Managing a network requires continuous evolution to keep up with the network technology changes. The number-one challenge faced by network operations teams is a lack of end-to-end network visibility, according to Enterprise Management Associates (EMA) research. The teams have an incomplete picture, especially as networks scale and grow in complexity and as applications start to migrate to the cloud. Device health, ping tests, traceroute, and mining the command line interface (CLI) aren’t no longer sufficient. Network managers must have a baseline for what is normal and acceptable.

EMA research further states that EMA research reveals that network teams spend 36 percent of their work week fighting fires in reactionary troubleshooting mode, and they spend another 35 percent of their week proactively preventing problems. This means that the typical enterprise devotes only 29 percent of its network engineering talent to strategic projects.

Furthermore, Gartner projects that by 2025, 70% of digital business initiatives will require Infrastructure & Operations leaders to report on the business metrics from digital experience, up from less than 15% in 2020.

NPM Tool Fragmentation Is The Core Problem

Many network managers are trapped in firefighting mode because they use a fragmented set of vendor and third-party network monitoring and troubleshooting tools. Cirries estimates that 40% of network managers use 4 to 10 tools to monitor and troubleshoot the network, and another 35% use 11 or more tools.

This tool fragmentation results in a cycle of constant firefighting. In fact, on average, 40% of all network problems are detected and reported by end users before network operations is aware of them. Tool fragmentation makes this problem worse. In organizations where network managers use 11 or more tools to monitor and troubleshoot networks, end users detect an average of 52% of network problems before IT operations is aware. By the time network managers start working on these tickets, end users are already suffering from poor performance and lost productivity.

These large management toolkits present inherent disadvantages. First, many of these tools focus on only one area, whether it’s applications, the data center, the wireless LAN, the Ethernet LAN, or the WAN. When network teams rely on a large set of discrete tools, they often spend too much time acting as human middleware, performing manual data correlation and analysis across multiple tools.

To properly manage a network, Network Performance Management (NPM) tools, Application Performance Management (APM) tools and Digital Experience Management (DEM) tools must be implemented and work in concert to provide an overall and complete view of the network performance as seen by the user. Anything short of that will lead to loss of users and competitiveness. This overall function encompassing NPM, APM and DEM is described as Total Network Performance Management (TNPM)

Traffic volume analysis, end-user experience insight, and performance data trending are the three most important and valuable features of an TNPM tool.

So, what do you do to ensure Network Excellence?

Deploy a TNPM tool that ensure the network performance, application performance and digital experience KPIs are met. This tool must automatically identify and resolve network connectivity issues to maximize end-user’s quality of experience and machine-to-machine performance.

How do you do that?

Implement an TNPM solution that includes Machine Learning and Workflows to discover and automatically identify and eliminate network outliers in real time. Its time you let your network tools keep up with the changing network landscape.

Total Network Performance Management (TNPM) software must include real time analytics augmented with machine learning and workflows to manage the millions of applications, processes, and network data points of your network. The data must be filtered, dissected, and humanized to be useful. TNPM can collect and monitor the key performance indicators for all device types, identify applications, and generate reports for your complete infrastructure. 

Why is TNPM needed?

Simply put, humans can no longer keep up with the hundreds of alarms being generated and have no idea which are the most critical.

Unfortunately, up to 95 percent of network alert investigations are still performed manually, resulting in operational costs two to three times higher. An TNPM solution to crunch the data and prioritize anomalies is essential for network operators to keep achieving greater IT efficiency, consistency, and service health.

TNPM reduces investigation of alerts from hours to minutes or even seconds.

TNPM uses algorithms to parse data, learn from it, and decide or predict without requiring explicit instructions. Imagine combining quality data, domain expertise, and syntax (metrics, classifiers, root causes, correlations, and ranking) to provide predictive recommendations on how to remediate existing issues.

  • Detecting network anomalies
    Can detect network anomalies with a correlation that allows quickly finding relationships between events that would not be obvious to even a seasoned network specialist.
  • Event correlation and root cause analysis
    Uses various data-mining techniques to explore terabytes of data in a matter of minutes. This ability quickly identifies what network element most related to a network problem, accelerating resolution.
  • Dynamic Bandwidth Allocation
    Today, bandwidth allocation happens largely through capacity planning and manual adjustments. TNPM can predict bandwidth capacity requirements based on usage trends and current network data analysis.
  • Self-correcting
    Identifies problems and provides the most probable actions to fix. TNPM -driven networks capture and analyze the data that correlate events not normally detected without the analysis of massive amount of data over time.

TNPM can discover every element and devices on your network and create a baseline of all network functions and data flows then continuously compare that baseline to your real time traffic to discover performance anomalies whether caused by congestion, application latency, equipment failures or an infection.

TNPM monitors service-impacting network events caused by changes in utilization levels, memory leaks and other abnormalities. TNPM’s streaming analytics driven alerting technology automatically monitors Key Performance Indicators (KPIs) for the customer, alerting when a KPI is not being met.


The best-of-breed TNPM solutions not only deploy and integrate effectively from data collection and reporting standpoints but provide an open architecture for integrating with upstream fault management and trouble ticketing systems. Besides the ability to sending and receiving trap notifications, the operator can “launch-in-context” instant reports when they are troubleshooting an infection or outage and need detailed network health data.