Intelligent Resource Optimization

Optimize IT infrastructure resources and gain the flexibility needed to stay ahead of dynamic business requirements.

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Intelligently Distribute Resources for Agility

In our fast-paced world, organizations require flexible IT infrastructures that can quickly adapt to dynamic, real-time demands. With ActiveBatch, users can easily optimize the distribution of workloads to improve the likelihood of on-time, successful job completions while reducing idle machines by leveraging machine learning and predictive analysis.

Dynamic Queue Characteristics Locate Optimal Resources for Completing Jobs

Users can assign custom Dynamic Queue Characteristics, instructing ActiveBatch to evaluate multiple servers before submitting Jobs to the servers on which they will run. For example, execution machines can be monitored and evaluated at runtime for characteristics like available disk space, registry values, or the presence or absence of a particular application.

Dynamic Queue Characteristics are useful because it is difficult, time-consuming, and tedious for IT personnel to manually search hundreds (or thousands) of servers with specific characteristics to successfully run tasks. By assigning Dynamic Queue Characteristics, IT can pair Jobs with capable machines without having to hunt for the right specifications, saving time and reducing overhead costs.

White Paper for ActiveBatch DATASHEET:

ActiveBatch Workload Automation Overview

Driven by marketplace demands, regulatory requirements, and rapidly changing IT environments, IT organizations are leveraging automation capabilities. Learn how ActiveBatch helps IT meet marketplace demands, regulatory requirements, and rapidly changing IT environments with this in-depth datasheet.
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Improve System Usage with Visual Insights from Machine Load View

Users can better monitor system usage and available systems with ActiveBatch’s Machine Load View. Machine Load View provides IT Operations with a better understanding and accounting of how systems and resources are being used by both ActiveBatch and non-ActiveBatch processes. Machine Load View features visual heat maps containing refined performance counter graphs that identify heavily used, lightly used, and available systems.

ActiveBatch Smart Queue Reduces Idle Machine Resources

ActiveBatch offers several flexible, scalable tools that help IT monitor and manage virtual machines, and private- and public-cloud resources. For example, ActiveBatch Smart Queue facilities will dynamically scale resources up or down based on real-time demands and historical analyses of past scheduling periods. By implementing Smart Queue facilities, IT teams can optimize their virtual/cloud environments while minimizing unnecessary costs.

Machine Learning Powers Heuristic Queue Allocation for Seamless Scalability

ActiveBatch comes equipped with Heuristic Queue Allocation (HQA), a unique feature that leverages machine learning to optimize the allocation of Queues. HQA analyzes historical Instance data and environmental statistics to anticipate the optimal allocation of future Queues, intelligently distributing Jobs across available and acceptable resources to minimize slack time and reduce idle machine resources. With HQA, users don't need to assign individual machines to each Job; this scalable approach allows IT to operate with more agility and speed when responding to business requests and changing demands.

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