I want to use SQS for calling Lambda.
An execution time of lambda function is 3 minutes.
I want to execute 1000 lambda functions at once, so I send 1000 messages to SQS queue
But according to an AWS documentation
Amazon Simple Queue Service supports an initial burst of 5 concurrent function invocations and increases concurrency by 60 concurrent invocations per minute.
https://docs.aws.amazon.com/en_us/lambda/latest/dg/scaling.html
So I should wait a few minutes until all messages will be processed. Is there any workaround to call 1000 concurrent lambda and avoid "cold start"?
UPD: I got answer from AWS support
You are correct that SQS will start at an initial burst of 5 and
increase by a concurrency of 60 per minute. Scaling rates can't be
increased
If you see the Automatic Scaling section of the documentation page that describes the autoscaling behaviour under sudden load. I don't think cold start would be a problem. The first batch of concurrent Lambdas executions would likely see the cold start and all the subsequent invocations would be fine.
Related
I have a lambda function that is triggered by an sqs queue . I set batch size to 1 because I want each message to map to one lambda instance to benefit from concurrency and finish processing faster.
However,after some trials with 1000 messages available in sqs queue max concurrent execution only reachs 50 although I reserve 1000 concurrency for my function.
Is there a reason behind this behavior
One reason could be that your functions finish quickly. Thus there is no reason to span 1000 concurrent functions. Lambda polls the sqs at fixed intervals, so you can just span 1000 concurrent invocations in an instance. Similarly, lambda does not scale to 1000 in an instant. Please read the following for more details:
Understanding how AWS Lambda scales with Amazon SQS standard queues
I've seen a number of SO questions on limiting Lambda concurrent execution but none on the inverse issue.
I need to increase my concurrent execution but am having issues. I've got a Lambda triggered off an SQS queue. I've published a version of the function and assigned it 3,000 concurrent execution (my limit has been increased to 5,000 from the default of 1,000).
Despite this, when I run my process I see hundreds of thousands of messages waiting in the queue while the Monitoring tab of my Lambda function shows my "Concurrent executions" never going above 1,250 and my "ProvisionedConcurrencyUtilization" never going above 50%. Moreover, the chart seems to imply a hard limit of 1,250.
I'd be inclined to suspect that there is some sort of limit preventing any single Lambda from using more than 25% of total provisioned capacity (1,250 is 25% of 5,000) but the AWS documentation states otherwise. I did see this SO question (AWS Lambda Triggered by SQS increases SQS request count) which discusses Labmda/SQS polling but it and the documentation it links to indicate my process should use 100% of the Provisioned Capacity. But perhaps it's the polling that's causing the issue.
In any event, these messages sit in the queue for over an hour to process ... with never more than 1,250 processing at the same time ... while the reset of that provisioned concurrency sits idle.
Any suggestions/ideas are greatly appreciated.
Jelly's suggestion was a good one.
Unfortunately, AWS says there is a hard limit of 1,250 Lambda concurrent executions when using Amazon SQS trigger.
I have a AWS Lambda function that I invoke with every 1 minute with >1000 SNS events. This is a problem because my account concurrency is set at 3000, so if I start adding more jobs then eventually I'm going to have >3000 concurrent Lambda instances.
Each job takes around 2-5 seconds to complete which means that within each 1 minute window the concurrency limit will only be threatened within the first 5 seconds and I'll have 0 concurrency for the remaining 55 seconds.
If I set a concurrency limit (e.g. 1000) for the lambda will it handle the first 1000 SNS events and then automatically pick up the remainder once the concurrency frees up? And will I only be charged for the actual runtime rather than time spent waiting for concurrency to reduce?
Otherwise, is there a way that AWS will allow me to spread the load of jobs throughout the 1 minute window so that I can invoke the lambda every ~5 seconds with a subset of the total number of jobs?
If I set a concurrency limit (e.g. 1000) for the lambda will it handle the first 1000 SNS events and then automatically pick up the remainder once the concurrency frees up? And will I only be charged for the actual runtime rather than time spent waiting for concurrency to reduce?
Yes. Setting the concurrency limit definitely comes in handy on your use case and is the way to go. This is one of the reasons why concurrency limit actually exists :)
Unfortunately you can't take advantage of batching with SNS because it always sends one and only event. What you could do is to hook up a SQS queue with your SNS topic and have the Lambda function subscribe to the SQS queue instead, then you can take advantage of batching (max batch size is 10), greatly reducing the amount of concurrent Lambda executions, but still, you'd need to set a concurrency limit to make sure you don't use up all the available concurrency.
Otherwise, is there a way that AWS will allow me to spread the load of jobs throughout the 1 minute window so that I can invoke the lambda every ~5 seconds with a subset of the total number of jobs?
No, but this is unnecessary because of the above.
I have 20K message in SQS queue. I also have a lambda will process the SQS messages, and put data into ElasticSearch server.
I have configured SQS as the lambda's trigger, and limited the Lambda's SQS batch size to be 10. I also limited the only one instance of the lambda can be run at a giving time.
However, sometime I see over 10K in-flight messages from the AWS console. Should it be max at 10 in-flight messages?
Because of this, the lambdas will only able to process 9K of the SQS message properly.
Below is a screen capture to show that I have limited the lambda to have only 1 instance running at a giving time.
I've been doing some testings and contacting AWS tech support at the same time.
What I do believe at the moment is that:
Amazon Simple Queue Service supports an initial burst of 5 concurrent function invocations and increases concurrency by 60 concurrent invocations per minute. Doc
1/ The thing that does that polling, is a separate entity. It is most likely to be a lambda function that will long-poll the SQS and then, invoke our lambda functions.
2/ That polling Lambda does not take into account any of our Receiver-Lambda at all. It does not care whether the function is running at max capacity or not, or how many max concurrency is available for the Receiver-Lambda
3/ Due to that combination. The behavior is not what we expected from the Lambda-SQS integration. And worse, If you have suddenly, millions of message burst in your queue. The Receiver-Lambda concurrency can never catch up with the amount of messages that the polling Lambda is sending, result in loss of work
The test:
Create one Lambda function that takes 30 seconds to return true;
Set that function's concurrency to 50;
Push 300 messages into the queue ( Visibility timeout : 10 Minutes, batch message count: 1, no re-drive )
The result:
Amount of messages available just increase gradually
At first, there are few enough messages to be processed by Receiver-Lambda
After half a minute, there are more messages available than what Receiver-Lambda can handle
These message would be discarded to dead queue. Due to polling Lambda unable to invoke Receiver-Lambda
I will update this answer as soon as I got the confirmation from AWS support
Support answer. As of Q1 2019, TL;DR version
1/ The assumption was correct, there was a "Poller"
2/ That Poller do not take into consideration of reserved concurrency
as part of its algorithm
3/ That poller have hard limit of 1000
Q2-2019 :
The above information need to be updated. Support said that the poller correctly consider reserved concurrency but it should be at least 5. The SQS-Lambda integration is still being updated and this answer will not. So please consult AWS if you get into some weird issues
Lambda has a 100 function limit.
What happens when you submit a 101 function when 100 are already running?
Will it:
fail with an error
queue up
If you are talking about Concurrent executions there isn't a limit of 100. The limit depends on the region but by default it's 1000 Concurrent executions.
To answer your question: As soon as the Concurrent executions limit is reached the next execution gets throttled. Each throttled invocation increases the Amazon CloudWatch Throttles metric for the function.
If your AWS Lambda is invoked asynchronous AWS Lambda automatically retries the throttled event for up to six hours, with delays between retries. If you didn't setup a Dead Letter Queue (DLQ) for your AWS Lambda your event is lost as soon as all retries fails.
For more information please check the AWS Lambda - Throttling Behavior
If the function doesn't have enough concurrency available to process all events, additional requests are throttled. For throttling errors (429) and system errors (500-series), Lambda returns the event to the queue and attempts to run the function again for up to 6 hours. The retry interval increases exponentially from 1 second after the first attempt to a maximum of 5 minutes. However, it might be longer if the queue is backed up. Lambda also reduces the rate at which it reads events from the queue.
As mentioned here.