What are the cons or challenges of Flow and Packet data?
Start with: The Pros and Cons of Flow and Packet Data - Part 1
While Flow data offers a high level of traffic visibility, it has little detail about what's actually flowing. For example, you can't see microbursts, or the amount of time an application spends churning on a request. It can also present complications for flow monitoring at the edge (small, remote offices), since many edge routers aren't full-featured enough to offer xFlow.
And although xFlow come "for free," it does put an extra processing load on the router, especially when the router is very busy, and this can lead to gaps in visibility when you need it most.
Finally, flow sampling is sometimes used to reduce the processing load on the router, making security detection much less effective since some flows, and perhaps the flows in question, may not be reported on due to sampling.
When it comes to Packet data, dedicated hardware and cabling are required between mirror ports on a router and a DPI application or appliance. This means there's more equipment to purchase, configure and maintain. Furthermore, when routers get busy the processing power required to mirror data can be reduced, resuling in some data not being mirrored, thereby reducing the effectiveness of the mirrored data. This can be addressed by using network taps or packet brokers, but this introduces even more hardware into the solution.
Packet data also requires specialized tools for analysis and a high level of expertise to be used effectively. To reap the benefits of packet data, organizations need to invest in solutions like protocol analyzers and have NetOps teams that understand how to use them. It also adds more complexity to network management, as network engineers need to be very aware of what data they want to monitor, and then ensure that the data mirroring they originally configure remains relevant as other network changes are made.
And the use of HTTPS and VPNs that create privacy tunneling is making packet payload analysis more challenging, often limited to specific instances where the keys for decryption are known for specific network flows.
What are some common ways to use Flow and Packet data to troubleshoot network performance?
The more complex underlying network problems are, the more sleuthing and expertise in protocol and packet analysis are needed. End-to-end visibility extrapolated from Flow and Packet data aids network troubleshooting at the most critical levels and sets the stage for further monitoring integrations that track application performance and sophisticated user experiences.
By using network monitoring solutions (like NPMD and NDR), finding the answers to common issues can be simplified. Here are four ways Packet and Flow data can help.
Topological Views
These views use Flow and Packet data to provide a comprehensive map of network performance. This helps Netops teams to identify infrastructure components in need of upgrading or replacement, and perform capacity planning. They also help when maintaining a real-time comprehensive device inventory, can trigger automatic device discovery, can help to proactively identify choke points on the network, and can be used to compare different performance metrics.
Flow Path Analysis
This is used to identify possible routes, hops, and network latency impacts across endpoints based on IP address. Packet and flow data allows Netops to identify issues caused by load balancing and to identify other issues caused by routing, such as sudden changes in network latency and poor performance of real-time protocols, typically voice and video.
Application Monitoring
Establishing performance baselines that can be used to monitor for abnormal traffic levels is crucial for application performance. Flow and Packet data allows NetOps to uncover insight into how the network is being used at the application level. For example, by identifying policy weaknesses that have allowed unwanted usage.
Intrusion Detection and Prevention Monitoring
Having insight into Flow and Packet data allows NetOps and SecOps to identify a known attack or type of attack based on its signature (signature-based). Teams can also identify deviations from the norm of network behaviors (anomaly-based) or the norms of protocol use (stateful protocol analysis).
Oftentimes, enterprises have seen Flow and Packet data as mutually exclusive — that one can be utilized without the need for the other — but the truth is that when combined NetOps teams can gain more complete visibility. This helps to protect against security threats, investigate alerts and ensure the overall performance of the network and applications.