Network analytics
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What is network analytics?
Network analytics is the process in which transmission of network data is collected and evaluated to increase the performance, visibility, or security of the network. In-network analytics, Network layer (Layer 3) of the Open Systems Interconnection (OSI) model, established by the International Organization for Standardization (ISO), receives the transmission of data. Where, the layer 2 devices, run by the switches, operates on the media access control addresses (MAC address). Similarly, the Transport Layer (Layer 4) of OSI model devices provides transmission of data associated with the webserver. Layer 3 device simply combines the functions of a switch and a router. It connects devices, which are on the same subnet and Virtual LAN (VLAN). A layer 3 switch operates on the MAC address and Internet Protocol (IP) routing table. Due to development of ecosystem and new switch, router, and firewall technology standards, network analytics application integrates information from Layer 2 and transport layer devices simultaneously.
The administrator uses Logs, reports, or graphs by utility software to have hourly, daily, monthly, and yearly representations of events that occur on a particular network or maybe on user-based and endpoint device activity. The most significant Protocol at the network layer (layer 3) is the IP address that controls the packet transmission from one-end nodes to another. Network analytics mostly improves the internal structure of existing data through monitoring Layer 3 Processes by arranging the information in a uniform pattern to highlight the data abnormality. Due to the increasing power of web server hardware, employees can view the packet transmission across the cloud architecture in real-time through network analytics. Machine learning (ML) techniques are essential to network analytics that allow better automation in telecommunication, e-commerce, and production industries.
What problems do network analytics solve?
Prediction: Network administrators review the usage Patterns timely to predict their needs for bandwidth, hardware, or other services.
Automated Security: It needs the real-time scanning of data packet transmission through AI and ML to remove or identified known security exploits, viruses, or malware. If the bad IP repeatedly send bad requests to a network, then automated security block the bad users, and it can detect and quarantine without the human intervention. Security scanner and automated anti-virus are the prominent uses of network analytics. Automated anti-virus and security scanning are important uses of network analytics.
Diagnostics: whenever there is a problem that occurs due to jamming, bad user actions, security threats, or device failure, system administrators need to diagnose each problem to repair or resolve the issue. Network analytics has a health check function with allows the administrator to launch diagnosis for data center operation. Admins cover network diagnostics with increased granularity to observe consecutively running application processes, with application-centric infrastructure. Admins use running telemetry to improve data transmissions for specific software, devices, or users on network-based IP addresses through routing and hub appliances.
Resource allocation: Complex associations use network analytics so that the administrators can accurately predict the numbers for switches, routers, hubs, and bandwidth that are needed in daily operations or industrial facilities.
Network analytics: It is used to offer administrators a synopsis of chronological or real-time activity on cloud architecture.
Benefits of network analytics
Business process optimization: Network analytics optimize the business process: corporate management, purchasing, and procurement with greater security and efficiency.
Greater accuracy in performance monitoring: Network analytics allow administrators to use performance-monitoring tools, which include historical patterns of practice, that allow them to calculate forthcoming infrastructure to fulfill the requirement for the data center.
Improved security: Network analytics allows the real-time scan of the data packet, which enormously increases the security of online assets and connected devices. To identify intruders, malware, and infected devices, IP addresses can be recorded to automatically detect spikes inactivity.
Rapid detection of security threats: Network analytics increases the speed of recognition of security threats, which is the main feature in avoiding the spread of hacking attacks into the business infrastructure. The ability to view connected device status by SNMP and Windows Management Instrumentation (WMI) cleaning data can allow users and security defense systems with broad means of identifying network complications, increase the time needed for repairs.
Ability to apply real-time streaming analytics to “Big Data” requirements: Companies can apply real-time streaming analytics to “Big Data” necessities to upgrade fraud protection on financial transactions or to use IP addresses for better location-based marketing. AI and machine learning can be used to build prediction-based content for unique customer production in e-commerce platforms product/media recommendations.
KPI tracking: KPI Workflow Manager analyzes key performance indicators (KPIs) and allows administrators to use them to make simpler the reporting and alert process for intricate online networks. KPI tracking is an influential device for the business with applications in high finance, mass media, engineering, medical, and telecommunications that can be modified for better levels of data center automation.
