Network teams must predict how long existing infrastructure will be able to support the dynamic needs of the business, and what is needed to support future growth.
Network upgrades are costly and require a strategic process that delivers significant advance warning for budget and resource planning. To accomplish this, the network team needs a way to predict how long existing infrastructure will support the needs of the business, and then understand what new resources will be required to support future growth. The ability to accurately forecast and optimize resource utilization based on real-world data is key to achieving a strong ROI.
Measure resource utilization
The ability to associate users, devices, and applications with the consumption of bandwidth enables the network team to understand the resource utilization and effect each has on the organization. SNMP tools and MIBs only provide macro-level visibility and lack the ability to associate consumption to users and devices. AI/ML-driven predictive analytics help network operations teams accurately forecast WAN capacity requirements and closely align infrastructure investments with business demands. And you can gain additional insights by streaming data to external data lakes for business intelligence.
Support business agility
The network team must support the dynamic needs of the organization. Business-critical applications get added to the network without any consultation, yet the team is expected to seamlessly support them. The ability to measure resource utilization and predict when additional network capacity will be required, based on empirical data, is strategically important.
Improve application experience
A positive user experience requires an efficient, latency-free network environment extending from the user all the way into the public cloud. The ability to measure application performance and contrast that against network capacity enables the NetOps team to know when existing network resources are insufficient to support user needs.
Identify disruptive applications
As important as it is to have visibility into business-critical applications, network teams must also see when applications are disruptive to business operations. A great example of this is the ability to know when expensive WAN links are clogged with Netflix traffic. In this case, user complaints may have nothing to do with a capacity problem.
Network capacity management fundamentals
Proper network capacity management will ensure that your company is using your network more efficiently and not wasting money on bandwidth that isn’t needed. One of the largest benefits of collecting NetFlow/IPFIX is that you can trend this data for multiple years while retaining conversation granularity, allowing you to pinpoint exactly what application is causing the sudden increase in bandwidth utilization.
Cloud adoption drives SD-WAN to replace traditional WAN and capacity planning
When managing traditional WAN capacity, hope is not a strategy. You need a methodology to determine how much bandwidth is enough. You must have a clear understanding of your current state of application usage and you need the opportunity to collaborate with business operations to consider the impact of yet to be deployed applications.
Do you know how much of your company’s bandwidth is being used for BYOD and phone updates?
Do you ever feel as though no matter how much bandwidth you buy, it still isn’t enough? Phone updates aren’t the only thing dragging down network bandwidth, but they do contribute to a large amount of it.
Harness the power of ML to improve capacity planning
ML-driven analytics can help network operations teams accurately predict network capacity requirements. A data-driven approach to capacity planning can help optimize investments and user experiences.