Splunk Dashboard Development for Elisa Navitas

Abstract

This thesis project was conducted in collaboration with Elisa’s Navitas team and focused on the development of a centralized log monitoring dashboard using Splunk. Navitas is a critical system responsible for transferring sensitive healthcare data between regions. Its log monitoring was previously handled manually, involving time-consuming and error-prone processes across multiple servers. The aim of the project was to improve system visibility and error detection through automated log collection and visualization. The study followed a product development approach and included system analysis, forwarder installation, SPL query development, dashboard design, and validation. Splunk was chosen for its advanced features, real-time monitoring capabilities, and existing use within Elisa, which allowed integration with the company’s infrastructure. During implementation, technical challenges included handling DEBUG-level logs containing confidential data, which were excluded from Splunk by rerouting them to local files. Organizational challenges involved delays due to limited availability of team members and access restrictions within the Splunk environment. The final solution included a functioning dashboard with interactive visualizations for adapter errors, login events, and system-level logs, enabling faster troubleshooting and trend detection. The results showed improved efficiency in identifying issues, enhanced security monitoring, and a scalable foundation for future development. Recommendations included expanding the monitoring scope to production systems, applying machine learning for anomaly detection, and implementing alerting features. This work demonstrates how centralized log management can support proactive IT operations in a secure and efficient way.