# Network Availability

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The minimization of network downtime is crucial for the efficiency and reliability of modern business operations, as network availability directly impacts productivity, customer satisfaction, and revenue. In today's interconnected world, where many business processes are dependent on networked services, even a small amount of downtime can lead to significant operational disruptions and financial losses. To mitigate this, a proactive approach to network management and monitoring is essential.

ElastiFlow provides a collection of anomaly detection jobs designed to identify network availability-related issues which play a pivotal role in this proactive approach. These jobs are engineered to quickly detect and alert network administrators about potential problems that could lead to network downtime or degraded performance. By identifying such issues early, these tools enable timely intervention and resolution, minimizing the impact on network services.

#### Downloads

| Schema    | Link                                                                                                                                                       |
| --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **CODEX** | [All Availability ML Jobs for CODEX Schema](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/codex/availability/availability.json) |
| **ECS**   | [All Availability ML Jobs for ECS Schema](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/ecs/availability/availability.json)     |

By employing these anomaly detection jobs, organizations can swiftly identify and address issues that threaten network availability. This collection provides comprehensive coverage of critical network components and interactions, ensuring that any potential issues are identified and resolved before they escalate into significant problems, thereby maintaining optimal network uptime and reliability.


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