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AWS Batch

AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.

AWS Batch Reviews and details

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  • AWS Batch Landing page
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How AWS Batch Works

Live from the London Loft | AWS Batch: Simplifying Batch Computing in the Cloud

AWS re:Invent 2018: AWS Batch & How AQR leverages AWS to Identify New Investment Signals (CMP372)

Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about AWS Batch and what they use it for.
  • Looking for a decent (self hostable) program to orchestrate scripts, notify on failures, etc
    After moving off Jenkins, I moved everything to AWS Batch with Fargate. This works quite well, but it is proving to be a little expensive, as I have to pay for:. Source: about 1 year ago
  • Hosting strategy suggestions
    If you're looking for more control over your infrastructure and want to run a full computing environment, EC2 might be the right choice for you. With EC2, you have complete control over the operating system, network, and storage, which can be useful if you need to install custom software or use specific hardware configurations. Additionally, EC2 + Batch processing provide a wider range of instance types, including... Source: over 1 year ago
  • Questions for bioinformatics researchers that use AWS
    AWS Batch is the equivalent of a university cluster you submit to with slurm/sge/lsf/etc. But does not use those schedulers as AWS has their own. Source: over 1 year ago
  • Scheduling "Fetch & Run" Batch Jobs with AWS Batch and CloudWatch Rules
    Developers frequently use batch computing to access significant amounts of processing power. You may perform batch computing workloads in the AWS Cloud with the aid of AWS Batch, a fully managed service provided by AWS. It is a powerful solution that can plan, schedule, and execute containerized batch or machine learning workloads across the entire spectrum of AWS compute capabilities, including Amazon ECS, Amazon... - Source: / over 1 year ago
  • can you run OS applications in lambda layers?
    As others mentioned, you *can*. It might be easier with AWS Batch ( depending on what you're trying to do. Source: over 1 year ago
  • A serverless architecture for high performance financial modelling
    I remember as part of the AWS certification exams this use was explicitly mentioned. - Source: Hacker News / almost 2 years ago
  • Alternatives to EKS
    Https:// is the go-to for HPC, or maybe I'm misunderstanding your requirements. Source: about 2 years ago
  • Tips for scalable workflows on AWS
    Instead, break up the workflow - run each step on its own compute instance with resources right sized for each step. There are a lot of AWS instance types to choose from, and if you connect a workflow engine to AWS Batch, AWS Batch will manage picking the right one for you based on CPU and memory (and GPU) requirements. - Source: / about 2 years ago
  • Rust: CSV processing
    Another alternative is to use AWS Batch with spot instances in conjunction with AWS Step Functions leveraging the service integration Run a Job (.sync) pattern. After calling AWS Batch submitJob, the workflow pauses. When the job is complete, Step Functions progresses to the next state. - Source: / over 2 years ago
  • Orchestration of processing in the cloud and locally
    Check out AWS Batch, it will provide the instances for you and remove them once the job is done. And if you're looking for a framework that allows you to quickly move back and forth between local and cloud, check out Ploomber. Source: over 2 years ago
  • Does anyone know of good AWS resources or tutorials for bioinformatics
    I would suggest the AWS genomics CLI and AWS Batch as good features to learn. Both benefit from knowledge of nextflow so I would start there and work towards to the cloud. There's already a website with loads of common bioinformatics workflows already implemented. Source: over 2 years ago
  • Launching VM instances only when needed
    If you're looking for something a bit more managed, check out Batch. It's basically a managed AWS service that does a lot of what I describe, kind of the same, but kind of differently. Batch has its own workflow peculiarities, but you may prefer dealing with those rather than dealing with something custom hacked together to behave like it. Source: over 2 years ago
  • running python scripts parallelly on aws
    I think AWS batch is what you're looking for. Source: almost 3 years ago
  • Auto Scaling EC2?
    Sounds like Batch could be what you are after; if you can package your software into a docker container and separate the parts of the pipeline needing different resources into different jobs and run them in separate queues with appropriately sized instances in their compute environments. I’d explore wrapping up the jobs in a Nextflow script too. Source: about 3 years ago

External sources with reviews and comparisons of AWS Batch

Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
AWS Batch: This is used for batch computing jobs on AWS resources. It has insane scalability and is well-suited for engineers look to do large compute jobs.

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This is an informative page about AWS Batch. You can review and discuss the product here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.