Batch Service

Batch Service (Batch) is a distributed cloud computing service enabling you to run large-scale batch processing jobs. It supports automatic scheduling of numerous tasks, yields refined resource management, and features superior data loading, making it the perfect solution for at-scale parallel computing scenarios.

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Advantages
  • High Efficiency

    You can run at-scale parallel batch processing jobs automatically and efficiently complete resource scheduling, task provisioning, and data loading.

  • Easy to Use

    With available job scheduling functions, you can use cloud services to develop your business without the need to dive into complex programming.

  • Fully Managed

    Batch fully manages resource and process scheduling in batch computing.

  • Cost Effective

    You only need to pay for the cloud resources you use, freeing up your capital investments in software, hardware, and labor-intensive O&M for revenue-generating endeavors.

Application Scenarios
  • Gene Detection

  • Deep Learning

  • Video Rendering

  • Video Transcoding

Gene Detection

Gene Detection

The volume of data that must be processed in gene sequencing continues to mushroom as efforts and mapping become more refined. The increased precision and clarity means more computing power is needed, otherwise systems become strained from the pressure. With Batch, you can cost-effectively make use of in-cloud computing resources to process massive volumes of data.

Advantages

Efficiency and Ease of Use

The convenient process control in the accessible data processing software and running environment allows you to process large quantity of tasks in parallel for accelerated analysis and computing timetables.

Compatible with Multiple Storage Services

Batch works seamlessly with cloud storage services like OBS, SFS, and EVS to meet the particulars of your storage needs.

Low Cost

You can use cloud resources without any software and hardware investment and only pay for the resources you use.

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Deep Learning

Deep Learning

You can use Batch to deploy offline training tasks in batches based on deep learning frameworks TensorFlow, Caffe, MXNet, and much more.

Advantages

Automated Management

Delivers one-stop closed-loop services covering computing resources, network, storage, and job management, allowing you to focus on your business rather than your mashup.

Easy to Use

Provides general job management utilities for unified deployment of various deep learning frameworks. All that means you can provision deep learning tasks with just a small amount of code integration.

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Video Rendering

Video Rendering

Batch is capable of running large quantities of jobs in parallel, removing the concerns over inadequate compute resources to handle the rendering tasks involved with production of videos, animations, and special effects.

Advantages

Accelerated Rendering

Supports running of numerous jobs in parallel to help you speed up the rendering process.

Simple Operation

Allows you to migrate services to the cloud without any special programming requirements. Multiple cloud storage services can be used for storing data.

Low Cost

Allows you to start using resources right away in pay-per-use mode without having to install and manage computing software and server clusters.

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Video Transcoding

Video Transcoding

Batch gives you immediate access to cloud resources so you can quickly perform transcoding on massive volumes of multimedia data without having to invest huge amounts upfront into hardware. Get what you need now and step away from the ensuring complexities in managing the host of software to run everything.

Advantages

Low Cost

Use the cloud resources you need without any software and hardware investment and only pay for the resources you use.

High Efficiency

A large amount of data can be processed in parallel to improve transcoding efficiency.

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ecs

obs

sfs

evs

Functions

  • Custom Job Scheduling

    You can specify job priority, execution time, and Directed Acyclic Graph (DAG)-based dependencies among multiple task groups in a job.

  • Flexible Resource Management

    Resources are dynamically allocated to fulfill job requirements. You can manage and allocate heterogeneous resources, such as the memory, CPU, and GPU.

  • Support for Multiple Storage Types

    Batch works seamlessly with cloud storage services, such as OBS and SFS.

Custom Job Scheduling

Flexible Resource Management

Support for Multiple Storage Types

  • Real-Time Task Log Query

    You can obtain task logs in real time and customize log storage paths.

  • Spot Instance Support

    Batch informs you when you need to purchase more Spot instances so you are not paying for more computing power than you need. This function is being rolled out soon.

Real-Time Task Log Query

Spot Instance Support

Usage Guides

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