AWS Batch Reviews & Insights

We encountered issues orchestrating long-running tasks in Lambda functions, as they have a limit of 15 minutes. We needed a solution that could be triggered from AWS Step Functions. Then we found yes it's a bit tedious to set up, has a steep learning curve but once that's passed you can easily run a 24 or 48 hours or other long-timed task without any issues, which helped our use case where needed to run a task which took 24 hours even with AWS Batch's Compute

In our case, we had a SQL shell script that ingested data into RDS using the MySQL command-line interface (CLI). However, the file was 4 gigabytes in size, so reading each line, transforming the data, and writing it to different tables for various files took a considerable amount of time.

Less Appropriate: if your job doesn't run on demand or can be completed in less than 15 mins , batch doesn't set your use case as the steep learning complexity for such a small time consuming workload is better spent on lambdas or EC2 configuration as well , and if you don't know but batch is a lot more expensive than lambda's or basic EC2

We have multiple scraping jobs written and this needs to be managed, we were facing difficulty to run, then we moved to AWS batch where we are running multiple jobs very easily and efficiently, so mainly we are using AWS for cost saving and optimisation, We are running 100s of jobs currently

Overall experience using AWS batch is good, our day to day tasks are full-filling using AWS batch, we have migrated our all the in premises job and we are able to run more than 100 jobs using AWS batch with efficiency, It is easy to use, Monitoring of the jobs i am finding little difficulty

We had to use AWS Batch for multiple jobs. As it is fully managed it will save you a lot of work. If you are working with AWS services like EC2, it integrates seamlessly. Also creating the cluster is difficult.

I would advise that to use AWS Batch if there is no other alternative. It delivers on its promise and is a great product and there is the factor of cost. I would suggest none other AWS Lamba or other alternatives in the market as it is quite slow from my experience.

We need to not manage the machines, very easy to use, great dashboard, fully supported SDK for programmatic access. We were short of resources, so we used batch which helped with no need of monitoring underlying infrastructure.

Easy to configure task queues and queue tasks that require async execution with AWS client for PHP. Good logs on AWS CloudWatch where you can log output and errors of the task execution.

Previously supported this on my previous job along with users integrating with 3rd party firewall in the AWS marketplace. Integration with AWS services is top-notch because of how it simplifies automation and batch jobs.

AWS Batch is perfect in EC2 instances as you'll easily automate the jobs in your hosted private servers. Not good in Lightsail since it is a standalone server, you have to automate on the server itself instead of using AWS Batch.

Currently using S3 for storage and adding direct links to these files for Members Area website to view videos and download PDF worksheets. The price is economical for the type and number of files I have and the program I use for my Membership website does not allow to store the videos there directly.

More appropriate if you have a tech group that can use more of the AWS Batch rather than one or 2 things. It works great for me, but there was a huge learning curve the first week of using it. Now, I love it - and I hope to dig deep into other parts not just S3.

AWS Batch is used for making smart scaling decisions by running multiple jobs. It is being used to automate and build various jobs from different resources across various departments. It also monitors our applications and automatically adds or removes capacity in real time. This is very helpful to maintain jobs and availability with our workload changing continuously.

Start with reviewing all your jobs, consolidating the timeline, and making a plan on what all jobs need to be prioritized. These can be optimized based on cost and performance. With a continuously changing workload, AWS Batch helps to build and automate the jobs across various resources. It also helps to manage the performance and workload.