CASE STUDY: RES Suite supporting batch capacity planning and forecasting
Batch-Watch, with its Predict capabilities, supported a major Italian banking group in assessing in advance the impact of increasing batch workloads resulting from the acquisition and integration of another banking institution. The analysis transformed historical data and current monitoring information into predictive scenarios, supporting capacity planning, integration activities and the definition of corrective actions.
THE CONTEXT
The Italian banking group was undergoing an evolution of its IT environment and the integration of new business entities. As part of this process, it needed to assess in advance the impact of increasing workloads on its batch infrastructure.
The objective was to determine whether the existing batch infrastructure and workload management model could support the expansion of the operational scope without causing slowdowns, bottlenecks or service disruptions.
The customer therefore needed to move from a monitoring-based approach to a predictive one: analysing actual batch behaviour, estimating available capacity, identifying the most sensitive areas and preparing any corrective actions in advance.
THE CHALLENGE
The challenge was to turn historical data and current monitoring information into a reliable basis for predictive simulations.
Predicting the impact of workload growth does not simply mean assuming a linear increase in volumes. It requires understanding how new workloads interact with existing processes, which time windows may become more critical, where congestion could occur and what capacity margins are actually available.
In a complex environment, this type of analysis requires an accurate understanding of real-world batch behaviour and tools capable of projecting future scenarios based on objective evidence.
THE SOLUTION
RES supported the customer through Batch-Watch, used both to monitor and control workloads and to leverage its Predict capabilities.
The project allowed the customer to:
- analyse actual batch behaviour;
- consolidate reliable data on existing workloads;
- build predictive scenarios;
- simulate the impact of an expanded operational scope;
- identify potential areas of concern in advance.
The value of the solution lay in its ability to estimate the impact of workload growth on the batch infrastructure before it occurred.
This enabled the customer to assess the effects of the integration process in advance and take action before potential issues could affect operations.
Batch-Watch provides effective predictive support for managing growth, integration and transformation scenarios in the banking sector.
THE BENEFITS
Effective prevention of critical issues
The bank was able to identify potential issues related to workload growth in advance, allowing corrective actions to be planned before they could impact operations.
More accurate batch capacity planning
Predictive scenarios made it easier to assess the resilience of the batch infrastructure. The customer could estimate available capacity and plan any necessary interventions.
Greater control over workload evolution
Predicting batch behaviour helped the customer monitor workload evolution in a more structured way, reducing uncertainty during a critical integration phase.
