I have a lambda which is triggered by an EventBridge custom bus. I want to send another event to the customer bus at the end of the function processing. I created a destination in the lambda to send to the same custom bus.
I have the following code where the function handler will return a CloudWatchEvent. This is not working.
public async Task<CloudWatchEvent<object>> FunctionHandler(CloudWatchEvent<object> evnt, ILambdaContext context)
{
return await ProcessMessageAsync(evnt, context);
}
My lambda was being triggered by S3 input event (which is asynchronous), I tried adding destination on Lambda "success" to EventBridge bus, created a rule to capture that and send it to CloudWatch logs but it didn't seem to work.
Turns out, while creating the Rule in EventBridge, event pattern was set to:
{
"source": ["aws.lambda"]
}
Which is what you get if you are using the console and selecting AWS Lambda as the AWS Service.
Infuriated, I couldn't seem to get it to work even with a simple event. On further inspection, I looked at the input event and realized that it wants lambda and not aws.lambda. It is also mentioned in the documentation: https://docs.aws.amazon.com/lambda/latest/dg/invocation-async.html
So to fix it, I changed it to
{
"source": ["lambda"]
}
and it worked for me.
Have you given a shot to AWS Lambda Destinations. There are 4 types of Destinations supported
SQS Queue
SNS Topic
Event Bridge Event Bus
Lambda Function itself.
Related
I have a AWS lambda that the trigger for activating it is an event from EventBridge (rule)
The rule looks like this:
{
"detail-type": ["ECS Task State Change"],
"source": ["aws.ecs"],
"detail": {
"stopCode": ["EssentialContainerExited", "UserInitiated"],
"clusterArn": ["arn:aws:ecs:.........."],
"containers": {
"name": ["some name"]
},
"lastStatus": ["DEACTIVATING"],
"desiredStatus": ["STOPPED"]
}
}
This event is normally triggered when ECS task status is changed (in this case when a task is killed)
My questions are:
Can I simulate this event from command line?
maybe by running aws events put-events --entries file://putevents.json
(What should I write in the putevents.json file?)
Can I simulate this event from Javascript code?
TL;DR Yes and yes, provided you deal with with the limitation that user-generated events cannot have a source that begins with aws.
Send custom events to EventBridge with the PutEvents API. The API is available in the CLI as well as in the SDKs (see AWS JS SDK). The list of custom events you pass in the entries parameter must have three fields at a minimum:
[
{
"source": "my-custom-event", // cannot start with aws !!,
"detail-type": "ECS Task State Change",
"detail": {} // copy from the ECS sample events docs
}
]
The ECS task state change event samples in the ECS documentation make handy templates for your custom events. You can safely prune any non-required field that you don't need for pattern matching.
Custom events are not permitted to mimic the aws system event sources. So amend your rule to also match on your custom source name:
"source": ["aws.ecs", "my-custom-event"],
I'm trying to use Winston to send logs to Datadog from an Aws Lambda. The problem with the lambdas is that once we return a response, the lambda execution stops and it doesn't give time to Winston to flush the logs.
Is there a way I can force the flush before returning. I'm trying this but it doesn't seem to do the trick:
async function handler (event): Promise<FormattedJSONResponse> {
const logger = getLogger()
// do some work
await closeLogger(logger)
return awsResponse
}
function closeLogger (logger: Logger): Promise<any> {
const loggerDone = new Promise((resolve, _) => {
logger.on('finish', () => {
resolve(logger)
})
})
logger.end()
logger.close()
return loggerDone
}
Versions:
AWS Lambda with nodejs 12
Winston: 3.3.3
Thanks for your help
First of all I don't understand why you would want to send your logs within you lambda function? If you do so your lambda function will run longer to process the logs, meaning you will be charged for the time it takes to send the logs to Datadog.
Instead, you could save the logs to CloudWatch. To avoid high charges for CloudWatch set the retention to a rather short time, maybe one day. On the CloudWatch log stream you can then add a subscriber which could be another lambda function. This "log-processor"-lambda-function will process, transform the logs and send them to Datadog. With this architecture your first lambda function containing the business logic won't fail if Datadog cannot be reached for instance. It makes your architecture more resilient and has better separation of concerns. Yan Cui wrote a great article on "Centralised logging for AWS Lambda"
Another approach, still separating your logging from your lambda function business logic to some degree, builds upon lambda extensions namely the Lambda Logs API.
Put simple, lambda extensions add an extra layer to your function but are not part of the lambda function's code itself. Probably the best part for you: Datadog already offers a ready to use extension, which is responsible for:
Pushing real-time enhanced Lambda metrics, custom metrics, and traces from the Datadog Lambda Library to Datadog.
Forwarding logs from your Lambda function to Datadog.
For more info on Lambda extensions follow the links mentioned above or have a look at Yan Cui's post "Lambda Logs API: a new way to process Lambda logs in real-time"
After spending 4 hours on this issue, I found no other way (that works, isn't buggy and is transport agnostic) than to use an arbitrary timeout before returning a response.
This example is for NextJS but you can easily remove res: NextApiResponse.
export const gracefulExit = (response: any, res: NextApiResponse) => {
setTimeout(() => {
res.send({ ...response, sessionId });
}, 400);
};
Then in all my serverless functions I don't do res.send({x}) but rather gracefulExit({x}, res)
I currently have one AWS Lambda function that is updating a DynamoDB table, and I need another Lambda function that needs to run after the data is updated. Is there any benefit to using a DynamoDB trigger in this case instead of invoking the second Lambda using the first one?
It looks like the programmatic invocation would give me more control over when the Lambda is called (ie. I could wait for several updates to occur before calling), and reading from a DynamoDB Stream costs money while simply invoking the Lambda does not.
So, is there a benefit to using a trigger here? Or would I be better off invoking the Lambda myself?
DynamoDB Stream seems to be the better practice because:
you delegate the responsibility of invoking the post-processor function from your writer-Lambda. Makes writer more simple (aka faster),
you simplify connecting new external writers to the same Table, otherwise you have to implement the logic to call post-processors in all of them as well,
you guarantee that all data is post-processed (even if somebody added a new item in the web-interface of DynamoDB. :)
moneywise, the execution time you will spend to send invoke() operation from writer Lambda will likely cover the costs of a stream.
unless you use DynamoDB transactions your data may still be not yet available for post-processor if you call him from writer too soon. If your business logic doesn't need transactions then using them just to cover this problem = extra time/cost.
P.S. You can batch from the DynamoDB stream of course out of the box with simple setting. You are not obliged to invoke post-processor for every write operation.
After the data is updated, you can publish a SQS message, then add a trigger to configure another function to read from Amazon SQS in the Lambda console, create an SQS trigger.
To create a trigger
Open the Lambda console Functions page.
Choose a function.
Under Designer, choose Add trigger.
Choose a trigger type.
Configure the required options and then choose Add.
Lambda supports the following options for Amazon SQS event sources.
Event Source Options
SQS queue – The Amazon SQS queue to read records from.
Batch size – The number of items to read from the queue in each batch, up to 10. The event may contain fewer items if the batch that Lambda read from the queue had fewer items.
Enabled – Disable the event source to stop processing items.
var QUEUE_URL = 'https://sqs.us-east-1.amazonaws.com/{AWS_ACCUOUNT_}/matsuoy-lambda';
var AWS = require('aws-sdk');
var sqs = new AWS.SQS({region : 'us-east-1'});
exports.handler = function(event, context) {
var params = {
MessageBody: JSON.stringify(event),
QueueUrl: QUEUE_URL
};
sqs.sendMessage(params, function(err,data){
if(err) {
console.log('error:',"Fail Send Message" + err);
context.done('error', "ERROR Put SQS"); // ERROR with message
}else{
console.log('data:',data.MessageId);
context.done(null,''); // SUCCESS
}
});
}
Please don't forget add a trigger from another function to this SQS topic. That function will receive the SQS message automatic to handle.
I have multiple cloudwatch events. Each of them triggers the same Lambda called app with different inputs at the same time: i.e.
event1 triggers lambda app at a schedule using input: app_name=app1
event2 triggers lambda app at the same schedule using input: app_name=app2.
event3 triggers lambda app at the same schedule using input: app_name=app3.
As you can see all the event has the same schedule. I really do not need so many duplicated events.
Is there any way I can use one CloudWatch event to trigger one Lambda with multiple input? i.e. at a time, the same event will trigger lambda app with input app1; it also triggers the same lambda with input app2, it also triggers the same lambda with input app3?
it will make my structure neat. one event, one lambda (with different input) for multiple app.
You can have one CloudWatch Rule with a Schedule event source and one Lambda function target. You will need to configure the input to use a Constant (JSON text) with an array of data as shown here:
Then in your Lambda function the event will be your constant. Example with Node.js 8.10 to start EC2 instances:
const AWS = require('aws-sdk');
const ec2 = new AWS.EC2();
exports.handler = async (event) => {
console.log('Starting instances: %j', event);
const data = await ec2.startInstances({ InstanceIds: event }).promise();
console.log(data);
};
I am having Lambda function that I expect to return some result. So if I send wrong parameters it fails for example in the middle of the function.
Is there a way I can handle if any error occurs to be sent in my DLQ, print the error in the message, then retry, then delete the message?
example error from CloudWatch:
TypeError: commandArray is not iterable
AWS Lambda function has a retry mechanism on Asynchronous invocation, If AWS Lambda is unable to fully process the event, it will automatically retry the invocation twice, with delays between retries.
After retries, AWS Lambda will send ERROR message detail to the specified Amazon SQS queue or Amazon SNS topic.
https://docs.aws.amazon.com/lambda/latest/dg/retries-on-errors.html
The error message does not contain failed Lambda function name due to any reason (exceptions/timeout). To add lambda function name in the error message, you can go for two ideas.
Solution - 1
Lambda function name can be found by S3 API, S3 bucket detail can be found by received event object in the error message.
Solution - 2
Convention: SNS topic name contains lambda function name in it
Configure SNS topic to lambda function
Add a lambda function to SNS topic subscriber list
Subscribed lambda function can get lambda function name from SNS topic name and can add any custom detail in the received error message
Lambda has the facility to retry and pump failures into a Dead Letter Queue.
Any Lambda function invoked asynchronously is retried twice before the event is discarded. If the retries fail and you're unsure why, use Dead Letter Queues (DLQ) to direct unprocessed events to an Amazon SQS queue or an Amazon SNS topic to analyze the failure.
You can then have a Lambda Function on the SNS topic or SQS queue that can respond to the error and react in the way you want it to.
For more information, see: https://docs.aws.amazon.com/lambda/latest/dg/dlq.html