# Railway Cloud Resource Management as a Service
## 3 Fault Management of Railway Cloud Resources  
### Fault Management Use Cases  
Fault management and performance management are two pillars of railway cloud resource management. They are highly related and independent, and address two different aspects of cloud health. While the fault management deals with detecting and isolating cloud problems, performance management focuses on monitoring for proactive warning of cloud performance degradation. Cloud fault management (FM) typically encompasses several key aspects:  
_Notification_: alerting cloud operator when a fault is detected, so a prompt action to resolve it could be taken;  
_Detection_: identifying faults and localizing problems;  
_Analysis_: investigating the root cause of the fault to understand its nature and impact on the system;  
_Resolution_: implementing corrective actions to resolve the fault, such as restarting services, patching software, or replacing hardware. Effective cloud FM strategies include tight integration with performance management, aimed at proactive monitoring which regularly checks for potential issues before they become major problems, automated remediation enabling the use of automated tools and scripts to quickly resolve common faults and minimize manual intervention, and incident management which implements a structured approach to managing incidents, including notification, analysis, and resolution. The detection aspects of cloud FM include, for example, the following: anomaly detection that uses patterns or events that derivate from normal behavior, such as unusual login times or unexpected changes in CPU usage; predictive analytics that use statistical models, machine learning algorithms, and historical data to predict when a fault is likely to occur; real time processing that analyses real-time data streams from cloud sources to detect issues before they become problems; and root cause analysis related to investigating the underlying causes of the problem. The notification aspects of cloud FM are related to alarm management and notifications alerting the cloud operator when a fault or anomaly is detected, including notifications about disk space exceeding threshold, high CPU usage, unusual network traffic, etc. The analysis aspects of cloud FM, in addition to root cause analysis, include troubleshooting, which involves methodical steps taken to identify and resolve a fault or anomaly, such as checking system logs, network traffic, and cloudified function performance, and testing different configurations, versions, or approaches to identify the problem cause. The resolution aspect of cloud FM involves implementing changes or fixes to resolve a fault or anomaly that has occurred in the cloud infrastructure or applications, and may include applying patches or updates of software components, updating system configuration, or deploying new versions of cloud platform software or cloudified applications. The detection and notification of cloud FM could be synthesized as a Cloud Resource Fault Management (CRFM) service. Typical use cases for railway cloud FM include alarm configuration, subscription management to alarm notifications, notifications of alarm occurrence, acknowledgement and clearance, and retrieval of alarm information. A fault is an error that the railway cloud resource detects. The railway cloud resource logs and stores all detected faults. To be notified about cloud resource faults, a cloud management (CM) application in the RMAO needs to subscribe to notifications of alarms. An alarm is a notification of a problem that needs the attention of the subscriber. To filter alarm notifications the cloud management application defines the subscription criteria. Figure 1 illustrates the communication model for an alarm subscription between a CM application in the RMAO and the CRFM service. The railway cloud operator provides a notification criterion to initiate the subscription. The CM application sends a subscription request, which identifies the subscriber to the CRFM service.