NetScout Vs. ExtraHop: Best Network Performance Monitoring Tool

Network performance monitoring (NPM) tools like NetScout and ExtraHop provide invaluable visibility into network infrastructure and application performance. With digital transformation accelerating, complex hybrid network environments are the new normal. NPM tools help IT teams monitor, analyze and troubleshoot performance issues across on-prem, cloud, and hybrid networks.

Both NetScout and ExtraHop offer advanced NPM capabilities leveraging real-time traffic analysis and machine learning algorithms. However, there are some key differences between the two solutions.

This article provides a detailed comparison of NetScout and ExtraHop, examining their architecture, features, analytics, scalability, and total cost of ownership.

A Brief Comparison Table

Feature	NetScout	ExtraHop
Architecture	Appliance-based	Cloud-native software
IT Ops Monitoring	Excellent	Very good
Security Analytics	Good	Excellent
Scalability	Requires additional appliances	Linear cloud scale
Machine Learning	Minimal	Extensive
Ease of Use	Moderate	Very easy
Total Cost	Higher CapEx	Lower OpEx

Overview Of NetScout

NetScout delivers smart data technology that helps enterprises manage performance, assure digital transformation, and secure networks. Their solutions provide real-time visibility into service, network, and application performance.

Some key aspects of NetScout’s NPM offering:

• Packet-flow technology: NetScout’s smart data technology is based on packet flow, which provides real-time visibility into all conversations on the network. This helps monitor infrastructure and app performance.
• nGeniusONE platform: The vendor’s nGeniusONE platform consolidates monitoring data, analyses it using smart analytics, and provides actionable intelligence.
• Synthetic testing: NetScout offers active testing capabilities to proactively monitor the user experience.
• On-prem and software form factors: NetScout is offered as physical on-prem appliances as well as virtualized software models like Vs.TREAM.
• Network forensics: Long-term packet capture and analysis helps reconstruct network events and security threats.

NetScout is especially known for its signature Adaptive Service Intelligence (ASI) technology that provides contextual analysis of interdependencies across applications, networks, and users.

Overview Of ExtraHop

ExtraHop delivers cloud-native network detection and response (NDR) designed for hybrid environments. Their solutions provide complete visibility and threat detection across network, cloud, and security infrastructure.

Some key aspects of ExtraHop’s NPM offering:

• Real-time stream processing: ExtraHop perform wire data analytics in real time using stream processing technology like Apache Kafka.
• Machine learning for IT Ops: The vendor applies unsupervised ML techniques for baselining, anomaly detection, and automated investigation.
• Cloud-native architecture: ExtraHop was born in the cloud and offers a fundamentally different architecture optimized for scalability.
• Decryption capabilities: ExtraHop can decrypt traffic from SSL/TLS, IPSec, and other protocols to analyze encryped traffic.
• EDR security analytics: ExtraHop Reveal(x) performs continuous packet capture for forensic investigation and threat hunting.

A key differentiator for ExtraHop is applying cloud-scale stream processing and machine learning to unlock advanced NPM use cases spanning IT operations, security, and business analytics.

Architecture Comparison

The underlying architecture of NetScout and ExtraHop solutions differ significantly:

NetScout

• Physical and virtual appliance-based
• Distributed session-based processing
• Centralized management and analytics
• Retains packet data for historical analysis

ExtraHop

• Purely software-based, cloud-native
• Centralized stream processing pipeline
• Inline decryption of traffic
• Machine learning models for advanced analytics
• Ephemeral packet data not stored long-term

NetScout utilizes a distributed architecture of physical or virtual appliances that process packets and generate session-based metrics. Management, reporting, and analytics are conducted centrally.

In contrast, ExtraHop is built as a scalable stream processing pipeline that analyzes packets in flight. All data is processed centrally in the cloud for real-time analytics and machine learning.

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Analytics And Visibility

Both vendors provide insightful analytics and comprehensive visibility into network and application performance. Here’s an overview:

NetScout

• 360-degree views of network and app performance
• Service dashboard roll-ups
• Adaptive Service Intelligence (ASI)
• Traffic flow analysis
• Session-based KPIs
• GTP correlation for mobile infrastructure

ExtraHop

• Machine learning-driven analytics
• Customizable metrics and dashboards
• Application dependency mapping
• L2-L7 decodes and protocols
• Device discovery and fingerprinting
• Cloud infrastructure visibility

NetScout offers very granular packet-flow based analytics that help reconstruct application flows, transactions, and communications. The vendor’s unique ASI technology provides deep app and network interdependency mapping.

ExtraHop focuses more on applying machine learning techniques to automatically detect anomalies, identify performance issues, and analyze security threats. The platform also provides flexibility to customize metrics and dashboards.

Both tools provide comprehensive L2-L7 visibility across on-prem, virtualized, cloud, and container environments. ExtraHop emphasizes cloud-infrastructure monitoring capabilities.

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Scalability And Performance

Given their different architectures, the scalability profile of NetScout and ExtraHop also diverges:

NetScout

• Physical appliances from 1Gbps to 100Gbps
• Virtual appliances scale up to 10Gbps
• Clustering appliances improves performance
• Capacity planning required upfront

ExtraHop

• Cloud-based architecture with unlimited scalability
• Single platform supports up to 100Gbps
• Right-sized on demand based on data rate
• No capacity planning needed

NetScout’s appliance-based design requires more upfront planning and sizing. The deployment is scaled by adding additional physical or virtual appliances. Larger appliances can support 20Gbps or more of throughput.

ExtraHop’s cloud-native architecture enables linear scalability to monitor ultra-high data rates across a single unified platform. The system can auto-scale dynamically based on data ingest.

This means ExtraHop can more easily scale on demand to handle new data sources, environments, and increasing network speeds.

Total Cost Of Ownership

Both NetScout and ExtraHop aim to improve ROI by optimizing network and application performance. But the total cost of ownership profiles differ:

NetScout

• Physical appliances have higher capital costs
• Software models available, but still appliance-based
• Scaling requires additional appliance purchases
• Maintenance and overhead of managing appliances

ExtraHop

• Entirely software-based, no hardware required
• Subscription-pricing scales with usage
• Automated provisioning streamlines deployment
• No maintenance or overhead costs

Due to its physical appliance architecture, NetScout entails greater capital expenditure upfront as well as ongoing management overhead.

ExtraHop’s cloud delivery model provides consumption-based pricing that flexes with usage. The software-only approach minimizes deployment costs and maintenance overhead.

Over the long term, ExtraHop’s pure SaaS model typically reduces TCO by 50% or more compared to legacy NPM tools. The OpEx-oriented pricing also makes costs more predictable.

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Use Cases And Integrations

Both NetScout and ExtraHop support a diverse range of use cases:

Common Use Cases

• Network and application performance monitoring
• Troubleshooting slowdowns and outages
• Diagnosing network and app latency
• Voice/video quality monitoring
• Assessing user experience
• Monitoring branch office networks
• Capacity planning and optimization

Advanced Use Cases

• Network security analytics
• Threat detection and response
• Malware and insider threat analysis
• Micro-segmentation validation
• Regulatory compliance
• Business analytics

For traditional NPM scenarios, the platforms have roughly parity in core features and use case support. NetScout provides deeper insights for large-scale communication networks thanks to capabilities like GTP correlation.

ExtraHop excels at expanding into adjacent use cases like security analytics, IoT monitoring, and business intelligence. The vendor’s machine learning expertise broadens the solution’s applicability.

Both vendors offer extensive integrations with IT infrastructure and management tools. Examples include Splunk, ServiceNow, AppDynamics, Dynatrace, and dozens more.

Frequently Asked Questions (FAQ)

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Conclusion

Both offerings provide robust network and application monitoring capabilities. NetScout stands out for packet-flow analysis and service dashboarding. ExtraHop differentiates with cloud scalability, machine learning, and expanded use cases.

Ultimately, ExtraHop’s cloud-native architecture and machine learning analytics provide greater long-term value, especially for modern hybrid environments. But NetScout remains a powerful option for traditional on-prem NPM deployments.

In summary, NetScout offers robust network performance management via appliance-based monitoring. ExtraHop provides cloud-scale monitoring and advanced machine learning for expanded use cases. ExtraHop’s cloud delivery model reduces TCO compared to NetScout’s hardware approach.