With AWS Batch, users package the code for batch jobs, specify dependencies, and submit batch jobs using the AWS Management Console, CLIs, or SDKs. AWS Batch allows users to specify execution parameters and job dependencies, and facilitates integration with a broad range of popular batch computing workflow engines and languages (e.g., Pegasus WMS, Luigi, Nextflow, Metaflow, Apache Airflow, and AWS Step Functions).
Cisco Intersight Workload Optimizer was a real-time decision engine for continuous optimization of application resources across on-premises, public cloud, and edge environments. The service is being discontinued.
Overall AWS Batch, I found easy compare to other softwares which i have tried, It is easy to setup the multiple jobs and on demand we can push our new jobs and same will be monitored by the monitoring dashboards provided by AWS batch, easy to schedule the new job using AWS batch.
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.
Key advantages include cost-effectiveness through dynamic resource provisioning and the use of spot instances. It auto-scales to meet workload demands, allowing easy job submission via the AWS Management Console or SDKs. It integrates seamlessly with other services like S3 and CloudWatch. It features automatic retries for failed jobs. It allows for a custom computing environment tailored to specific needs