Workload Automation Re-imagined with AI-based Analytics
Complementing automation domain-specific intelligent analytics.
As workload automation evolves to become more strategic and critical to business operations, there is a need to complement automation with intelligence. Today’s complex workload ecosystems can no longer be managed by workload automation tools and schedulers alone and need to be combined with the advantages of artificial intelligence, Machine Learning, cross-platform visibility to ensure resilient IT operations.
This paper discusses how workload analytics can fulfill such requirements by complementing workload automation tools with AI-based multi-level analytics that help IT operations become more proactive and strategic. You will learn:
- Scope and challenges in workloads automation
- Analytics for efficient SLA compliance, predictive operations, and strategic planning
- How workload automation can evolve beyond batch jobs
