NETSCOUT (VSS) 網路資料分流設備 News


NETSCOUT Delivers Network Data to Big Data Analytics Systems

Big-Data Visibility Solution is Industry's First System to Capture, Groom and Distribute Network Data to Both Network and Application Performance Tools, And Big-Data Analytics Systems.

SAN JOSE, CA, November 19, 2013 - NETSCOUT, a leading provider of network packet brokers (NPBs), today launched the Big Data Visibility solution, a system that closes the visibility gap into corporate data by combining network data with big data from external sources to allow analysis of that data as a single dataset - whether for performance or business intelligence applications, forensics, compliance, or security assurance.
Supplementing real-time, synchronous analysis of data in motion with cost-effective asynchronous analysis of stored data, the Big Data Visibility solution scales analytics and forensics to larger datasets than they could with legacy technology. Furthermore the NETSCOUT’s vMesh? architecture enables organizations to connect hundreds of packet broker nodes and gain real-time views into big data across their entire global network. Because of this unique value proposition, the solution is already supported by an ecosystem of partners including industry-leading companies Corvil, Hitachi Data Systems, LogRhythm, Polystar, Quantea and Riverbed, among others.

The Big Data Visibility solution is built on two new advances in the vMesh Architecture: vSpool and vNetConnect:

• The vSpool hardware module for NETSCOUT’s vBroker chassis enables network data to be captured directly from the network infrastructure, and delivered to and analyzed synchronously or asynchronously by any network analytics, forensics and big data systems over a common storage or content platform.

vNetConnectsoftware enables agent-free visibility into Vmware and Cisco virtual switches, providing visibility into physical and virtual workloads and the associated network traffic without requiring any additional software to be installed on the hypervisor or as a virtual machine.

“There are prodigious volumes of operational and business data available within network packet streams, waiting to be fully leveraged by the fast growing ranks of Big Data analytics solutions,” said Jim Frey, vice president of research, Enterprise Management Associates. “By offering new methods for directly forwarding packet captures into Big Data architectures, NETSCOUT is opening a new door for operational-intelligence solutions. Further, NETSCOUT has added an important extension that can restore visibility into virtualized server environments, where VM-to-VM packet communications can and do occur without ever crossing a physical network wire.”

Brings Visibility to Data in Motion

According to IDC’s 2012 Digital Universe Study, only about 3 percent of the potentially useful data in the digital universe is tagged and even less is analyzed. A significant gap in this missing data is the “data in motion” that is not captured by big data analytics systems. By allowing big-data applications to gain access into these network data alongside other sources of structured or unstructured data, the NETSCOUT Big Data Visibility solution closes this “big data gap” and presents a much richer view of the business’s market and organizational posture.

Big Data applications today largely lack visibility into network data in motion. While specialized network data-capture tools have long been available, those tools can analyze, store and present only that portion of a dataset suited to their purpose. Furthermore, because they are typically used in silos, they cannot effectively scale to the massive data volumes on today’s networks, have a narrow scope, and store data only in proprietary formats. This situation often leads to the use of multiple specialized tools, which increases costs and limit the broader use of the datasets.

“Big data is not just about dealing with the pure scale of data," said Dwight DeClouette, vice president, Communications, Media and Entertainment, Hitachi Data Systems."Service providers and enterprise customers are now looking for more comprehensive and ‘cross-domain’ insights to make informed business decisions. Hitachi Content Platform (HCP) brings to market an unmatched level of capabilities for big data, including search, storage scalability, management and protection. By adding NETSCOUT NPBs powered by vSpool, end users can perform deep analysis on data in motion and gain a new level of visibility and intelligence from their own big data.”

The NETSCOUT Big Data Visibility Solution closes the gap between the network and analytics by deploying a distributed architecture that centralizes access to network data, optimizes storage and enables real-time, interactive and batch analysis. The addition of vNetConnect enables packets from both virtual switches and physical switches to be directed into the network packet broker layer, while vSpool provides capture and delivery of those packets to analytics tools and content platforms from a single point and in an open standard format. The Big Data Visibility Solution enables multiple applications to leverage a single copy of the packaged data, thereby eliminating storage and analytics silos, optimizing and scaling the delivery of these network data:

• Network data is encapsulated in open standard file format that can be directly transported to any (non-network tool) storage appliance or content platform, which do not natively support network packet ingestion. The capture files can be read by many applications.

• These data files are written to disk using open and standard transport protocols onto a commodity storage appliance or content platform in addition to traditional application-specific tools.

The solution makes network traffic available in real time and asynchronously. With additional grooming and packet optimization applied to the capture, only the optimized data and metadata of interest are extracted and ingested by the big data systems.

"Riverbed is committed to providing its customers with a holistic view of data to manage application and network performance,” said Dimitri Vlachos, vice president, marketing and products at Riverbed. “By bringing together the Riverbed Cascade Shark continuous packet capture, analysis and storage appliance with NETSCOUT’s vBrokers powered by vSpool, customers are able to gain a new level of visibility, flexibility and control over their Big Data, resulting in significant ROI and enhanced intelligence about their IT and network infrastructure.”

Supports All Pillars of the Virtualized Data Center: Network, Compute and Storage

Network packet brokers have traditionally focused on solving the visibility problem from the network perspective. Today, scalability and flexibility of network data storage is becoming a critical challenge because of the increase in data volume, variety and velocity. The “stove-pipe” nature of traditional monitoring systems also makes it difficult for organizations to query, retrieve and analyze all the data in a holistic manner. Further, these monitoring systems do not scale effectively to persistent storage systems. The NETSCOUT Big Data Visibility solution brings all three pillars of the virtualized data center together by delivering non-invasive, agent-free visibility into virtualized compute, and providing asynchronous management and control of network data under a single common storage platform.

“Big-data systems are often blind to an invaluable resource: the data that represents every transaction in any networked business,” said Martin Breslin, Founder and President, VSS Monitoring. “Bridging this gap by linking network data with big data systems, enables a comprehensive view of the information that the business needs to make the right decisions. vSpool addresses these challenges by delivering line-rate performance and advanced traffic grooming, while vNetConnect provides total visibility into network traffic from both physical and virtual hosts, and from active and stored data alike. No longer are variations in data types, interfaces between systems, network latency, or physical locations of network assets a limitation to high-quality analysis.” In addition, the “tool consolidation” and the use of commodity hardware made possible by vSpool allow for cost-effective scaling of network analytics and forensics, added Breslin.