Processes 5TB of data daily
Region Midtjylland ingests and analyzes five terabytes of security and log data every single day to protect critical healthcare infrastructure.
Monitors 3,000 servers and 35,000 endpoints
The security team maintains visibility across a massive estate, including 3,000 servers and 35,000 endpoints used by hospital staff and administrators.
Leverages machine learning for rapid threat detection
By integrating Elastic machine learning capabilities, the team has significantly reduced the time required to investigate alerts and create complex detection rules.
Region Midtjylland (Central Denmark Region) is responsible for healthcare services for approximately 1.3 million citizens. It operates a vast network of hospitals, psychiatric centers, and social institutions, employing over 30,000 people. With digital healthcare records and connected medical devices becoming standard, the region faces the critical task of protecting sensitive patient data against an increasingly complex threat landscape.
To safeguard its digital infrastructure, Region Midtjylland has partnered with Elastic to build a robust, data-driven security operations center (SOC). This partnership enables the region to monitor its expansive environment effectively while adopting cutting-edge AI technologies to stay ahead of cyber threats.
Securing a massive healthcare estate
Managing the IT security for a healthcare region of this size presents unique challenges. The infrastructure includes over 3,000 servers and 35,000 endpoints scattered across numerous hospitals and clinics. The volume of data generated is immense, with the security team ingesting approximately five terabytes of log data daily.
Previously, the region faced difficulties in gaining a unified view of its security posture. The sheer volume of data made it challenging to isolate genuine threats from background noise. Jørgen Metzdorff, head of security operations at Region Midtjylland, recognized the need for a solution that could handle this scale while providing actionable insights.
"We needed a platform that could digest massive amounts of data without slowing down our operations. Elastic provided the scalability and speed we required to monitor our entire estate effectively, ensuring that we can protect patient data around the clock."
Accelerating detection with machine learning
A key component of Region Midtjylland’s security strategy is the use of Elastic’s machine learning capabilities for anomaly and outlier detection. In a high-pressure environment where every second counts, the ability to identify unusual behavior and surface potential threats early is invaluable.
By applying machine learning to large volumes of security data, the team can detect patterns and deviations that might otherwise be difficult to spot through manual analysis alone. This helps analysts prioritize investigations faster and focus their attention on the events that matter most.
“Elastic’s machine learning capabilities have transformed how our analysts work,” says Metzdorff. "It acts as a force multiplier, allowing us to interpret alerts and build detection rules much faster than before. It empowers our team to focus on high-value decision-making rather than getting bogged down in syntax."
Looking ahead, Region Midtjylland sees Elastic AI Assistant as a natural next step in its security journey. As the team continues to mature its operations, AI-driven support for investigations and query creation represents an exciting future opportunity to further improve speed and efficiency.
Unified visibility across the region
Transitioning to Elastic has allowed Region Midtjylland to consolidate its monitoring efforts. By treating security as a data problem, the team can ingest logs from diverse sources — network devices, medical equipment, and administrative systems — into a single, searchable platform.
This unified visibility is critical for maintaining operational resilience. The team can now correlate events across different parts of the infrastructure, identifying patterns that might indicate a coordinated attack or a system anomaly.
"With Elastic, we have a holistic view of our environment," notes Metzdorff. "Whether it’s a server in a regional hospital or an endpoint in a psychiatric clinic, we have the visibility to detect anomalies and respond immediately. This comprehensive coverage is essential for maintaining the trust of the 1.3 million citizens we serve."
Future-proofing with open, flexible architecture
Looking ahead, Region Midtjylland plans to further deepen its use of Elastic’s capabilities. The flexibility of the platform allows the region to adapt to new healthcare technologies and security standards without overhauling its core infrastructure.
The team is currently exploring ways to expand their use of machine learning to predict potential security incidents before they occur. By analyzing historical data and usage patterns, they aim to shift from a reactive stance to a proactive defense strategy.
