Other CLI commands:

python sld_cli.py status    # Check deployment status
python sld_cli.py stop      # Stop all services
python sld_cli.py restart   # Restart services
python sld_cli.py logs      # View logs

Option 2: Installation with Kubernetes (Kind)

1. Clone the SLD repo

   git clone https://github.com/D10S0VSkY-OSS/Stack-Lifecycle-Deployment.git
   cd Stack-Lifecycle-Deployment
   

2. Install CLI dependencies

   pip install -r requirements.txt
   

3. Deploy SLD in k8s with kind

   python sld_cli.py start -m k8s
   

   Result:

   🚀 Starting SLD deployment in Kubernetes mode...
   
   ✓ Checking prerequisites...
   ✓ Creating Kind cluster...
   ✓ Deploying SLD services...
   ✓ Initializing admin user...
   
   #################################################
   #  Now, you can play with SLD 🕹️                #
   #################################################
   API: http://localhost:8000/docs
   DASHBOARD: http://localhost:5000/
   ---------------------------------------------
   username: admin
   password: Password08@
   ---------------------------------------------
   

   Other Kubernetes commands:

   python sld_cli.py status -m k8s    # Check deployment status
   python sld_cli.py stop -m k8s      # Stop all services
   python sld_cli.py restart -m k8s   # Restart services
   python sld_cli.py logs -m k8s      # View logs
   

Usage

1. Sign-in to DASHBOARD:

   Click the dashboard link:

2. Add Cloud account

   fill in the form with the required data. in our example we will use

   • Squad: squad1
   • Environment: develop

   by default workers are running as squad1 and squad2 for play purpose, but you can change it and scale when you want

   When you add an account to a provider ( aws, gcp, azure ) one squad is created, you must create a worker for the name of the created squad, if you don't do it the deployment will remain in a "PENDING" state Read Workers

   finally add:

   • Access_key_id
   • Secret_access_key
   • Default_region ( default eu-west-1) In case you use assume role, fill in the rest of the data.

3. Add terraform module or stack

   • Name: Add the name with a valid prefix according to the cloud provider.

   Prefixs supported: aws_ , gcp_, azure_

   • git: Add a valid git repository, like github, gitlab, bitbucket, etc. in our case to play we use (https://github.com/D10S0VSkY-OSS/aws_vpc_poc)

   You can pass user and password as https://username:password@github.com/aws_vpc For ssh you can pass it as a secret in the deployment to the user sld

   • Branch: Add the branch you want to deploy by default is master
   • Squad Access: Assign who you want to have access to this stack by squad

   '*' = gives access to all, you can allow access to one or many squads separated by commas: squad1,squad2

   • tf version: indicates the version of terraform required by the module or stack

   https://releases.hashicorp.com/terraform/

   • Description: Describe the module or stack to help others during implementation.

4. Deploy your first stack!!!

   List stacks for deploy

   Choose deploy

   SLD will generate a dynamic form based on the stack variables, fill in the form and press the Deploy button

   Important! assign the same squad and environment that we previously created when adding the account (See Add Cloud account)

   Now, the status of the task will change as the deployment progresses.

   You can control the implementation life cycle You can destroy, re-implement that SLD will keep the old values ​​or you can also edit those values ​​at will. And finally you can manage the life cycle programmatically, handle the destruction / creation of the infrastructure, a good practice for the savings plan!!!

Custom settings

Storage backend

SLD uses its own remote backend, so you don't need to configure any backend in terraform. The following example shows a backend config

        terraform {
          backend "http" {
            address = "http://remote-state:8080/terraform_state/aws_vpc-squad1-develop-vpc_core"
            lock_address = "http://remote-state:8080/terraform_lock/aws_vpc-squad1-develop-vpc_core"
            lock_method = "PUT"
            unlock_address = "http://remote-state:8080/terraform_lock/aws_vpc-squad1-develop-vpc_core"
            unlock_method = "DELETE"
          }
        }
        

At the moment SLD supports MongoDB, S3 and local backend (for testing purposes only) To configure MongoDB as a backend, you must pass the following variables as parameters to the remote-state service:

# docker-compose.yaml
    environment:                                                                                                     
      SLD_STORE: mongodb                                                                                             
      SLD_MONGODB_URL: "mongodb:27017/"
      MONGODB_USER: admin
      MONGODB_PASSWD: admin

# k8s yaml
    env:
    - name: SLD_STORE
      value: mongodb
    - name: SLD_MONGODB_URL
      value: "mongodb:27017/"
    - name: MONGODB_USER
      value: admin
    - name: MONGODB_PASSWD
      value: admin

To configure S3 you can pass the access and secret keys of aws, in case SLD is running in AWS it is recommended to use roles

    env:
    - name: SLD_STORE
      value: "S3"
    - name: SLD_BUCKET
      value: "s3-sld-backend-cloud-tf-state"
    - name: AWS_ACCESS_KEY
      value: ""
    - name: AWS_SECRET_ACCESS_KEY
      value: ""

For Azure env you need set the next env

          env:                                                                                                                                    
          - name: SLD_STORE
            value: azure
          - name: AZURE_STORAGE_CONNECTION_STRING
            value: "DefaultEndpointsProtocol=https;AccountName=<YOUR ACCOUNT>;AccountKey=<YOUR ACCESS KEY>;EndpointSuffix=core.windows.net"

See azure-storage-configure-connection-string

For google cloud storage set:

SLD_STORE=gcp
export GOOGLE_APPLICATION_CREDENTIALS="/app/sld-gcp-credentials.json"

Import google service account key to k8s secret

kubectl create secret generic gcp-storage --from-file=~/Downloads/storage.json

Modify sld-remote-state.yml set gcp storage cloud backend and mount secret:

apiVersion: apps/v1                                                                                                                               
kind: Deployment                                                                                                                                  
metadata:                                                                                                                                         
  name: remote-state