I am writing a lambda function for file extraction and need to store a file while performing this function so need to store that file in aws lambda function .
Is it possible to store store a file on lambda .
Yes, quoting from the AWS Lambda FAQ
Each Lambda function receives 500MB of non-persistent disk space in its own /tmp directory.
https://aws.amazon.com/lambda/faqs/
Note that as the commenters point out, it is only reliably there for a single execution of your function. You don't have control over the execution environment, so subsequent runs may be in different instances of your lambda function.
If you need the data to be more persistent you should use AWS S3.
Related
I have an automation task that uses a lambda which calls two other lambdas. The first invoked lambda, lambda 1, fetches some data, processes it and writes it to /tmp. The other lambda, lambda 2, was intended to be run by reading the file written to /tmp before uploading to another location outside of AWS. The upload lambda 2 is based off a docker image. Is it possible to mount /tmp from the runtime of the lambda calling lambda 2 so lambda 2 can read the file written by lambda 1?
If this is not possible the only other alternative would be to use either a EFS file system or pass the data directly into lambda 2's payload as a string correct? These files are not too large so I am thinking of passing the string into the payload directly as the alternative option.
Different Lambda functions don't share the same disk. The best way to share state in this use case would be with something like S3.
I have following 2 use case to apply on this
Case 1. I would need to call the lambda alone to invoke athena to perform query on s3 data? Question: How to invoke lambda alone via api?
Case 2. I would need lambda function to invoke athena whenever a file copied to the same s3 bucket that already mapped to the athena?
Iam referring following link to do the same to perform the Lambda operation over athena
Link:
https://dev.classmethod.jp/cloud/run-amazon-athenas-query-with-aws-lambda/
For the case 2: Following are eg want to integrate:
File in s3-1 is sales.csv - and i would updating sales details by copying data from other s3-2 . And the schema/column defined in the s3-1 data would remain same.
so when i copy some file to the same s3 data that mapped to the athena, the lambda should call athena to perform the query
Appreciate if can provide the better way to achieve above cases?
Thanks
Case 1
An AWS Lambda can be directly invoked via the invoke() command. This can be done via the AWS Command-Line Interface (CLI) or from a programming language using an AWS SDK.
Case 2
An Amazon S3 event can be configured on a bucket to automatically trigger an AWS Lambda function when a file is uploaded. The event provides the bucket name and file name (object name) to the Lambda function.
The Lambda function can extract these details from the event record and can then use that information in an Amazon Athena command.
Please note that, if the file name is different each time, a CREATE TABLE command would be required before a SELECT command can query the data.
General Comments
A Lambda function can run for a maximum of 15 minutes, so make sure the Athena queries do not take more than this time. This is not a particularly efficient use of an AWS Lambda function because it will be billed for the duration of the function call, even if it is just waiting for Athena to finish.
Another option would be to have the Lambda function directly process the file, assuming that the query is not particularly complex. For example, the Lambda function could download the file to temporary storage (maximum 500MB), read through the file, do some calculations (eg add up the total of some columns), then store the results somewhere.
The next step wuold be create a end point to your lambda, you ver can use aws-apigateway for that.
On the other hand, using the amazon console or amazon cli, you can invoke the lambda in order to test.
I am creating an AWS Lambda function that is triggered for each PUT on an S3 bucket. A separate Java application creates the S3 bucket, sets up the trigger to the Lambda on Put, and PUTs a set of files into the bucket. The Lambda function executes a compiled binary, it passes to the binary a script, which acts on the new S3 object.
All of this is working fine.
My problem is that I have a set of close to 100 different scripts, and am regularly developing new scripts. The ZIP for the Lambda contains all the scripts. Scripts correspond to different types of files, so when I run the Java application, I want to specify WHICH script in the Lambda function to use. I'm trying to avoid having to create a new Lambda for each script, since each one effectively does the exact same thing but for the name of the script.
When you INVOKE a Lambda, you can put parameters into the context. But my Lambda is triggered, so most of what I react to is in the event. I can't figure out how to communicate this simple parameter to the Lambda efficiently as I set up the S3 bucket and the event trigger.
How can I do this?
You can't have S3 post extra parameters to your Lambda function. What you can do is create a DynamoDB table that maps S3 buckets to scripts, or S3 prefixes to scripts, or something of the sort. Then your Lambda function can lookup that mapping before executing your script.
It is not possible to specify parameters that are passed to the AWS Lambda function. The function is triggered by Amazon S3, which passes standard information (bucket, key).
However, when creating the object in Amazon S3 you could attach object metadata. The Lambda function could then retrieve the metadata after it has been notified of the event.
An alternate approach would be to subscribe several Lambda functions to the S3 bucket. The functions could look at the event and decide whether or not to process the event.
For example, if you had pictures and text files being stored, you could create one Lambda function for pictures and another for text files. Both functions would be triggered upon object creation. Each function would look at the file extension (or, if necessary, look within the object itself). If it is a filetype that is handles, then it can process the object. If it is not a filetype it handles, the function can simply exit. This type of check could be performed very quickly and Lambda only charges per 100ms, so the cost would be close to irrelevant.
The benefit of this approach is that you could keep your libraries separate from each other, rather than making one large Lambda package.
I have a lambda function that reads from DynamoDB and creates a large file (~500M) in /tmp that finally uploaded to s3. Once uploaded the lambda clears the file from /tmp (since there is a high probability that the instance may be reused)
This function takes about 1 minute to execute, even if you ignore the latencies.
In this scenario, when i try to invoke the function again, in < 1m, i have no control if i will have enough space to write to /tmp. My function fails.
Questions:
1. What are the known work arounds in these kind of scenario?
(Potentially give more space in /tmp or ensure a clean /tmp is given for each new execution)
2. What are the best practices regarding file creation and management in Lambda?
3. Can i attach another EBS or other storage to Lambda for execution ?
4. Is there a way to have file system like access to s3 so that my function instead of using /tmp can write directly to s3?
I doubt that two concurrently running instances of AWS Lambda will share /tmp or any other local resource, since they must execute in complete isolation. Your error should have a different explanation. If you mean, that a subsequent invocation of AWS Lambda reuses the same instance, then you should simply clear /tmp on your own.
In general, if your Lambda is a resource hog, you better do that work in an ECS container worker and use the Lambda for launching ECS tasks, as described here.
You are likely running into the 512 MB /tmp limit of AWS Lambda.
You can improve your performance and address your problem by storing the file in-memory, since the memory limit for Lambda functions can go as high as 1.5 GB.
Starting March 2022, Lambda now supports increasing /tmp directory's maximum size limit up to 10,240MB.
More information available here.
Now it is even easy, AWS storage can be increased to 10GB named Ephemeral Storage. It is available in general configuration of the AWS lambda functions.
I have following basic security related questions regarding AWS Lambda service:
Where does AWS Lambda store data if for example I try to store data on local disk?
Is is possible to encrypt the data on Lambda?
Thanks
One important sidenote to the /tmp of Lambda functions is that the Lambda function containers are re-used and scratch space is not always erased. If an invocation uses a container that was spun up because of a previous invocation (this happens if you execute a few Lambda function in quick succession), the scratch space is shared.
This screwed up a functionality for me once.
I store temporary data in my lambda function, never had any issue.
Store your data in /tmp, you may not have access to other dirs
The temporary data - as the name indicates - is available only for that invocation of lambda
If the data is sensitive, encrypt it (if the encryption libraries are not provided by default for that language, make sure you package the library)
Files stored on Lambda's local volumes should be for temporary short-term storage only and should not be expected to persist beyond the lifetime of your single Lambda function invocation.
If you need to store data long-term, use a database like DynamoDB or use Amazon S3.
If you must store data on the local volume, you can encrypt it, but you must do it yourself. Also, note that the next time the function is called, the data most likely will be gone.
If you by "secure" asks who will have access to data then the answer is anyone that can call the lambda. If you by "secure" also wonder if it is durable storage, then the answer is no. Lambda functions only have access to an ephemeral /tmp folder. There is no guarantee that the two consecutive calls to the same lambda function will be executed on the same physical machine. However, if the function is called twice within a short period of time, it could be executed on the very same machine and then a file that was saved by the first call may be available to the second call. If you choose to use this temporary file storage you should also be aware that there are some limitations of how much data that can be stored.
Lambda store data in lambdas \tmp folder.
and it is not secure the store data on lambda
reason is when lambda function completes its execution it will delete all the data which is in the \tmp folder
solution before terminating the lambda function or completion of the script move data from \tmp folder aws s3 bucket.