Scenario- There is a master lambda who is splitting work and giving it off to multiple other lambdas (workers). The first lambda iterates and invokes the other lambdas asynchronously
If the number of lambdas which are getting spawned are more than 1000, will it fail?
Should there be an SNS between the two lambdas... so that the SNS will retry?
Or a more complicated approach of putting the messages into a queue and then sending notification of 'X' number of worker lambdas to start polling the queue?
Is there a better way?
Yes, there should be some kind of decoupling between the producer and consumers. The most obvious way is to have the producer create 1000 messages on an SNS topic and let AWS handle how many consumers are needed (perhaps it can reuse consumer lambdas). Other ways include triggering from records inserted into DynamoDB.
If you want the listeners to pull messages from an SQS queue you'll need to trigger them yourself, which you can do with CloudWatch (maximum 1 trigger per minute)
If the number of lambdas which are getting spawned are more than 1000 Qn: Will it fail?
Yes it will Fail. But you can increase the default limits(1000) to n numbers based on region by requesting AWS Customer Support.
http://docs.aws.amazon.com/lambda/latest/dg/limits.html
http://docs.aws.amazon.com/lambda/latest/dg/concurrent-executions.html
I am not sure about your exact requirements. Based on your requirements you need to make sure spawning 1000 lambdas is required in your design.
My suggestions are below
Suggestion 1:-
AWS Step Functions
By AWS Step Functions you can invoke your child lambda from master using state machine language. Based on how your master lambda invoked.(ex: Cloudwatch rules, Triggers). For more information goto:-
https://aws.amazon.com/step-functions/
https://states-language.net/spec.html
Suggestion 2:-
AWS ECS Container
From Master Lambda Send Messages to SQS. Launch your child program as ECS Container Service. In Program, you can consume your SQS Messages and Solve your business logic.
http://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs_services.html
Related
My requirement is like this.
Read from a SQS every 2 hours, take all the messages available and then process it.
Processing includes creating a file with details from SQS messages and sending it to an sftp server.
I implemented a AWS Lambda to achieve point 1. I have a Lambda which has an sqs trigger. I have set batch size as 50 and then batch window as 2 hours. My assumption was that Lambda will get triggered every 2 hours and 50 messages will be delivered to the lambda function in one go and I will create a file for every 50 records.
But I observed that my lambda function is triggered with varied number of messages(sometimes 50 sometimes 20, sometimes 5 etc) even though I have configured batch size as 50.
After reading some documentation I got to know(I am not sure) that there are 5 long polling connections which lambda spawns to read from SQS and this is causing this behaviour of lambda function being triggered with varied number of messages.
My question is
Is my assumption on 5 parallel connections being established correct? If yes, is there a way I can control it? I want this to happen in a single thread / connection
If 1 is not possible, what other alternative do I have here. I do not want to have one file created for every few records. I want one file to be generated every two hours with all the messages in sqs.
A "SQS Trigger" for Lambda is implemented with the so-called Event Source Mapping integration, which polls, batches and deletes messages from the queue on your behalf. It's designed for continuous polling, although you can disable it. You can set a maximum batch size of up to 10,000 records a function receives (BatchSize) and a maximum of 300s long polling time (MaximumBatchingWindowInSeconds). That doesn't meet your once-every-two-hours requirement.
Two alternatives:
Remove the Event Source Mapping. Instead, trigger the Lambda every two hours on a schedule with an EventBridge rule. Your Lambda is responsible for the SQS ReceiveMessage and DeleteMessageBatch operations. This approach ensures your Lambda will be invoked only once per cron event.
Keep the Event Source Mapping. Process messages as they arrive, accumulating the partial results in S3. Once every two hours, run a second, EventBridge-triggered Lambda, which bundles the partial results from S3 and sends them to the SFTP server. You don't control the number of Lambda invocations.
Note on scaling:
<Edit (mid-Jan 2023): AWS Lambda now supports SQS Maximum Concurrency>
AWS Lambda now supports setting Maximum Concurrency to the Amazon SQS event source, a more direct and less fiddly way to control concurrency than with reserved concurrency. The Maximum Concurrency setting limits the number of concurrent instances of the function that an Amazon SQS event source can invoke. The valid range is 2-1000 concurrent instances.
The create and update Event Source Mapping APIs now have a ScalingConfig option for SQS:
aws lambda update-event-source-mapping \
--uuid "a1b2c3d4-5678-90ab-cdef-11111EXAMPLE" \
--scaling-config '{"MaximumConcurrency":2}' # valid range is 2-1000
</Edit>
With the SQS Event Source Mapping integration you can tweak the batch settings, but ultimately the Lambda service is in charge of Lambda scaling. As the AWS Blog Understanding how AWS Lambda scales with Amazon SQS standard queues says:
Lambda consumes messages in batches, starting at five concurrent batches with five functions at a time. If there are more messages in the queue, Lambda adds up to 60 functions per minute, up to 1,000 functions, to consume those messages.
You could theoretically restrict the number of concurrent Lambda executions with reserved concurrency, but you would risk dropped messages due to throttling errors.
You could try to set the ReservedConcurrency of the function to 1. That may help. See the docs for reference.
A simple solution would be to create a CloudWatch Event Trigger (similar to a Cronjob) that triggers your Lambda function every two hours. In the Lambda function, you call ReceiveMessage on the Queue until you get all messages, process them and afterward delete them from the Queue. The drawback is that there may be too many messages to process within 15 minutes so that's something you'd have to manage.
I have an AWS Lambda function to read from an SQS queue. The lambda logic is basically to read off one message from SQS and then it processes and deletes the message. Code to read the message being something like.
ReceiveMessageRequest messageRequest =
new ReceiveMessageRequest(queueUrl).withWaitTimeSeconds(5).withMaxNumberOfMessages(1);
Now my question is what is the best way to trigger this lambda and how does this lambda scale for instance, if there are let's say 1000 messages in the queue so will there be a 1000 lambdas running together, since in my case one lambda can read only one message off the queue.
Any pointers on best practices around this kind of design.
Right now you best option is probably to setup an AWS Cloudwatch event rule that calls the lambda function on the interval that you need.
Here is a sample app from AWS to do just that:
https://github.com/awslabs/aws-serverless-sqs-event-source
I do believe that AWS will eventually support SQS as a event type for AWS lambda, which should make this even easier, but for now you best choice is probably a version of the code I linked above.
We can now use SQS messages to trigger AWS Lambda Functions. Moreover, no longer required to run a message polling service or create an SQS to SNS mapping.
Further details:
https://aws.amazon.com/blogs/aws/aws-lambda-adds-amazon-simple-queue-service-to-supported-event-sources/
https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html
AWS added native support in June 2018: https://aws.amazon.com/blogs/aws/aws-lambda-adds-amazon-simple-queue-service-to-supported-event-sources/
There are probably a few ways to do this, but I found this guide to be fairly helpful when I tried to implement the same sort of functionality you are describing in Node.js. One downside to this strategy is that you can only poll the queue every 60s.
The basic workflow would look something like this:
Set up a CloudWatch Alarm that gets triggered when the queue has a certain number of messages.
The Cloudwatch alarm then posts to SNS
The SNS message triggers a Lambda scale() function
The scale() function updates a configuration record in a DynamoDB table that sets the number of worker processes needed
You then have a main CloudWatch Schedule that invokes a worker() function every 60s
The worker() function reads configuration from DynamoDB to determine how many concurrent processes are needed, based on the queue size.
Worker() then invokes the appropriate number of process() functions
Process() function consumes messages from SQS, performs your main application logic, and then removes the item from the queue.
You can find an example of what the scaling functions would look like in Node.js here
I have used this solution in a production environment for almost a year without any issues, even with thousands of messages in the queue. If you cut out the scaling portion it is only going to do one message a time.
I'm using an AWS Lambda function that is triggered from an SNS event trigger to consume from an SQS queue. When the Lambda function executes, it pulls 10 messages from the queue, processes them, pulls another 10, and so on and so forth - up to a certain time limit that's coded into the Lambda function (less than the max of 5 minutes, obviously).
It's my understanding that a Lambda function triggered by an SNS event is one-to-one, is that correct? In other words, one SNS event won't trigger multiple Lambda functions (up to the maximum concurrent execution limit). There's no scaling based on load.
Are there any other potential solutions, leveraging Lambda, that would let me consume from SQS as frequently/fast as possible? I had considered trying to auto-scale my Lambda functions by leveraging CloudWatch alarms (and SNS event triggers) based on SQS queue size, but it seems like those alarms can fire, at most, every 5 minutes. I've also considered developing a master Lambda function that can automatically execute (many) slave Lambdas based on querying the queue size.
I understand that the more optimal design may be to leverage Kinesis instead of SNS. I may consider incorporating Kinesis in the future, but let's just pretend that Kinesis is not an option at this time.
There is no best way to do this. One approach (which you've kind of already mentioned) is to use CloudWatch and schedule a Lambda function to run every minute (that's the minimum schedule time for Lambda). This Lambda function will then look for new SQS messages and invoke other Lambda functions to handle new message(s). Here is a very good article for that use case: https://cloudonaut.io/integrate-sqs-and-lambda-serverless-architecture-for-asynchronous-workloads/
Personally, I do not recommend triggering your Lambda by SNS for this use case, because SNS doesn't give a full guarantee for delivery and recommend sending the SNS notifications to SQS - which does not solve your problem. From the FAQ's:
[...] If it is critical that all published messages be successfully processed, developers should have notifications delivered to an SQS queue (in addition to notifications over other transports).
Source: https://aws.amazon.com/sns/faqs/
For this kind of processing, instead of SQS if you push messages to Kinesis Stream you should be able to flexibly process(In batches of needed size) the messages.
Note: If you use SQS, after triggering a Lambda function through SNS (or using a Scheduled Lambda), it can invoke inner Lambda functions to check the queue where multiple concurrent inner Lambdas are spawned. However the problem is that its not practical to process SQS items in batches.
I have a Lambda function that’s triggered by a PUT to an S3 bucket.
I want to limit this Lambda function so that it’s only running one instance at a time – I don’t want two instances running concurrently.
I’ve had a look through the Lambda configuration and docs, but I can’t see anything obvious. I can about writing my own locking system, but it would be nice if this was already a solved problem.
How can I limit the number of concurrent invocations of a Lambda?
AWS Lambda now supports concurrency limits on individual functions:
https://aws.amazon.com/about-aws/whats-new/2017/11/set-concurrency-limits-on-individual-aws-lambda-functions/
I would suggest you to use Kinesis Streams (or alternatively DynamoDB + DynamoDB Streams, which essentially have the same behavior).
You can see Kinesis Streams as as queue. The good part is that you can use a Kinesis Stream as a Trigger to you Lambda function. So anything that gets inserted into this queue will automatically be passed over to your function, in order. So you will be able to process those S3 events one by one, one Lambda execution after the other (one instance at a time).
In order to do that, you'll need to create a Lambda function with the simple purpose of getting S3 Events and putting them into a Kinesis Stream. Then you'll configure that Kinesis Stream as your Lambda Trigger.
When you configure the Kinesis Stream as your Lambda Trigger I suggest you to use the following configuration:
Batch size: 1
This means that your Lambda will be called with only one event from Kinesis. You can select a higher number and you'll get a list of events of that size (for example, if you want to process the last 10 events in one Lambda execution instead of 10 consecutive Lambda executions).
Starting position: Trim horizon
This means it'll behave as a queue (FIFO)
A bit more info on AWS May Webinar Series - Streaming Data Processing with Amazon Kinesis and AWS Lambda.
I hope this helps anyone with a similar problem.
P.S. Bear in mind that Kinesis Streams have their own pricing. Using DynamoDB + DynamoDB Streams might be cheaper (or even free due to the non-expiring Free Tier of DynamoDB).
No, this is one of the things I'd really like to see Lambda support, but currently it does not. One of the problems is that if there were a lot of S3 PUT operations happening AWS would have to queue up all the Lambda invocations somehow, and there is currently no support for that.
If you built a locking mechanism into your Lambda function, what would you do with the requests you don't process due to a lock? Would you just throw those S3 notifications away?
The solution most people recommend is to have S3 send the notifications to an SQS queue, and then have your Lambda function scheduled to run periodically, like once a minute, and check if there is an item in the queue that needs to be processed.
Alternatively, have S3 send the notifications to SQS and just have a t2.nano EC2 instance with a single-threaded service polling the queue.
I know this is an old thread, but I ran across it trying to figure out how to make sure my time sequenced SQS messages were processed in order coming out of a FIFO queue and not getting processed simultaneously/out-of-order via multiple Lambda threads running.
Per the documentation:
For FIFO queues, Lambda sends messages to your function in the order
that it receives them. When you send a message to a FIFO queue, you
specify a message group ID. Amazon SQS ensures that messages in the
same group are delivered to Lambda in order. Lambda sorts the messages
into groups and sends only one batch at a time for a group. If your
function returns an error, the function attempts all retries on the
affected messages before Lambda receives additional messages from the
same group.
Your function can scale in concurrency to the number of active message
groups.
Link: https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html
So essentially, as long as you use a FIFO queue and submit your messages that need to stay in sequence with the same MessageGroupID, SQS/Lambda automatically handles the sequencing without any additional settings necessary.
Have the S3 "Put events" cause a message to be placed on the queue (instead of involving a lambda function). The message should contain a reference to the S3 object. Then SCHEDULE a lambda to "SHORT POLL the entire queue".
PS: S3 events can not trigger a Kinesis Stream... only SQS, SMS, Lambda (see http://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html#supported-notification-destinations). Kinesis Stream are expensive and used for real-time event handling.
I have the following infrastructure:
I have an EC2 instance with a NodeJS+Express process listening on a port for messages (process 1). Every time the process receives a message it sends it to an SQS queue. Then I have another process in the same machine reading the queue using long polling (process 2). When it finds a message in the queue it inserts the data in a MariaDB database sitting on an RDS instance.
(Just to clarify, messages are generated by users, they send a chunk of data which can contain arbitrary information to the endpoint where the process 1 is listening)
Now I want to put the process that reads the SQS (process 2) in a Lambda function so that the process that writes to the queue and the one that reads from the queue are completely independent. The problem is that I don't know if this is possible.
I know that Lambda function are invoked in response to an event, and the events supported at the moment are S3, SNS, SES, DynamoDB, Kinesis, Cognito, CloudWatch and Cloudformation but NOT SQS.
I was thinking in using SNS notifications to invoke the Lambda function so that every time a message is pushed to the queue, an SNS notification is fired and invokes the Lambda function but after playing a bit with it I've realised that is not possible to create an SNS notification from SQS, it's only possible to write SNS notifications to the queue.
Right now I'm a bit stuck because I don't know how to continue. I have the feeling that is not possible to create this infrastructure due to the current limitations in the AWS services. Is there another way to do what I want or am I in a dead-end?
Just to extend my question with some research I've made, this github repo shows how to read an SQS queu from a Lambda function but the lambda function works only if is fired from the command line:
https://github.com/robinjmurphy/sqs-to-lambda
In the readme, the author mentions the following:
Update: Lambda now supports SNS notifications as an event source,
which makes this hack entirely unneccessary for SNS notifcations. You
might still find it useful if you like the idea of using a Lambda
function to process jobs on an SQS queue.
But I think this doesn't solve my problem, an SNS notification can invoke the Lambda function but I don't see how I can create a notification when a message is received in the SQS queue.
Thanks
There are couple of Strategies which can be used to connect the dots, (A)Synchronously or Run-Sleep-Run to keep the data process flow between SNS, SQS, Lambda.
Strategy 1 : Have a Lambda function listen to SNS and process it in real time [Please note that an SQS Queue can subscribe to an SNS Topic - which would may be helpful for logging / auditing / retry handling]
Strategy 2 : Given that you are getting data sourced to SQS Queue. You can try with 2 Lambda Functions [Feeder & Worker].
Feeder would be scheduled lambda function whose job is to take items
from SQS (if any) and push it as an SNS topic (and continue doing it forever)
Worker would be linked to listen the SNS topic which would do the actual data processing
We can now use SQS messages to trigger AWS Lambda Functions. Moreover, no longer required to run a message polling service or create an SQS to SNS mapping.
Further details:
https://aws.amazon.com/blogs/aws/aws-lambda-adds-amazon-simple-queue-service-to-supported-event-sources/
AWS SQS is one of the oldest products of Amazon, which only supported polling (long and short) up until June 2018. As mentioned in this answer, AWS SQS now supports the feature of triggering lambda functions on new message arrival in SQS. A complete tutorial for this is provided in this document.
I used to tackle this problem using different mechanisms, and given below are some approaches you can use.
You can develop a simple polling application in Lambda, and use AWS CloudWatch to invoke it every 5 mins or so. You can make this near real-time by using CloudWatch events to invoke lambda with short downtimes. Use this tutorial or this tutorial for this purpose. (This could cost more on Lambdas)
You can consider that SQS is redundant if you don't need to persist the messages nor guarantee the order of delivery. You can use AWS SNS (Simple Notification Service) to directly invoke a lambda function and do whatever the processing required. Use this tutorial for this purpose. This will happen in real-time. But the main drawback is the number of lambdas that can be initiated per region at a given time. Please read this and understand the limitation before following this approach. Nevertheless AWS SNS Guarantees the order of delivery. Also SNS can directly call an HTTP endpoint and store the message in your DB.
I had a similar situation (and now have a working solution deploed). I have addressed it in a following manner:
i.e. publishing events to SNS; which then get fanned-out to Lambda and SQS.
NOTE: This is not applicable to the events that have to be processed in a certain order.
That there are some gotchas (w/ possible solutions) such as:
racing condition: lambda might get invoked before messages is deposited into the queue
distributed nature of SQS queue may lead to returning no messages even though there is a message note1.
The solution to both cases would be to do long-polling of SQS queue; but this does make your lambda bill more expensive.
note1
Short poll is the default behavior where a weighted random set of machines is sampled on a ReceiveMessage call. This means only the messages on the sampled machines are returned. If the number of messages in the queue is small (less than 1000), it is likely you will get fewer messages than you requested per ReceiveMessage call. If the number of messages in the queue is extremely small, you might not receive any messages in a particular ReceiveMessage response; in which case you should repeat the request.
http://docs.aws.amazon.com/AWSSimpleQueueService/latest/APIReference/API_ReceiveMessage.html
We had some similar requirements so we ended up building a library and open sourcing it to help with SQS to Lambda async. I'm not sure if this fills your particular set of requirements, but thought it might be worth a look: https://read.iopipe.com/sqs-lambda-teaming-up-92c4096be49c