There is a data being stored on a s3 bucket in a daily basis, we are trying to automate parsing and processing that daily data being sent to s3 bucket, we already have the script that will parse the data, we just need to have the approach on the AWS how to automate this,the approach/use-case we thought was AWS batch that is scheduled to do the script on a daily basis or will get the latest data on that day before EOD, but seems like batch is incapable of doing it.
any ideas and approach? we've seen some approach like using Lambda and SQS/SNS
just to summarize:
data (Daily) > stored in S3 > data will be process by our team > stored to elastic search.
Thanks your ideas.
AWS Lambda is exactly what you want in this case. You can trigger lambda executing on S3 file showing up, that will process the file, and can then send it to ElasticSearch or wherever you want it to end up.
Here's an official explanation from AWS: https://docs.aws.amazon.com/lambda/latest/dg/with-s3.html
You can use Lambda + cloud watch events to execute your code on a regular schedule. You can specify a fixed rate ( or you can specify a Cron expression ), for example, in your case, you can execute your lambda every 24 hours, this way, your logic for data processing will run once daily.
Take a look at this article from AWS : Schedule AWS Lambda Functions Using CloudWatch Events
Related
I am looking to trigger code every 1 Hour in AWS.
The code should: Parse through a list of zip codes, fetch data for each of the zip codes, store that data somewhere in AWS.
Is there a specific AWS service would I use for parsing through the list of zip codes and call the api for each zip code? Would this be Lambda?
How could I schedule this service to run every X hours? Do I have to use another AWS Service to call my Lambda function (assuming that's the right answer to #1)?
Which AWS service could I use to store this data?
I tried looking up different approaches and services in AWS. I found I could write serverless code in Lambda which made me think it would be the answer to my first question. Then I tried to look into how that could be ran every x time, but that's where I was struggling to know if I could still use Lambda for that. Then knowing where my options were to store the data. I saw that Glue may be an option, but wasn't sure.
Yes, you can use Lambda to run your code (as long as the total run time is less than 15 minutes).
You can use Amazon EventBridge Scheduler to trigger the Lambda every 1 hour.
Which AWS service could I use to store this data?
That depends on the format of the data and how you will subsequently use it. Some options are
Amazon DynamoDB for key-value, noSQL data
Amazon Aurora for relational data
Amazon S3 for object storage
If you choose S3, you can still do SQL-like queries on the data using Amazon Athena
I'd like to peform the following tasks on a regular basis (e.g. every day at 6AM) using AWS:
get new set of data using API. This dataset is updated on a daily basis.
run a python script that would process the obtained dataset by the means of several python libraries like matplotlib, pandas, plotly
automatically send the output of the script, which would be a single pdf file or a html dashboard, via email to a group of specified recipients
I know how to perform all of the above items locally - my goal is to automate this routine. I'm new to AWS and would appreciate some advice on how to perform these tasks in a straightforward way. Based on the reading I did so far, it looks like the serverless approach may be able to do the job and also reduce the complexity, but I'm not sure which functionalities exactly I should use.
For scheduling you can use aws event bridge.
You can schedule AWS lambda or AWS Step Functions both of these are serverless :).
You can have 3 lambdas
To get the data and save it in S3/dynamo (if you want to persist the data)
Processor lambda and save the report to S3.
Another lambda to send email using AWS SES which will read the report from S3 and send it.
If you don't want to use step function you can start your lambda from S3 put event or you can trigger one lambda from another lambda using aws-sdk.
So there are different approaches you can take.
First off, I would create a Lambda. You can schedule the function to run on a cron job.
If the Message you want to send is small:
I would create a SNS Topic with a email fan out.
Inside your lambda you can then transform the data and send out via SNS.
Otherwise:
I would use SES and send a mail via the SES SDK.
I am pulling data from Salesforce using AWS Appflow and it is dumping data into S3. It is creating many files in S3. How can I run lambda only once per Appflow run. In my scenario, lambda is triggering n number of times, where n is the number of files created in S3 per run.
Note : 1. I can't create 1 file per run.
2. I am open for any other approach
As you have made it clear that your using S3 event for the trigger.
That addresses the issue of why your lambda function is being triggered every time there is a PUT event on S3.
Unfortunately there is no such trigger that would help you in this use case.
If you still want to use Lambda you can have a cloud watch event as a trigger for lambda function like a corn job.
You can schedule it for any interval which you feel would be appropriate for the function.
Hope this was helpfull
Appflow has the option of aggregating the files to a single file before loading it to S3. You can see that option in additional settings just before the scheduling.
I wouldn't mind my Lambda function get invoked multiple times, as long as it is idempotent.
Normally one AppFlow output file in the S3 bucket should only trigger your Lambda function once if the Lambda function can finish the execution within the timeout and return no error. Failing to do so may trigger a retry mechanism.
As #krr7931 suggested, you can try the aggregation option when setting up your AppFlow flow. AppFlow also supports filters, which can help reduce the amount of data you need to handle.
PS: here's my reflection on using AppFlow with Salesforce https://www.capturedlabs.com/amazon-app-flow-with-salesforce-in-action
I want to build an end to end automated system which consists of the following steps:
Getting data from source to landing bucket AWS S3 using AWS Lambda
Running some transformation job using AWS Lambda and storing in processed bucket of AWS S3
Running Redshift copy command using AWS Lambda to push the transformed/processed data from AWS S3 to AWS Redshift
From the above points, I've completed pulling data, transforming data and running manual copy command from a Redshift using a SQL query tool.
Doubts:
I've heard AWS CloudWatch can be used to schedule/automate things but never worked on it. So, if I want to achieve the steps above in a streamlined fashion, how to go about it?
Should I use Lambda to trigger copy and insert statements? Or are there better AWS services to do the same?
Any other suggestion on other AWS Services and of the likes are most welcome.
Constraint: Want as many tasks as possible to be serverless (except for semantic layer, Redshift).
CloudWatch:
Your options here are either to use CloudWatch Alarms or Events.
With alarms, you can respond to any metric of your system (eg CPU utilization, Disk IOPS, count of Lambda invocations etc) when it crosses some threshold, and when this alarm is triggered, invoke a lambda function (or send SNS notification etc) to perform a task.
With events you can use either a cron expression or some AWS service event (eg EC2 instance state change, SNS notification etc) to then trigger another service (eg Lambda), so you could for example run some kind of clean-up operation via lambda on a regular schedule, or create a snapshot of an EBS volume when its instance is shut down.
Lambda itself is a very powerful tool, and should allow you to program a decent copy/insert function in a language you are familiar with. AWS has several GitHub repos with lots of examples too, see for example the serverless examples and many samples. There may be other services which could work for you in your specific case, but part of Lambda's power is its flexibility.
I am new with AWS and don't know how to do the following. When I put an object in S3 I want to launch a python script that does some transformations and returns it to another path in S3. I've tried a lambda function but the process takes more than 300 seconds. I've also tried it with a Glue job but I don't know how to trigger it when I put the file in S3.
Does anyone know how to do it? Maybe I'm using the wrong AWS tools.
The simple solution for your problem is here:
Since you've already mentioned that you have AWS Glue job working to do this operation. And all you don't know is how to trigger glue job when file placed in s3, I am answering to that question.
You can write an AWS lambda using boto3 module which can be triggered based up on the s3 event and have setup glue.start_job_run command in your lambda function.
response = client.start_job_run(
JobName='string')
https://boto3.readthedocs.io/en/latest/reference/services/glue.html#Glue.Client.start_job_run
Note:: I strongly believe Glue is the right tool rather than lambda for your requirement that you mentioned in question, because AWS lambda have time out limitation. It will get timeout after 300 seconds.
One option would be to use SQS:
Create the SQS queue.
Setup S3 to send notifications to the SQS queue when new objects are added to the source bucket. See Configuring Amazon S3 Event Notifications.
Setup your Python script on an EC2 instance and listen to the SQS queue in your code.
Upload the output of your Python script into the target S3 bucket after script finished.
Can you break up the Python processing into smaller steps? I'd definitely recommend that you use Lambda instead of managing EC2 if you can get your code to run within the Lambda restrictions.