I created a cloud formation stack as below, I'm setting MaximumRetryAttempts: 1 , but once the function is created the retry events is always set to 2 ( attached screenshot) . how can i change the value of this.
HelloWorldLambdaFunction:
Type: AWS::Lambda::Function
Properties:
FunctionName: hello-world
Runtime: python3.7
Handler: index.lambda_handler
version:
Type: AWS::Lambda::Version
Properties:
FunctionName: !Ref HelloWorldLambdaFunction
asynconfig:
Type: AWS::Lambda::EventInvokeConfig
Properties:
FunctionName: !Ref HelloWorldLambdaFunction
MaximumRetryAttempts: 1
Qualifier: !GetAtt version.Version
The code looks fine. However, it seems to me that you are viewing $LATEST version in the console.
However, you set the asynconfig for version 1. Thus, in the console you have to explicitly select the correct lambda function version:
Update
To use latest version:
asynconfig:
Type: AWS::Lambda::EventInvokeConfig
Properties:
FunctionName: !Ref HelloWorldLambdaFunction
MaximumRetryAttempts: 1
Qualifier: $LATEST
Related
I have found questions to convert terraform to cloudformation , but wondering if there is one for this . I am creating a REST api , with api gateway and lambda ( code below) . the stack is working with cloudformation, trying to convert this to terraform. I have version (AWS::Lambda::Version) and asynconfig (AWS::Lambda::EventInvokeConfig) set up for my lambda , but don't see anything similar in terraform.
lambdaFunc
Type: AWS::Serverless::Function
Properties:
FunctionName: something
...
version:
Type: AWS::Lambda::Version
Properties:
FunctionName:
Ref: lambdaFunc
asyncconfig:
Type: AWS::Lambda::EventInvokeConfig
Properties:
FunctionName:
Ref: lambdaFunc
MaximumRetryAttemps: 0
Qualifier: $LATEST
Pretty new to AWS Lambda function, and this is my time to get my hands dirty. I got this error in the title when I wanted to docker build my function. And here is how I configured my function:
PitchAiIngest:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub pitch-ai-ingest-${Environment}
Handler: lambda_function.lambda_handler
Runtime: python3.7
CodeUri: pitchai_ingest/
Description: get pitchai information from API and publish to dynamodb
MemorySize: 128
Timeout: 900
Role: !GetAtt LambdaRole.Arn
Environment:
Variables:
LOGGING_LEVEL: INFO
APP_NAME: pitch-ai-ingest
APP_ENV: !Ref Environment
DYNAMO_DB: !Ref PitchAiEventDynamoDBTable
PLAYER_DB: !Ref PitchAiPlayerDynamoDBTable
PITCH_SQS: !Ref PitchAiIngestQueue
Tags:
env: !Ref Environment
service: pitch-ai-service
function_name: !Sub pitch-ai-ingest-${Environment}
Roughly speaking, I post the snippet above in file cfn-tempate.yml under the same directory of folder pitchai_ingest (including Lambda handler).
What should I do to fix it?
I mistakenly set AWS_ACCESS_KEY_ID as AWS_ACCESS_KEY. That's why the credential wasn't found.
I have added one layer to my Lambda function through CloudFormation. Now I have a requirement to add one more layer to my function. Basically, I need two layers in my existing Lambda function. Is it possible? I tried searching the AWS docs but I don't see it.
Resources:
LambdaLayer:
Type: "AWS::Lambda::LayerVersion"
Properties:
CompatibleRuntimes:
- python3.8
Content:
S3Bucket: !Sub "hello-${AWS::Region}"
S3Key: !Sub "myapp/layer1.zip"
LayerName: "layer1"
LambdaFunction:
Type: "AWS::Lambda::Function"
Properties:
Code:
S3Bucket: hello
S3Key: myapp/function.zip"
FunctionName: "hello-function"
Handler: "hello-function.lambda_handler"
Layers:
- !Ref LambdaLayer
Yes, is it possible. Add additional layers in the same way that you did the first layer, only append numbers to the resource names to distinguish them:
Resources:
LambdaLayer1:
Type: "AWS::Lambda::LayerVersion"
Properties:
CompatibleRuntimes:
- python3.8
Content:
S3Bucket: !Sub "hello-${AWS::Region}"
S3Key: !Sub "myapp/layer1.zip"
LayerName: "layer1"
LambdaLayer2:
Type: "AWS::Lambda::LayerVersion"
...
LayerName: "layer2"
LambdaFunction:
Type: "AWS::Lambda::Function"
Properties:
Code:
S3Bucket: hello
S3Key: myapp/function.zip"
FunctionName: "hello-function"
Handler: "hello-function.lambda_handler"
Layers:
- !Ref LambdaLayer1
- !Ref LambdaLayer2
I am trying to achieve something similar to below in a AWS Cloudformation YAML file:
AWSTemplateFormatVersion: 2010-09-09
testAttribute = "test"
Resources:
Lambda:
Type: AWS::Lambda::Function
Properties:
Runtime: python3.7
Role: !GetAtt iam.Arn
MemorySize: 128
Timeout: 10
Handler: lambda_function.lambda_handler
FunctionName: "testName"+${testAttribute}
Description: 'This is my lambda'
Code:
S3Bucket: myBucket
S3Key: "lambda/testName"+${testAttribute}+".zip"
I know that above isn't quite correct, but I cant find a good answer when searching how to achieve it. Anyone who have some guidance on this matter?
It depends on the use case but if the "variable" would be static and you don't need the change it when deploying the stack, I would suggest an alternative solution, to use the Mappings section.
This allows you to define some static values without sending them when deploying the stack (you will have much cleaner deploy commands, and the logic would be on the template side instead of the deploy side).
In this case, I'm using !Sub intrinsic function with a mapping (you can set multiple variables to be substituted using !Sub):
AWSTemplateFormatVersion: 2010-09-09
Mappings:
attributes:
lambda:
testAttribute: "test"
Resources:
Lambda:
Type: AWS::Lambda::Function
Properties:
Runtime: python3.7
Role: !GetAtt iam.Arn
MemorySize: 128
Timeout: 10
Handler: lambda_function.lambda_handler
FunctionName: !Sub
- "testName${attr}"
- {attr: !FindInMap [attributes, lambda, testAttribute]}
Description: 'This is my lambda'
Code:
S3Bucket: myBucket
S3Key: !Sub
- "lambda/testName${attr}.zip"
- {attr: !FindInMap [attributes, lambda, testAttribute]}
Note: Mappings have a mandatory three-level nesting, take this into consideration while designing your solution
You could use Parameters with a default value, and Sub later in the template:
AWSTemplateFormatVersion: 2010-09-09
Parameters:
testAttribute:
Type: String
Default: test
Resources:
Lambda:
Type: AWS::Lambda::Function
Properties:
Runtime: python3.7
Role: !GetAtt iam.Arn
MemorySize: 128
Timeout: 10
Handler: lambda_function.lambda_handler
FunctionName: !Sub "testName${testAttribute}"
Description: 'This is my lambda'
Code:
S3Bucket: myBucket
S3Key: !Sub "lambda/testName${testAttribute}.zip"
[Edited for typo]
I'm trying to set up a local dev environment for my Lambda functions using SAM. I had everything working until I added a reference to a layer in my configuration.
I followed the instructions here: https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-layers.html. I added my ARN for my layer version in my template.ymal as follows:
# template.ymal
TestLayerFunction:
Type: AWS::Serverless::Function
Properties:
FunctionName: TestLayer
Role: arn:aws:iam::111111111111:role/ReadStreamingTable
CodeUri: src/streaming/test-layer/
Handler: app.handler
Runtime: nodejs8.10
Layers:
- arn:aws:lambda:eu-west-1:111111111111:layer:Global:7
However when running a "sam local invoke" I get the following error:
botocore.exceptions.EndpointConnectionError: Could not connect to the endpoint URL:
"https://lambda.eu-west-1a.amazonaws.com/2018-10-31/layers/arn%3Aaws%3Alambda%3Aeu-west-1%3A111111111111%3Alayer%3AGlobal/versions/7"
The way I've added the layer ARN in the configuration seems to be exactly how they do it in the example so I'm not sure what is causing the error.
I know it's not exactly a solution but can you not have your layer as part of your SAM file?
If you have a look on this article on the AWS site they use both the layer and the lambda function on the same yaml file so you'd end up with something like this:
Resources:
TempConversionFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: hello-world/
Handler: app.lambdaHandler
Layers:
- !Ref TempConversionDepLayer
Events:
HelloWorld:
Type: Api
Properties:
Path: /{conversion}/{value}
Method: get
TempConversionDepLayer:
Type: AWS::Serverless::LayerVersion
Properties:
LayerName: sam-app-dependencies
Description: Dependencies for sam app [temp-units-conv]
ContentUri: dependencies/
CompatibleRuntimes:
- nodejs6.10
- nodejs8.10
LicenseInfo: 'MIT'
RetentionPolicy: Retain