AWS Batch has several improvement areas. AWS could provide better visibility into job execution and failure, as well as easier debugging and logging, which is much needed. AWS could also provide simplified configuration because it is very complex for beginners. Additionally, AWS can improve job startup times because currently, job startup time is less than optimal. The initial setup for AWS Batch can feel heavy compared to simpler services such as Lambda. Currently, AWS Batch has complexity in setup and limited debugging visibility, which is really challenging for beginners.
Senior Data Engineer at a tech services company with 5,001-10,000 employees
MSP
Top 20
Apr 24, 2025
I haven't identified any significant improvements for AWS Batch. In other AWS services, I've encountered issues with APIs and documentation, but AWS Batch is straightforward and user-friendly. The user interface for queue searches could use fewer clicks, but that is a minor concern.
A feature allowing AWS Batch configuration to be directly deployed to different environments as code would be beneficial, as it would simplify the process, especially for non-technical users. Automating monitoring and getting notifications on job status and failures would enhance its functionality.
Software Engineering Manager – Digital Production Optimization at Yara International ASA
Real User
Top 5
Mar 10, 2025
The error handling capabilities could be more robust, particularly when using Spot Instances. AWS ( /products/amazon-aws-reviews ) should enhance its error handling for situations where Spot Instances can be taken away at any time.
The solution could improve its pricing-based resources like job execution. The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources. The solution should be updated to improve overall performance, including scalability and reliability. AWS Batch should regularly update its service and provide the most accurate and up-to-date information.
AWS Batch is a powerful service for managing compute-intensive workloads efficiently. By seamlessly integrating with EC2 and other AWS services, it streamlines the execution of container and batch computing jobs, maximizing resource use and scalability.AWS Batch provides a comprehensive job scheduling platform, automating resource provisioning and scaling for dynamic workloads. It supports container workloads and offers both EC2 and Fargate options, boosting flexibility and maintaining costs....
AWS Batch has several improvement areas. AWS could provide better visibility into job execution and failure, as well as easier debugging and logging, which is much needed. AWS could also provide simplified configuration because it is very complex for beginners. Additionally, AWS can improve job startup times because currently, job startup time is less than optimal. The initial setup for AWS Batch can feel heavy compared to simpler services such as Lambda. Currently, AWS Batch has complexity in setup and limited debugging visibility, which is really challenging for beginners.
I haven't identified any significant improvements for AWS Batch. In other AWS services, I've encountered issues with APIs and documentation, but AWS Batch is straightforward and user-friendly. The user interface for queue searches could use fewer clicks, but that is a minor concern.
A feature allowing AWS Batch configuration to be directly deployed to different environments as code would be beneficial, as it would simplify the process, especially for non-technical users. Automating monitoring and getting notifications on job status and failures would enhance its functionality.
The error handling capabilities could be more robust, particularly when using Spot Instances. AWS ( /products/amazon-aws-reviews ) should enhance its error handling for situations where Spot Instances can be taken away at any time.
The solution could improve its pricing-based resources like job execution. The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources. The solution should be updated to improve overall performance, including scalability and reliability. AWS Batch should regularly update its service and provide the most accurate and up-to-date information.
AWS Batch needs to improve its documentation.