I'm trying to implement a worker queue to handle burst of messages. Every few days/weeks I get a burst of ~5,000 messages that need to be processed in a reasonable time (each message can be proceeded in about 1-2 min). Ideally if I could run 5,000 lambdas simultaneous the whole process should take 1-2 min but my account is limit to 1,000 concurrency lambda.
I was planning to create an SQS as event source to lambda but I can't see any Throttling mechanism? I can set reserved concurrency on the lambda but it will be deducted from my account limit and it sound "expensive" to keep those lambda idle for an event that can occur only one per few weeks.
Is there a way to throttling SQS? or maybe I need to choose other service to implement such queue?
In that case, the reserved concurrency is the way to limit number of your lambda functions that can run at the same time:
Reserved concurrency – Reserved concurrency creates a pool of requests that can only be used by its function, and also prevents its function from using unreserved concurrency.
It does not cost extra. I think you are confusing reserved concurrency with provisioned concurrency:
When enabled, Provisioned Concurrency keeps functions initialized and hyper-ready to respond in double-digit milliseconds.
Related
I've set a Lambda trigger with a SQS Queue. Lambda's reserved concurrency is set to 1000. However, there are millions of messages waiting in the queue need to be processed and it only invokes around 50 Lambdas at the same time. Ideally, I want SQS to trigger 1000 (or close to 1000) Lambda functions concurrently. Do I miss any configuration in SQS or Lambda? Thank you for any suggestion.
As stated in AWS Lambda developer guide:
...Lambda increases the number of processes that are reading batches by up to 60 more instances per minute. The maximum number of batches that an event source mapping can process simultaneously is 1,000.
So the behavior that you encountered (only invokes around 50 Lambdas at the same time) is actually expected.
If you are not using already, I would suggest doing batch processing in your lambda (so you can process 10 messages per invocation). If that is still not enough, you can potentially create more queues and lambdas to divide your load (considering that order is not relevant in your case), or move away from it and start polling the queue directly with EC2/ECS (which can increase your costs considerably however).
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 am invoking a data processing lambda in bulk fashion by submitting ~5k sns requests in an asynchronous fashion. This causes all the requests to hit sns in a very short time. What I am noticing is that my lambda seems to have exactly 5k errors, and then seems to "wake up" and handle the load.
Am I doing something largely out of the ordinary use case here?
Is there any way to combat this?
I suspect it's a combination of concurrency, and the way lambda connects to SNS.
Lambda is only so good at automatically scaling up to deal with spikes in load.
Full details are here: (https://docs.aws.amazon.com/lambda/latest/dg/scaling.html), but the key points to note that
There's an account-wide concurrency limit, which you can ask to be
raised. By default it's much less than 5k, so that will limit how
concurrent your lambda could ever become.
There's a hard scaling limit (+1000 instances/minute), which means even if you've managed to convince AWS to let you have a concurrency limit of 30k, you'll have to be under sustained load for 30 minutes before you'll have that many lambdas going at once.
SNS is a non-stream-based asynchronous invocation (https://docs.aws.amazon.com/lambda/latest/dg/invoking-lambda-function.html#supported-event-source-sns) so what you see is a lot of errors as each SNS attempts to invoke 5k lambdas, but only the first X (say 1k) get through, but they keep retrying. The queue then clears concurrently at your initial burst (typically 1k, depending on your region), +1k a minute until your reach maximum capacity.
Note that SNS only retries three times at intervals (AWS is a bit sketchy about the intervals, but it is probably based on the retry: delay the service returns, so should be approximately intelligent); I suggest you setup a DLQ to make sure you're not dropping messages because the time for the queue to clear.
While your pattern is not a bad one, it seems like you're very exposed to the concurrency issues that surround lambda.
An alternative is to use a stream based event-source (like Kinesis), which processes in batches at a set concurrency (e.g. 500 records per lambda, concurrent by shard count, rather than 1:1 with SNS), and waits for each batch to finish before processing the next.
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