AWS Batch

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

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.

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.

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.

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