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Scheduling Analytics

Optimize your resources and improve SLA success rates with ActiveBatch's dynamic scheduling analytics capabilities

Intelligent Automation at your Fingertips

ActiveBatch allows users to optimize their resources while scheduling and executing workloads to ensure that service-level agreements (SLAs) and business deadlines are met. Scheduling Analytic tools combine historical and predictive analysis by measuring behavioral insight such as historical workflow performance, resource availability and capacity, and upcoming workload schedules, to make predictions about possible future workflow execution times and durations.

Scheduling Analytics consists of: 

  • SLA Monitor - Concerned with workflows and jobs that have been marked as SLA-sensitive. This view provides a single place in which you can observe SLA statistics as well as summary and detailed information concerning SLA-tied executing workflows and Jobs.
  • Analysis Dashboard - Provides access to OLAP-generated dashboards and reports for easy display and analysis.
  • Critical Path Analysis – Provides statistics information about workflow runtimes and SLA satisfaction rates as well as real-time critical path analytics as workflows are executing.
  • Quick-access summary views containing information concerning Managed Queues and SLA-marked Plans and Jobs.

Additionally, Scheduling Analytic tools interact with ActiveBatch's Smart Queue to ensure that virtual and cloud-based systems are appropriately provisioned. ActiveBatch's ability to intelligently automate the provisioning and allocation of resources to ensure the successful completion of workflows is critical to reduce the cost of IT operations.

Datasheet Resource on ActiveBatch DATASHEET:

ActiveBatch Workload Automation Overview

Driven by marketplace demands, regulatory requirements, and rapidly changing IT environments, IT organizations are automating increasingly complex business and IT operational processes that span distributed environments comprised of various applications, databases, technologies, and process types. As a result, organizations need to automate workflows in order to quickly and reliably pass data and manage dependencies between systems and technologies.
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