Network analytics help IT teams manage and secure data networks, improve security, fine-tune performance, troubleshoot network problems, predict traffic trends, perform forensic investigations for incidents and open new business opportunities in some cases
As enterprise IT ecosystems grow IT teams, tasked with safeguarding data and ensuring critical systems remain resilient, are confronted by a harsh reality – “you can’t protect what you can’t see.” Having the ability to monitor everything that is happening in your network is the first step in improving the security, performance, and reliability of your environment. But how you capture, interpret, and respond to that sea of data from your network is what ultimately allows you to truly take control of your operational environment. This is where real-time network analytics comes into play.
This holds especially true for complex, overtaxed or high-security networks such as those seen in the Middle East government, Financial Services, Telecom, Healthcare and other sectors. Additionally, being able to capture and store network data allows historical network performance reports to be generated – a vital tool in maintaining system health, data security and optimising I/O transfer speeds between connected devices. IT teams can also quickly identify, isolate, and quarantine incoming malware, viruses or worms by using real-time packet scanning to identify threats.
Network analytics help IT teams manage and secure data networks, improve security, fine-tune performance, troubleshoot network problems, predict traffic trends, perform forensic investigations for incidents and open new business opportunities in some cases.
Real-world network analytics applications
Though every enterprise network can benefit from analytics, for some industries the benefits can be manifold. For example, telcos can use network analytics to manage high volumes of user traffic in mobile communications and broadband connections. The same technology can assist mining and oil and gas companies in monitoring remote IoT devices that regulate pipelines, drilling, and reservoir facilities. The automotive and high-tech industries can extensively use real-time data analytics to develop self-driving vehicle networks and implement Artificial Intelligence (AI) and Machine Learning (ML) guidance for autonomous vehicle navigation.
Streaming real-time data analytics opens innovation opportunities across all industries based on Big Data applications, AI and ML.
How does network analytics work?
Network analytics works by providing insights into various aspects of network performance. With it, teams can monitor latencies for traffic through its entire path with hop-by-hop analysis, or the bit rates through a particular network port, broken down by application. They can see collision and packet drop rates at a port or observe the number of packets or flows from any location, device, application, or identity. Diving deeper, they can see the number of packets or flows affected by specific security policies, and carry out infrastructure monitoring for SNMP, WMI, and increasingly streaming telemetry.
The visibility and insights presented by network analytics can be used for several tasks, such as identifying and mitigating bottlenecks, evaluating the health of devices, root-cause analysis, issue remediation, identifying connected endpoints, and probing for potential security lapses.
Safeguarding networks and driving business growth
Network analytics offers a wide range of benefits beyond traffic analysis:
- Enhanced Security: Network analytics improves cloud resource and device security by allowing real-time scanning of data packet transmissions. Administrators can track I/O data packet resource consumption by IP address to detect anomalous changes in activity and quickly identify intruders, malware, and infected devices.
It also speeds up the detection of security threats, preventing hacking attacks from spreading deep into the corporate infrastructure. Network analytics can not only track the path of a compromise through the network in real-time but also can be used to retrospectively investigate once a new attack vector has been identified and understood.
- SNMP and WMI Filtering: Data can be used to diagnose network device problems and reduce remediation time.
- Real-time Analytics: Integration with AI and machine learning provides real-time and historical insights into network data, enabling tailored operations.
- Streamlined Business Processes: Analytics optimises enterprise-wide IT operations, security, and efficiency while streamlining business management.
- Performance Monitoring: Administrators can monitor performance, including historical usage patterns that help predict future data centre needs.
- Track KPIs: Network monitoring tools can analyse KPIs and present them to administrators, simplifying complex cloud network reporting and alert processes. IT teams can track specific KPIs for their specific industry application.
As networks have become more complex and security requirements have increased, we need an automated way to correlate, interpret, analyse and respond. Network analytics empowers IT teams with the visibility they need to not only protect their organisations’ most prised digital assets, but also enhance customer and employee experiences by delivering performance gains.