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from datetime import date import zipfile import boto3 from botocore.exceptions import ClientError
################################################################################################ # # Configuration Parameters # ################################################################################################
# a bucket in S3 will be created to store the counter bucket names need to be world-wide unique ;) # Hence we create a bucket name that contains your group number and the current year. # The counter will be stores as key (file) "us-east-1" in the bucket (same name as our default region) # in the bucket and expects a number in it to increase groupNr = 22 currentYear = date.today().year
globallyUniqueS3GroupBucketName = "cloudcomp-counter-" + str(currentYear) + "-group" + str(groupNr)
# region = 'eu-central-1' region = 'us-east-1' functionName = 'cloudcomp-counter-lambda-demo'
# The Lambda function will run using privileges of a role, that allows the function to access/create # resources in AWS (in this case read/write to S3). In AWS Academy you need to use the role that # use created for your student account in the lab (see lab readme). # see ARN for AWS Academy LabRole function here: # https://us-east-1.console.aws.amazon.com/iamv2/home?region=us-east-1#/roles/details/LabRole?section=permissions # # e.g.: (309000625112, 919927306708, 488766701848 would in your case be your AWS Account ID, see Lab Details) # # roleArn = 'arn:aws:iam::309000625112:role/service-role/cloudcomp-counter-demo-role-6rs7pah3' # roleArn = 'arn:aws:iam::919927306708:role/cloudcomp-s3-access' # roleArn = 'arn:aws:iam::488766701848:role/LabRole'
# standard name for role in AWS Academy lab created by vocareum is "LabRole". See README of the # lab. The following code will lookup the AWS Resource Name (ARN) (sort of the ID for this role) # that has the following name: roleName = "LabRole"
################################################################################################ # # boto3 code # ################################################################################################
def cleanup_s3_bucket(s3_bucket): # Deleting objects for s3_object in s3_bucket.objects.all(): s3_object.delete() # Deleting objects versions if S3 versioning enabled for s3_object_ver in s3_bucket.object_versions.all(): s3_object_ver.delete()
client = boto3.setup_default_session(region_name=region) iamClient = boto3.client('iam') s3Client = boto3.client('s3') s3Resource = boto3.resource('s3') lClient = boto3.client('lambda') apiClient = boto3.client("apigatewayv2")
print("Getting AWS Academy LabRole ARN...") print("------------------------------------") response = iamClient.list_roles() for role in response["Roles"]: if role["RoleName"] == roleName: roleArn = role["Arn"] print(roleArn)
print("Searching for old API gateway...") print("------------------------------------") for api in apiClient.get_apis()["Items"]: if api["Name"] == functionName + '-api': print("Deleting old API gateway...") print("------------------------------------") response = apiClient.delete_api( ApiId=api["ApiId"], )
print("Deleting old function...") print("------------------------------------") try: response = lClient.delete_function( FunctionName=functionName, ) except lClient.exceptions.ResourceNotFoundException: print('Function not available. No need to delete it.')
print("Deleting old bucket...") print("------------------------------------")
try: currentBucket = s3Resource.Bucket(globallyUniqueS3GroupBucketName) cleanup_s3_bucket(currentBucket) currentBucket.delete() except s3Client.exceptions.NoSuchBucket: print('Bucket not available. No need to delete it.')
print("creating S3 bucket (must be globally unique)...") print("------------------------------------")
try: response = s3Client.create_bucket(Bucket=globallyUniqueS3GroupBucketName) response = s3Client.put_object(Bucket=globallyUniqueS3GroupBucketName, Key='us-east-1', Body=str(0)) except ClientError as e: print(e)
print("creating new function...") print("------------------------------------")
zf = zipfile.ZipFile('lambda-deployment-archive.zip', 'w', zipfile.ZIP_DEFLATED) zf.write('lambda_function.py') zf.close()
lambdaFunctionARN = "" with open('lambda-deployment-archive.zip', mode='rb') as file: zipfileContent = file.read()
response = lClient.create_function( FunctionName=functionName, Runtime='python3.9', Role=roleArn, Code={ 'ZipFile': zipfileContent }, Handler='lambda_function.lambda_handler', Publish=True, Environment={ 'Variables': { 'bucketName': globallyUniqueS3GroupBucketName } } ) lambdaFunctionARN = response['FunctionArn']
# API gateway to get an HTTP endpoint that we can access directly in the browser, # which will call our function, as in the provided demo: # https://348yxdily0.execute-api.eu-central-1.amazonaws.com/default/cloudcomp-counter-demo
print("creating API gateway...") print("------------------------------------")
response = apiClient.create_api( Name=functionName + '-api', ProtocolType='HTTP', Target=lambdaFunctionARN, CredentialsArn=roleArn )
print("Lambda Function and S3 Bucket to store the counter are created.\n" "\n" "You can access the API gateway and increment the counter using the created Lambda function\n" "at: " + response["ApiEndpoint"] + " \n" "You can also run invoke-function.py to view an increment the counter. You can also use \n" "the test button in the Lambda AWS console. In this case you need to send the content\n" "\n" "{\n" " \"input\": \"1\"\n" "}\n" "\n" "to increment the counter by 1.\n" "Try to understand how Lambda can be used to cut costs regarding cloud services and what its pros\n" "and cons are.\n")
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