what Data
To elevate the efficacy of AI/ML-fueled endeavors in Network Operations, an array of diverse data inputs is indispensable. Here is an elaborated list of the top ten sources:
1. **SNMP (Simple Network Management Protocol)** - This protocol is instrumental in aggregating and structuring data regarding devices under management within IP networks, simplifying the modification of device functions to streamline network management.
2. **Telemetry** - This technology employs sensors and telemeters for the autonomous collection of data concerning various metrics such as pressure, velocity, and temperature. Such data is paramount for real-time performance monitoring.
3. **Log Data** - These are chronicles of events transpiring within the network. Understanding these logs is vital for discerning system performance, security events, and operational quandaries, offering insights pivotal for AI/ML-driven analytics.
4. **CMDB (Configuration Management Database)** - This database holds crucial details about all significant components of an information system, encompassing their configurations and interrelations, and is essential for adept management of network operations.
5. **NetFlow/sFlow** - These tools provide insights into network traffic flows and volumes, aiding in network monitoring, capacity planning, and the identification of security threats.
6. **API (Application Programming Interface) Data** - This category involves data exchanged between network management systems and devices or other software via APIs, which is critical for automating processes and integrating systems.
7. **Performance Metrics** - This data encompasses metrics on device and network performance, including latency, error rates, and throughput, crucial for sustaining optimal network operations.
8. **Device Configurations** - Information pertaining to the settings and configurations of network devices, necessary for comprehending the network's structure and behavior.
9. **Security Logs** - Logs that record security-related events, essential for developing threat detection and response strategies.
10. **Environmental Data** - This includes external factors such as temperature and humidity that might impact network hardware and infrastructure, vital for preventive maintenance and operational planning.
These data reservoirs furnish the comprehensive insights necessary to propel AI/ML applications in network operations, thus enhancing both the efficiency and reliability of network systems.