Enterprise networks have evolved beyond recognition. What once centered on a hub-and-spoke topology with a single data center now sprawls across UCaaS platforms, SaaS applications, public clouds, colos, and remote sites. Each environment generates telemetry using different protocols, timestamps, and data formats, creating a fragmented visibility landscape where IT teams struggle to distinguish signal from noise.
To understand how organizations can restore clarity to this chaos, The Tolly Group spoke with Eileen Haggerty, who has spent more than 20 years working with NETSCOUT's enterprise performance management customers. The conversation revealed how architectural decisions made decades ago continue to differentiate deep packet inspection from alternative monitoring approaches.
The Multi-Environment Visibility Challenge
Modern networks no longer have a single point of aggregation where visibility tools can capture everything. Traffic flows directly between remote sites and cloud services, bypassing traditional monitoring points entirely. This distributed reality creates blind spots in predictable locations: SaaS applications, UCaaS platforms, public and private cloud environments, third-party colos, WAN links, and remote sites. Many organizations assume they have adequate visibility because they receive dashboards from various providers. The problem is not the absence of data but rather inconsistency in data quality and format.
"Everything from UCaaS and SaaS and colos and public cloud," Haggerty explains. "Historically that wasn't the case. It was a data center. Everything was centralized. The challenge for many of these organizations is when they utilize tools with different data sources and sampling intervals, they may conflict with each other, which elongates troubleshooting time and then impacts the ability to really maintain a network that today's users expect," Haggerty notes.
The Source of Truth Problem
Many monitoring solutions rely on sampled flow data, aggregated metrics, or incomplete telemetry that lacks layer 7 application visibility. Each vendor formats data differently, uses different timestamps, and provides different batching intervals.
"Packets cannot be manipulated," Haggerty explains. "Every one of those packets that come through will behave and look the same as opposed to using a variety, whether it's NetFlow or MIB2 or metrics, events, Logs and traces (MELT). They're different, don't match, won't be the same and don't have the same timestamp."
When performance issues span multiple environments, inconsistent data sources make root cause analysis nearly impossible. Teams waste hours attempting to correlate sampled flow records from one vendor with aggregated metrics from another, all while users experience degraded service.
One common misconception Haggerty encounters are that organizations believe they have "enough tools." The reality is more nuanced. "Maybe you have enough, but they aren't complete," she explains. These incomplete data sources are sampled, lack seven-layer application visibility, or create inefficiencies when trying to correlate information across different vendor implementations.
NETSCOUT's Architecture: Processing at the Source
NETSCOUT addresses the data consistency challenge through an architecture based on processing packets at their source rather than shipping raw packet data across the network for centralized analysis. This approach eliminates the network overhead of transporting massive volumes of packet data, enables real-time processing without introducing latency, and removes the need for middleware that other solutions require.
"We're not shipping it off over the network, posing your network with excess data that may or may not be meaningful," Haggerty explains. The distributed architecture also reduces power consumption and infrastructure costs while allowing for scalability of performance and better modulation of infrastructure costs.
NETSCOUT's deep packet inspection using Adaptive Service Intelligence technology provides real-time Smart Data for analyzing service performance, user experience, security threats, and historical reporting capabilities across complex physical, virtual and cloud environments. NETSCOUT's distributed processing architecture ensures that packet-flow analysis is performed at the source of capture and only necessary metadata sent to the analytics platform which reduces unnecessary strain on the network and eliminates the need for expensive middleware and correlation engines and allows customers to make their own decisions about packet storage. Many customers do not need to store packets because the deep packet inspection is so efficient, though the option remains available for those who require it.
Extending Visibility to Virtualized and Cloud Environments
NETSCOUT's vStream technology, which Haggerty notes has been available for at least 8 years, addresses visibility in VMware, Azure, AWS, and Kubernetes environments where traditional physical sensors cannot reach. The company worked directly with Microsoft to leverage VTAP capabilities for Azure. In AWS, NETSCOUT integrated with existing traffic mirroring.
Most recently, NETSCOUT introduced the Omnis ClearSight sensor for Kubernetes, which Haggerty describes as "groundbreaking" for customers. The sensor works across service provider and enterprise deployments, public and private clouds, providing consistent visibility regardless of infrastructure type. The technology can also send data from vStream to a local InfiniStream for customers who need additional local visibility and analysis capabilities.
Scaling from Remote Sites to Core Infrastructure
NETSCOUT's portfolio addresses visibility requirements from small remote offices to 100-gigabit data center cores. For remote locations lacking dedicated IT staff, the company offers one-gigabit solutions combining packet analysis with Wi-Fi monitoring and synthetic testing.
The synthetic testing component transforms operations from reactive to proactive. Haggerty shared a compelling example: "The employee walks in, sits down, starts going into his account, wants to get into the network, has to go through the VPN, not a problem. The company has deployed colos for faster access for their remote locations. The employees start trying to log in and they can't get through."
In this scenario, users might blame the VPN or corporate network while calling IT. But with synthetic testing continuously checking VPN availability, IT receives alerts the moment problems occur. "The problem actually started at 2:30 in the morning," Haggerty explains. "If they use our solutions that has the synthetic testing, checking VPN all the time and sending the results up that it's unavailable right now all of a sudden, IT is already working on it at 2:35."
By the time employees arrive for work, IT may have already identified the server problem in the colo with the smart data we collected at the site, contacted the provider, rerouted traffic, or fixed the hardware. "When that employee comes in, they're up and running. They don't know there's a problem because the problem isn't there anymore."
This matters particularly for distributed organizations where downtime translates directly to lost revenue. A credit card processing outage during the holiday shopping season impacts retail locations immediately. Medical clinics unable to access electronic health records cannot provide patient care. Bank branches experiencing network issues cannot process transactions.
Business Value: Time, People, Money, and Risk
At the end of the day, organizations quantify NETSCOUT's value through multiple dimensions that impact and are expressed through things like time savings, productivity improvements, cost avoidance and risk mitigation. Haggerty cites customer examples where troubleshooting time dropped dramatically once teams gained packet-level visibility. One healthcare customer struggled for six weeks with intermittent login delays affecting electronic medical records at remote physician offices. Sometimes login took 10 seconds or more; other times it was very quick. Multiple teams investigated but could not determine why one method was slower than the other since both connected to the same system.
NETSCOUT deployed a remote device to monitor the traffic. Within 20 minutes of watching the traffic and analyzing conversation pairs, the team identified that one form of authentication traversed the network differently than another. "They were able to show how that traveled the network because it had a network perspective with an application viewpoint," Haggerty explains. The application provider then rewrote the code to correct the issue.
Manufacturing facilities provide another clear ROI example. These organizations know exactly how many units produce value per hour. Reducing an outage from one hour to 20 minutes produces immediate, measurable cost savings based on units not produced during downtime.
The broader impact extends beyond individual incidents. Faster problem resolution reduces mean time to knowledge and mean time to resolution, which has people effects, time effects, money effects, and risk effects. In an environment where board-level conversations now focus on infrastructure reliability following high-profile outages affecting major cloud providers and airlines, comprehensive visibility has become a strategic necessity rather than an operational luxury.
Embracing AI: Three Complementary Approaches
NETSCOUT introduced Omnis AI Insights approximately one year ago. The solution curates packet data in ways that can be shared with major partner systems, enhancing their CMDB accuracy and providing faster problem resolution through comprehensive visibility. First, the company feeds high-quality AI-ready packet data is fed into AI platforms from partners including Splunk, ServiceNow, and Palo Alto Networks. Organizations using these platforms find value in resolving problems faster because NETSCOUT provides application-layer visibility often missing from data sources that include MELT telemetry. The network vantage point reveals network errors and issues like DNS problems that affect multiple services simultaneously, helping IT teams understand when seemingly different trouble tickets represent a single underlying issue.
Second, NETSCOUT embeds AI and machine learning across its products and solutions portfolio to enhance cybersecurity, network performance, observability and analytics. The ATLAS Threat Intelligence Feed uses AI/ML to analyze massive volumes of internet traffic in real time to identify emerging threats, attack patterns, and malicious sources and feeds this intelligence back into its products. Adaptive DDoS Protection uses AI/ML algorithms for automatic detection and mitigation of DDoS attacks. And AI/ML techniques are used for network analytics for automated performance monitoring, DPI enhanced observability, insights, SLA violation detection and anomaly detection. The goal is to use AI/ML to reduce risk and make smarter better decisions – faster.
Third, NETSCOUT's product roadmap includes agentic AI capabilities designed to accelerate problem resolution through large language model interfaces. This maps directly to the newer generation of professionals who are accustomed to asking sophisticated questions and rapidly drilling down into issues to get the answers they need.
Deployment Flexibility and Pricing
NETSCOUT offers both subscription and perpetual licensing models, though Haggerty notes that more customers choose perpetual licenses. "It's a purchase and it's a perpetual license for both" hardware and software, she explains. The company strongly encourages MasterCare maintenance and support adoption.
The rationale for widespread MasterCare adoption stems from NETSCOUT's commitment to equipping customers with the latest features. Regardless of whether a release focuses on bug fixes or introduces feature enhancements, customers receive automatic updates. "Every time a new software release comes out, and we put in a new application to support, like one from last summer that was for the broadcast industry, the customer has it automatically. It's on every device. It's not a license you have to buy," Haggerty notes.
NETSCOUT currently supports over 3,000 applications combining well-known applications, custom implementations, industry-specific solutions, and web URLs. As new applications emerge, support gets added automatically across the customer base.
The software pricing is fixed with 50 supported interfaces, and customers then purchase appropriate instrumentation based on their needs. A 100-gigabit deployment naturally costs more than one-gigabit or 10-gigabit models, but the hardware is highly reliable. Haggerty hears stories repeatedly of customers upgrading to 100 gigabits and moving their 10-gigabit units to other locations in the network where they continue operating effectively delivering observability in another critical area of the network.
The company's approach to smaller organizations and remote locations addresses earlier assumptions about affordability. Pay-as-you-grow licensing allows organizations to start with smaller interface licensing options for the management applications and expand as needed. InfiniStream solutions scale from one gigabit to 100 gigabits, with pathways to 400 gigabits.
The Path Forward
As networks continue fragmenting across multiple clouds, edge deployments, and virtualized infrastructure, maintaining consistent visibility becomes increasingly challenging. Organizations that treat visibility as a collection of vendor-provided dashboards will struggle with data quality and correlation issues that slow problem resolution and extend outages.
Packet-based visibility provides a consistent foundation across any network environment. For organizations struggling with inconsistent monitoring data or spending days troubleshooting issues that packet analysis could resolve in minutes, the question becomes how long they can tolerate operational inefficiency and bottom-line risks before addressing fundamental visibility gaps.
Key Takeaways
Modern distributed networks create blind spots in SaaS, UCaaS, cloud, colo, WAN, and remote site environments
Inconsistent data sources using flow records, metrics, and logs with different timestamps and batching intervals extend troubleshooting time significantly
Processing packets at the source provides real-time analysis without network overhead, middleware requirements, or excessive power consumption
Virtualized sensors extend visibility into VMware, Azure, AWS, and Kubernetes environments where physical sensors cannot reach
Proactive synthetic testing shifts operations from reactive problem-solving to prevention, with IT resolving issues before users arrive for work
Business value derives from reduced mean time to resolution measured across time, people, money, and risk dimensions
High Quality AI-Ready Packet data enhances the output quality of AI platforms, while internal AI and machine learning enhance threat intelligence and DDoS mitigation
Perpetual licensing with automatic feature updates across 3,000-plus supported applications eliminates nickel-and-diming customers for new capabilities
Learn More
For detailed information about NETSCOUT's network visibility solutions, visit https://www.netscout.com or connect with Eileen Haggerty on LinkedIn.