IT groups must support many applications and servers across multiple platforms that frequently operate independently of each other. However, coordinating job scheduling across all these applications and networks is often required to optimize resource utilization. The traditional approach of applying more staff, toolkits, and rudimentary scheduling software to cobble together automated batch processing solutions becomes cost-prohibitive, inefficient, and error-prone, as the number of moving parts increases and the environment becomes more heterogeneous.
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