CASE STUDY
Enhancing IIB & ACE Infrastructure with Dynatrace Implementation: A Success Story with ArcelorMittal
About The Client
ArcelorMittal, a global steel and mining company headquartered in Luxembourg, is a key player in the steel industry. With a presence in over 60 countries and a commitment to sustainability, they produce high-quality steel products for various sectors. Their innovative solutions and dedication to environmental responsibility make them an industry leader.
Industry | Manufacturing
Solutions | IIB & ACE
Location | Luxemburg
Business Challenges
- Comprehensive Cluster Performance Monitoring: The client needed real-time visibility into resource utilization and performance indicators for their EKS clusters to proactively optimize cluster performance.
- Resource Utilization Insights: They sought to monitor CPU, memory, and storage consumption for better resource allocation in EKS clusters.
- Efficient Resource Allocation for Cost Optimization: By monitoring core utilization and performance metrics, the client aimed to make data-driven decisions for cost-effective EKS cluster management.
- Granular Core Utilization Tracking: Tracking core utilization at both cluster and API levels allowed efficient resource allocation and bottleneck identification.
Business Solutions
- Extended Data Retention: Dynatrace extended data retention, allowing the client to archive historical performance data for comprehensive analysis, without overloading the system, aiding long-term performance improvements
- Real-Time Monitoring: Dynatrace provided real-time CPU and memory monitoring, ensuring continuous oversight of cluster and workload-level resource utilization, facilitating quick decision-making.
- Threshold Alerts: Dynatrace's alerting system promptly notified the client of performance threshold breaches. This enabled swift responses to potential issues, minimizing disruptions to their EKS workloads.
- Optimized Performance: By implementing Dynatrace, the client successfully optimized resource utilization, improved EKS cluster performance, and ensured the stability and efficiency of their containerized workloads on Amazon EKS.
Key Outcomes
20% Increase in Resource Efficiency
20% Increase in Overall System Stability
25% Reduction in Downtime
Improved Visibility By 100%
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