I saw some code on quip to s3 exporter in GitHub but it seems like that page has been taken down.
Basically for any change event (or regular interval sync also works) in the quip, an s3 bucket (table) should be updated. The code I saw in GitHub had used Lambda among other AWS services.
Related
When running an AWS Glue crawler that points to S3, the second log entry in CloudWatch is always:
Crawl is not running in S3 event mode
What is S3 event mode?
The name sounds like some way of getting S3 to invoke Glue for partial crawls after every object upload to the prefix. But as far as I can tell, such functionality does not exist. So what is this log entry referring to?
The closest thing I found in the Glue documentation was event based triggers for Glue jobs, but Glue Jobs are different to Glue Crawlers.
Steps to reproduce
Create a Glue Crawler. Choose any configuration. Point it to anywhere in any S3 bucket with any dataset (even an empty one)
Run the crawler. It doesn't matter if the crawl fails or succeeds
Open the logs for that crawl
Look at the second log entry
2021-07-01T20:04:39.882+10:00
[6588c8ba-57e2-46e3-94b4-1bc4dfc5957d] BENCHMARK : Running Start Crawl for Crawler my-crawler
2021-07-01T20:04:40.200+10:00
[6588c8ba-57e2-46e3-94b4-1bc4dfc5957d] INFO : Crawl is not running in S3 event mode
AWS Support gave me an answer.
S3 Event mode is functionality available internally inside AWS. As I suspected it means S3 triggers crawler crawls for every file upload. But this functionality is not public at the moment.
I had the same problem and I found a solution in this article https://www.linkedin.com/pulse/my-top-5-gotchas-working-aws-glue-tanveer-uddin/
In short though the solution was to have aws-glue- before the name of my bucket. So, for example trying to get a crawler to go through a bucket called test-bucket would not work but if I change the name to aws-glue-test-bucket then works.
I am working on a requirement, where i am doing multipart upload of the csv file from on prem server to S3 Bucket.
To achieve this using AWS Lambda I create a presigned url and use this url i am uploading the csv file. Now, once i have the file in AWS S3, i want it to be moved to AWS RDS Oracle DB. Initially i was planning to use AWS Lambda for this.
So once i have the file in S3, it triggers lambda(s3 event) and lambda will push this file to RDS. But with this the issue is with the file Size(600 MB).
I am looking for some other way, where whenever there is a file uploaded to S3, it should trigger any AWS service and that service will push this csv file to RDS. I have gone through AWS DMS/Data Pipeline, but not able to find any way to automate this migration
I need to automate this migration on every s3 upload, that is also cost effective.
Setup S3 Integration and build SPROCS to help automate load. Details found here.
UPDATE:
Looks like you don't even need to create a SPROC. You can just use the RDS procedure as outlined here. You would then just create an event-driven lambda function that is triggered on a given S3 event--e.g. on object PUT(), POST(), COPY, etc..--which passes the S3 metadata requisite to access the event object. Here is a simple Python example of what that Lambda and config might look like. You would then use the metadata passed on the trigger event--as outlined in the Python example--to dynamically create your procedure call then execute that procedure. You can also add the ensuing workflow logic that meets your requirements--i.e. TASK_ID fetch & operational handling, monitoring, etc...--to the same lambda function or separate those concerns by adding additional lambdas. Hope this helps!
Some images which is already uploaded on AWS S3 bucket and of course there is a lot of image. I want to edit and replace those images and I want to do it on AWS server, Here I want to use aws lambda.
I already can do my job from my local pc. But it takes a very long time. So I want to do it on server.
Is it possible?
Unfortunately directly editing file in S3 is not supported Check out the thread. To overcome the situation, you need to download the file locally in server/local machine, then edit it and re-upload it again to s3 bucket. Also you can enable versions
For node js you can use Jimp
For java: ImageIO
For python: Pillow
or you can use any technology to edit it and later upload it using aws-sdk.
For lambda function you can use serverless framework - https://serverless.com/
I have made youtube videos long back. This is related to how get started with aws-lambda and serverless
https://www.youtube.com/watch?v=uXZCNnzSMkI
You can trigger a Lambda using the AWS SDK.
Write a Lambda to process a single image and deploy it.
Then locally use the AWS SDK to list the images in the bucket and invoke the Lambda (asynchronously) for each file using invoke. I would also save somewhere which files have been processed so you can continue if something fails.
Note that the default limit for Lambda is 1000 concurrent executions, so to avoid reaching the limit you can send messages to an SQS queue (which then triggers the Lambda) or just retry when invoke throws an error.
I have recently joined a company that uses S3 Buckets for various different projects within AWS. I want to identify and potentially delete S3 Objects that are not being accessed (read and write), in an effort to reduce the cost of S3 in my AWS account.
I read this, which helped me to some extent.
Is there a way to find out which objects are being accessed and which are not?
There is no native way of doing this at the moment, so all the options are workarounds depending on your usecase.
You have a few options:
Tag each S3 Object (e.g. 2018-10-24). First turn on Object Level Logging for your S3 bucket. Set up CloudWatch Events for CloudTrail. The Tag could then be updated by a Lambda Function which runs on a CloudWatch Event, which is fired on a Get event. Then create a function that runs on a Scheduled CloudWatch Event to delete all objects with a date tag prior to today.
Query CloudTrail logs on, write a custom function to query the last access times from Object Level CloudTrail Logs. This could be done with Athena, or a direct query to S3.
Create a Separate Index, in something like DynamoDB, which you update in your application on read activities.
Use a Lifecycle Policy on the S3 Bucket / key prefix to archive or delete the objects after x days. This is based on upload time rather than last access time, so you could copy the object to itself to reset the timestamp and start the clock again.
No objects in Amazon S3 are required by other AWS services, but you might have configured services to use the files.
For example, you might be serving content through Amazon CloudFront, providing templates for AWS CloudFormation or transcoding videos that are stored in Amazon S3.
If you didn't create the files and you aren't knowingly using the files, can you probably delete them. But you would be the only person who would know whether they are necessary.
There is recent AWS blog post which I found very interesting and cost optimized approach to solve this problem.
Here is the description from AWS blog:
The S3 server access logs capture S3 object requests. These are generated and stored in the target S3 bucket.
An S3 inventory report is generated for the source bucket daily. It is written to the S3 inventory target bucket.
An Amazon EventBridge rule is configured that will initiate an AWS Lambda function once a day, or as desired.
The Lambda function initiates an S3 Batch Operation job to tag objects in the source bucket. These must be expired using the following logic:
Capture the number of days (x) configuration from the S3 Lifecycle configuration.
Run an Amazon Athena query that will get the list of objects from the S3 inventory report and server access logs. Create a delta list with objects that were created earlier than 'x' days, but not accessed during that time.
Write a manifest file with the list of these objects to an S3 bucket.
Create an S3 Batch operation job that will tag all objects in the manifest file with a tag of "delete=True".
The Lifecycle rule on the source S3 bucket will expire all objects that were created prior to 'x' days. They will have the tag given via the S3 batch operation of "delete=True".
Expiring Amazon S3 Objects Based on Last Accessed Date to Decrease Costs
Simple problem, i have got a google bucket which gets content 3 times a day from an external provider. I want to fetch this content as soon as it arrives and push it onto a S3 bucket. I have been able to achieve this via running my python scripts as a cron job. But I have to provide high availability and such if i follow this route.
My idea was to set this up in aws lambda, so I don't have to sweat the infrastructure limitations. Any pointers on this marriage between gs and lambda. I am not a native Node speaker so any pointers will be really helpful.
GCS can send object notifications when an object is created/updated. You can catch the notifications (which are HTTP post requests) by a simple web app hosted on GAE, and then handle the file transfer to S3. Highly available, event driven solution.