A reference project to deploy a serverless jobs processor on AWS with Terraform
A service which returns Fibonacci sequence
App URL here: https://8nalvgvzrl.execute-api.us-east-1.amazonaws.com/production/api/v1/jobs
- Make sure you have installed Terraform, AWS CLI, and configured a
default
AWS CLI profile (see doc here)
terraform -help # prints Terraform options
which aws # prints /usr/local/bin/aws
aws --version # prints aws-cli/2.0.36 Python/3.7.4 Darwin/18.7.0 botocore/2.0.0
aws configure # configure your AWS CLI profile
-
Create an S3 bucket to store Terraform state. Populate bucket name in
01-main.tf
-
Create another S3 bucket to store Lambda functions build artifacts:
aws s3api create-bucket --bucket=<YOUR_UNIQUE_BUCKET_NAME> --region=<DEFAULT_REGION>
- Populate
terraform.tfvars
:
default_region = "<YOUR_AWS_DEFAULT_REGION>"
app_name = "<GIVE_YOUR_APP_A_NAME!>"
environment = "<ENVIRONMENT_NAME>"
- Navigate to
/deploy/lambdas/<FUNCTION_NAME>
- Create a
.zip
file:
zip -r <FUNCTION_NAME>.zip .
- Uploads Lambda artifact to S3 bucket:
aws s3 cp <FUNCTION_NAME>.zip s3://<BUCKET_NAME>/v1.0.0/<FUNCTION_NAME>.zip
cd deploy/lambdas/layer # change to lambda layer directory
sh updateLayer.sh # uploads lambda layer to S3 bucket
cd deploy # change to deploy directory
terraform init # initialises Terraform
terraform apply # deploys AWS stack. See output for API url
terraform destroy # destroys AWS stack
- Make a
POST
request to<API_ENDPOINT>/api/v1/jobs
to trigger a job which returns Fibonacci sequence with N numbers
{
"data": 10
}
- Make a
GET
request to<API_ENDPOINT>/api/v1/jobs
to retrieve all jobs - Make a
GET
request to<API_ENDPOINT>/api/v1/jobs/<JOB_ID>
to retrieve a specific job
-
Update the
deploy/lambdas/processQueue/updateFunction.sh
shell script with correct values i.e. Amazon S3 bucket name, and key. See documentation on AWS CLIupdate-function-code
here -
Run the script:
cd deploy/lambdas/processQueue # change to lambda directory
chmod +x updateFunction.sh # set permission to run script
./updateFunction.sh # run the script
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
If you find this project helpful, please give a ⭐ or even better buy me a coffee ☕ 👇 because I'm a caffeine addict 😅