![]() Do you want a delay or queue here to accommodate for failure so you can retrieve them at a later point? So it’ll retry by putting that message back in the queue for I believe up to three or five retries before finally putting it to the DLC. ![]() SQS -> Lambda = Eventual failures: This follows the same principles of the Asynchronous invitation that I just spoke about. But if you don’t have that, this message can be potentially lost forever. Now, if you have a dead letter Q, a DLQ configured on this account, that message can be sent to a dead letter Q where you can kind of pick it up and redirect it at a later point in time. Now it will automatically retry for, I believe, three times. Now, if when it pulls the queue and it attempts to process that request, your concurrency limit is hit, it will fail and it’ll put that message back into the queue. Manual (Sync) = Eventual failures: So different behavior actually and the way this one works is that when an asynchronous invocation is made against your Lambda function, Lambda will put the instance or the metadata about that invocation in an internal queue, and Lambda will pull that queue internally to process that request. Maybe you sleep for 100, so you can do some kind of exponential backoff here and attempt multiple times before throwing some kind of permanent exception back to your client. If you fail again, you back off a little bit more. So you sleep for 50 milliseconds and then you try again. Now, typically, how people handle these types of exceptions are in your actual logic in your code If you receive a throttling exception, you can back off for some time or sleep the thread that’s making the call. Manual (Sync) = Immediate failures: If a Rest API is trying to hit a Lambda function synchronously to get a response, it will receive a throttling exception. Now, if you have a retry policy that’s configured on your SNS topic, SNS will try to invoke your Lambda function for some time, but it can’t guarantee that it will eventually succeed. When SNS will try and invoke your Lambda function, if your throttling limit is hit, it will receive a throttling exception. SNS -> Lambda = Immediate failures: It’s one of the more common ones, the common setups that we typically use, and this results in immediate failures. Handling by Event Source & Invocation Type So this is truly the danger of throttling using the default configuration. You can have scenarios where a high burst of traffic to one part of your application can have some cascading effects on other portions of your application. That means that a sudden burst of traffic to function one can start to result in throttling when new requests come in for function two and function three.Īnd this is the kind of problem with throttling. Function two is for another function three is for another. What we’re saying here is that the concurrency limit, the pool of concurrency is shared across all of your Lambda functions that are within the same account and within the same region. They all have different behaviors when encountering throttling exceptions. But it does get a little bit more complicated in terms of how this rule applies when you have multiple Lambda functions in the same region and the same account.ĭepending on the invocation event source, whether it’s manual, SQS, SMS, Kinesis, Dynamo, or something else. What are the configure limits? Lambda has a default 1000 concurrency limit that’s specified per region within an account. ![]() So assume we’re at a particular instant in time if you have more invocations that are running that exceed your configured limit, all new requests to your Lambda function will get a throttling exception. Now, just as a reminder, if this wasn’t clear, Lambda can handle multiple instance invocations at the same time and the sum of all of those invocations amounts to your concurrency execution count. why does it occur? Throttling occurs when your concurrent execution count exceeds your concurrency limit. But there are also some different mechanisms that you can use, so that’s interesting, Lambda will reject your request. Typically, people handle this by backing off for some time and retrying. What is throttling and why does it happen?Īt the highest level, throttling just means that Lambda will intentionally reject one of your requests and so what we see from the user side is that when making a client call, Lambda will throw a throttling exception, which you need to handle.
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