Network analytics can deliver positive results, particularly for organizations embracing automation and undergoing significant digital transformation. When implemented properly, network analytics promises to reduce the time needed to repair outages, fine-tune capacity and proactively stop network problems. Additionally, effective use of network analytics can help drive down costs and improve service delivery.
One challenge facing many organizations is how to integrate existing network monitoring and analytics. Deploying new analytics technology in conjunction with legacy network monitoring tools and management systems can be a headache. These management platforms typically gobble up vendor-specific data from routers, switches and wireless LAN gear.
However, many analytics products cannot import proprietary telemetry data. This limits the specificity of the information the analytics software can assess. As a result, you may need to obtain this data manually, an exercise that could be too onerous for the IT group to tackle.
Network monitoring and analytics complicate cloud environments
IT groups running hybrid cloud environments often select monitoring and management tools that work specifically with the cloud provider's platform. Here, too, the inability of the analytics software to seamlessly process that proprietary data creates the same roadblocks as those confronted within a traditional IT environment.
Analytics software that can't access relevant data limits the efficacy of the analytics. The workaround is to rely on APIs that can translate proprietary streams into information the analytics software can process.
Organizations evaluating analytics should assess whether it's time to swap out existing management and monitoring platforms for ones that are compatible with modern analytics software. New platforms and tools are more likely to work well with modern analytics tools.
Giving analytics the capabilities it's engineered to provide
It's important to allow analytics software to do its job, which is to capture data from standard monitoring and management protocols. Modern analytics software can also apply machine learning and associated AI methods to determine a baseline understanding of network performance. From this, along with data flow collection information, analytics tools can quickly identify anomalies and potential inefficiencies.
The goal of integrating network monitoring and analytics is to be alerted to performance issues as rapidly as possible, enabling the appropriate configuration changes or equipment fixes to take place with the least amount of manual intervention. A well-integrated analytics package not only helps reduce operating costs, but it also improves the end-user experience, ultimately leading to a big increase in productivity.