Types of Network Data
As software-defined networking (SDN) and Network Function Virtualization (NFV) continue to change how to design networks, it is increasingly becoming complex for IT to get a complete picture of the whole network. At the same time, it is becoming hard to measure key performance indicators (KPIs) precisely.
The organization usually uses individual tools to resolve problems to compensate. It may result in tool sprawl or rely on a single source of network data, including Simple Network Management Protocol (SNMP). However, that is no longer sufficient in the present hybrid IT landscape.
Eventually, organizations are increasingly deploying network performance monitoring and diagnostic (NPMD) in order to overcome these challenges. This is a platform, which collects and visualizes varied network data. The main goal is to manage the network from the data centers to the cloud or remote sites.
There are different types and formats of networking data. Each has pros, cons, along with unique characteristics. Most IT teams are monitoring these data types as much as possible. Here are they:
Network Telemetry Data
It is usually coming from networking devices at remote locations. Usually, around performance management, it is transmitted to monitor systems for off-net processing ad analytics. For network telemetry data, there are two primary sources, the flow data, and the SNMP data.
At tracking near real-time path data, this is where flow excels. It activates notifications and isolation of issues since there are changes in the network. On the other hand, SNMP data provides a methodology for network elements along with a subset of objects via the SNMP management information base (MB).
Synthetic Testing and Virtual Software Agent Data
When it comes to synthetic testing, it understands the user experience with an application by predicting its behavior. To ensure that users are getting the experience they expect, cloud applications can lack visibility as well as in performance data. It can continuously monitor applications by using virtual software agents and gathering data from them. It assures that applications are providing the latency and path quality required to achieve optimal performance for end-user.
Application Recognition Data
Applications running in enterprise networks require a variety of service-based levels on various business requirements. Therefore, to maintain performance, it is vital to have insights and data. Network-based application recognition is the next generation of the protocol. It offers a mechanism that can classify and regulate bandwidth for network apps.
Application Visibility and Control Data
Another important source is the application visibility and control data (AVC). It incorporates several technologies such as application recognition and performance monitoring into WAN routers. AVC is also tracking for a combination of metric providers, embedded monitoring agents, and flexible NetFlow. AVC includes bandwidth use, response time, as well as latency.
There are many ways to collect data in order to measure the performance of network applications. This will depend on what and where your resources are. Ultimately, to deliver a complete end-to-end view of the status of your network, you will need multiple data sets.