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Gigamon Deep Observability Pipeline vs Omnipliance comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Customer Service

Sentiment score
10.0
Customer service for Gigamon Deep Observability Pipeline is mixed, with some praising it while others find it lacking in direct assistance.
No sentiment score available
 

Room For Improvement

Sentiment score
4.8
Gigamon needs better security, traffic inspection, improved GUI, increased capacity, better filtering, and easier cloud setup, with faster hardware delivery.
No sentiment score available
 

Scalability Issues

Sentiment score
7.1
Gigamon Deep Observability Pipeline scales well in cloud environments but may face challenges with on-premise scalability and outdated hardware.
No sentiment score available
 

Setup Cost

Sentiment score
7.8
<p>Gigamon Deep Observability Pipeline's pricing is considered high but varies by equipment needs, with competitive alternatives available.</p>
No sentiment score available
 

Stability Issues

Sentiment score
8.1
Users consistently rate Gigamon Deep Observability Pipeline highly for its stability, with minimal issues reported over a year of use.
No sentiment score available
 

Valuable Features

Sentiment score
7.9
Gigamon Deep Observability Pipeline improves firewall performance and enhances network traffic analysis with features like deduplication and encryption.
No sentiment score available
 

Categories and Ranking

Gigamon Deep Observability ...
Ranking in Application Performance Monitoring (APM) and Observability
26th
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
8
Ranking in other categories
Event Monitoring (11th), Data Loss Prevention (DLP) (17th), Security Information and Event Management (SIEM) (28th), Web Application Firewall (WAF) (19th), Advanced Threat Protection (ATP) (22nd), Network Packet Broker (NPB) (1st), Network Detection and Response (NDR) (11th)
Omnipliance
Ranking in Application Performance Monitoring (APM) and Observability
73rd
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
Network Monitoring Software (104th)
 

Featured Reviews

LeonardoAlves - PeerSpot reviewer
Improved the capability to analyze the environment and network problems with easy setup
It improved the capability to analyze the environment and network problems. It also helped streamline your security and performance monitoring The application I use is a script. My environment is a mix of technologies. I have many passionate people in my network who are on a journey in…
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
17%
Manufacturing Company
9%
Government
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Gigamon Deep Observability Pipeline?
The most valuable feature for improving network visibility with Gigamon is the packet filtering capability.
What needs improvement with Gigamon Deep Observability Pipeline?
The challenge is monitoring the cloud network. In on-premises environments, monitoring is straightforward, as I can verify all packets and communications. However, due to the way access tools and p...
What is your primary use case for Gigamon Deep Observability Pipeline?
It improved the capability to analyze the environment and network problems. It also helped streamline your security and performance monitoring.
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Also Known As

Gigamon, GigaSecure
Savvius Omnipliance
 

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Overview

 

Sample Customers

Amica Insurance, College of William & Mary, Gamma, IntercontinentalExchange, OppenheimerFunds
Cisco Systems, Ekahau, HP, IBM, IXIA, Meru Networks, Napatech, NextComputing, Procera Networks, Qualcomm Atheros
Find out what your peers are saying about Datadog, Dynatrace, New Relic and others in Application Performance Monitoring (APM) and Observability. Updated: November 2024.
816,406 professionals have used our research since 2012.