I have one use case where I am supposed to execute a piece of code based on idle time of a given lambda function, I mean if given function has been idle for say 5 mins, my piece of code should run.
Is there any way to check the lambda state/status?
I assume you are looking to avoid lambda cold starts, please leverage Provisioned Concurrency which will have lambda running up with the amount of concurrency setup
https://aws.amazon.com/blogs/aws/new-provisioned-concurrency-for-lambda-functions/
If you did not mean this, then I assume idleness as "no requests processed" by lambda, if yes, then use cloudwatch metric/alarm to monitor # of invocations over a timeframe and then do whatever in its action
I have a Lambda function(written in java) which was scheduled to execute every 15mins and it will run for next 15 mins( as this is the highest value for lambda timeout). So this is how the architecture looks: CloudwatchEvent(every 15mins) -----> Lambda(Runs for 15mins)
I have removed the cloudwatch event from lambda console but still I can see it has been invoked for few hours every 15 mins. Is this a bug or some architectural concept issue?
Thanks
On my project there is REST API which implemented on AWS API Gateway and AWS Lambda. As AWS Lambda functions are serverless and stateless while we make a call to it, AWS starts a container with code of the Lambda function which process our call. According AWS documentation after finishing of lambda function execution AWS don't stop the container and we are able to process next call in that container. Such approach improves performance of the service - only in time of first call AWS spend time to start container (cold start of Lambda function) and all next calls are executed faster because their use the same container (warm starts).
As a next step for improving the performance we created cron job which calls periodically our Lambda function (we use Cloudwatch rules for that). Such approach allow to keep Lambda function "warm" allowing to avoid stopping and restarting of containers. I.e. when the real user will call our REST API, Lambda will not spent time to start a new container.
But we faced with the issue - such approach allow to keep warm only one container of Lambda function while the actual number of parallel calls from different users can be much larger (in our case that's hundreds and sometimes even thousands of users). Is there any way to implement warm up functionality for Lambda function which could warm not only single container, but some desired number of them?
I understand that such approach can affect cost of Lambda function's using and possibly, at all it will be better to use good old application server, but comparison of these approaches and their costs will be the next steps, I think, and in current moment I would like just to find the way to warm desired count of Lambda function containers.
This can be long but bear with me as this would probably give you workaround and may be would make you understand better How Lambda Works ?
Alternatively You can Skip to Bottom "The Workaround" if you are not interested in reading.
For folks who are not aware about cold starts please read this blog post to better understand it. To describe this in short:
Cold Starts
When a function is executed for the first time or after having the
functions code or resource configuration updated, a container will be
spun up to execute this function. All the code and libraries will be
loaded into the container for it to be able to execute. The code will
then run, starting with the initialisation code. The initialisation
code is the code written outside the handler. This code is only run
when the container is created for the first time. Finally, the Lambda
handler is executed. This set-up process is what is considered a cold
start.
For performance, Lambda has the ability to re-use containers created
by previous invocations. This will avoid the initialisation of a new
container and loading of code. Only the handler code will be
executed. However, you cannot depend on a container from a previous
invocation to be reused. if you haven’t changed the code and not too
much time has gone by, Lambda may reuse the previous container.
If you change the code, resource configuration or some time has
passed since the previous invocation, a new container will be
initialized and you will experience a cold start.
Now Consider these scenarios for better understanding:
Consider the Lambda function, in the example, is invoked for the first time. Lambda will create a container, load the code into the container and run the initialisation code. The function handler will then be executed. This invocation will have experienced a cold start. As mentioned in the comments, the function takes 15 seconds to complete. After a minute, the function is invoked again. Lambda will most likely re-use the container from the previous invocation. This invocation will not experience a cold start.
Now consider the second scenario, where the second invocation is executed 5 seconds after the first invocation. Since the previous function takes 15 seconds to complete and has not finished executing, the new invocation will have to create a new container for this function to execute. Therefore this invocation will experience a cold start.
Now to Come up First Part of Problem that you have solved :
Regarding preventing cold starts, this is a possibility, however, it is not guaranteed, the common workaround will only keep warm one container of the Lambda function. To do, you would run a CloudWatch event using a schedule event (cron expression) that will invoke your Lambda function every couple of minutes to keep it warm.
The Workaround:
For your use-case, your Lambda function will be invoked very frequently with a very high concurrency rate. To avoid as many cold starts as possible, you will need to keep warm as many containers as you expect your highest concurrency to reach. To do this you will need to invoke the functions with a delay to allow the concurrency of this function to build and reach the desired amount of concurrent executions. This will force Lambda to spin up the number of containers you desire. This, as a result, can bring up costs and will not guarantee to avoid cold starts.
That being said, here is a break down on how you can keep multiple containers for your function warm at one time:
You should have a CloudWatch Events Rule that is triggered on a schedule. This schedule can be a fixed rate or a cron expression. for example, You can set this rule to trigger every 5 minutes. You will then specify a Lambda function (Controller function) as the target of this rule.
Your Controller Lambda function will then invoke the Lambda function (Function that you want to be kept warm) for as many concurrent running containers as you desire.
There are a few things to consider here:
You will have to build concurrency because if the first invocation
is finished before another invocation starts then this invocation
may reuse the previous invocations container and not create a new
one. To do this you will need to add some sort of delay on the
Lambda function if the function is invoked by the controller
function. This can be done by passing in a specific payload to
the function with these invocations. The lambda function that you
want to be kept warm will then check if this payload exists. If
it does then the function will wait (to build concurrent
invocations), if it does not then the function can execute as
expected.
You will also need to ensure you are not getting throttled on the Invoke Lambda API call if you are calling it repeatedly. Your
Lambda
function should be written to handle this throttling if it occurs
and consider adding a delay between API calls to avoid throttling.
At the End this solution can reduce cold starts but it will increase costs and will not guarantee that cold starts will occur as they are inevitable when working with Lambda.If your application needs faster response times then what occurs with a Lambda cold start, I would recommend looking into having your server on a EC2 instance.
We are using java (spring boot) lambdas and have come to pretty much an identical solution as Kush Vyas's answer above which works very well.
We did find during load testing, however, that a legitimate user request would often occur during the period that the "Controller function" was executing, again causing the inevitable cold start...
So, now in our "Controller function", we have our regular number of X concurrent warm-up requests, however every 5th execution of the function we call our target lambda an additional 2 times. Theory being that we will end up with X+2 lambdas staying warm, but for 4 out of 5 warm up calls there will still be 2 redundant lambdas that can service user requests.
It did reduce our number of cold starts even further (but obviously still not completely) and we are still playing with concurrency/frequency of warm-ups/sleep-time combinations to find optimum solution for us - these values will always likely be dependent on load requirements for a specific situation.
AWS just announced this:
https://aws.amazon.com/about-aws/whats-new/2019/12/aws-lambda-announces-provisioned-concurrency/
Be aware though that it is not free and for our simple use case of keeping 10 lambda instances warm it seems our daily cost would increase from $0.06 to $4
If you use the serverless framework with AWS Lambda, you can use this plugin to keep all your lambdas warm with a certain level of concurrency.
I'd like to share small but useful tip which we use to reduce 'observed by user' delay related to cold starts. In our case the Lambda function handles HTTP requests from front-end via AWS API Gateway, in particular executes search functionality when user type something in the input field. Usually user start to type with some delay after UI is rendered, so we have some time to execute ping call to our Lambda function for warming it up. And when user will make requests to the back-end, most likely the Lambda will be ready for work.
Actually such approach do nothing for fixing the issue with cold starts on the back-end side and you will need to look for other options how to fix it, but it can be an user experience improvement without much efforts (something like hotfix).
One thing you should remember - if your service is public and you care about Google Insights score you should be careful implementing such approach.
I have a Lambda that is triggered to run every week, and I want to have a CloudWatch alarm if it ever does not run for more than 7 consecutive days.
My thinking was Alarm if < 1 invocation for 8 days but it does not seem to be possible to set it longer than 24 hours:
The alarm evaluation period (number of datapoints times the period of
the metric) must be no longer than 24 hours.
Is there another way to ensure execution of Lambdas that are triggered on a period of greater than 24 hours?
Maximum evaluation period is 24 hours.
You can get around that by creating a custom metric using CloudWatch PutMetricData API. You can publish the time elapsed since the last execution of your lambda function and then alarm when the value rises above 8 days.
One way of doing this would be to have your lambda function store the timestamp of execution to DynamoDB every time it triggers. Then you can create a new function that will read that timestamp from DynamoDB and publish the difference between it and current time to a custom metric (have that lambda trigger every 1h for example).
Once you have the new custom metric flowing, you can create an alarm that will fire if the value goes above 8 days for one 1h datapoint (this will solve your initial issue). You can also set the Treat missing data as option to bad - breaching threshold (this will alert you if the second lambda function doesn't trigger).
You should also set alarms on CloudWatch Events errors and Lambda errors. This will alert you if something goes wrong with the scheduling or the lambda itself. But the custom metric I mentioned above will also alert you in the case of human error where someone disables or deletes the event or the function by mistake for example.
I have problem with AWS lambda execution time.
I have 8 lambdas, each of my lambda functions get the same data from S3 and draw images then upload to S3. So I use SNS to distribute the trigger event to each lambdas.
When testing, I just run 1 of them (it call lambda_1), and it only take about 200s for its execution. But when I add all lambdas to SNS topic to make them run at same time, that lambda_1 takes more than 200s event get timeout (over 300s).
The same data I use, the same configuration for both execute, the only difference is 8 lambdas are executed at same time (get trigger from SNS event).
Is it the behavior of aws lambda? I have no idea about this.
Any document or suggestion is very appreciated!
Thanks