Client Background
The client is a large-scale automobile enterprise operating across multiple manufacturing plants, engineering hubs, and administrative offices. Their IT infrastructure supports critical engineering applications, production systems, and enterprise workloads that require stable and optimized system performance.
With thousands of machines running simultaneously, memory utilization monitoring became a critical aspect of IT operations. However, the growing volume of performance-related alerts and tickets created significant pressure on IT support teams, leading to delays in resolution and reduced operational efficiency.
Challenges
The organization needed a faster and more reliable mechanism to monitor memory utilization and manage related support tickets efficiently. However, several operational challenges impacted performance.
Some of the Key Challenges
- High volume of tickets generated for memory utilization alerts across systems
- Increased dependency on specialized IT resources for analysis and resolution
- Delays in identifying whether issues required escalation or simple closure
- Rising backlog of performance-related tickets affecting IT service efficiency
- Frequent escalations due to delayed response and manual processing
Our Solution
We implemented an RPA-based automation system designed to streamline memory utilization ticket handling and reduce manual intervention.
The solution automated key decision-making and operational steps within the ticket lifecycle:
- Bot logs into the IT service management portal and filters tickets related to memory utilization.
- It retrieves machine and user details associated with each ticket.
- Bot checks the current memory usage levels for the identified systems.
- If memory utilization is high, the ticket is automatically assigned to the appropriate IT engineer for action.
- If utilization is within acceptable limits, the bot closes the ticket with an updated status.
Automation Benefits
The implemented automation delivered significant improvements in IT operations and resource efficiency.