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AWS Auto Scaling vs Gigamon Deep Observability Pipeline 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:
 

ROI

Sentiment score
5.1
AWS Auto Scaling optimizes costs and availability, achieving up to 30% savings by right-sizing and reducing unused capacity.
Sentiment score
4.8
Gigamon Deep Observability Pipeline boosts productivity and efficiency through reduced troubleshooting, improved security visibility, and optimized resource management.
 

Customer Service

Sentiment score
5.3
AWS Auto Scaling offers responsive, helpful support with high user ratings, though some desire faster response times.
Sentiment score
5.4
Gigamon Deep Observability Pipeline's technical support is generally praised, though outsourced support presents challenges for some users.
AWS support is very good.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
The technical support by Gigamon Deep Observability Pipeline is good because it has a local architect in my area.
Senior Relationship Banker at Joint stock Commercial Bank for Foreign Trade of V
 

Scalability Issues

Sentiment score
7.9
AWS Auto Scaling is praised for seamless scalability, ease of integration, and handling diverse needs during high traffic.
Sentiment score
6.5
Gigamon Deep Observability Pipeline excels in scalability, especially in cloud environments, accommodating large deployments with ease and flexibility.
Scalability is impressive, as it allowed us to go from 1,000 to 10,000 active users within a week during a traffic spike.
AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)
 

Stability Issues

Sentiment score
6.8
AWS Auto Scaling is reliable with minor issues, earning stability ratings mostly between nine and ten out of ten.
Sentiment score
7.2
Gigamon Deep Observability Pipeline delivers stable, reliable performance in data centers, with high ratings despite minor issues in older systems.
 

Room For Improvement

AWS Auto Scaling needs enhancements in speed, usability, pricing, scalability, security, flexibility, and simplicity for better user experience.
Gigamon Deep Observability Pipeline needs security enhancements, improved GUI, better performance, cloud support, and easier setup and hardware handling.
This complexity led me to migrate to CloudFormation, which simplifies the deployment process.
AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)
If you could add more training on how to use it correctly and on the functions that I haven't used before or some people have not really used before, that would help.
DevOps Engineer Intern at HNG Tech
It requires a downtime before deploying the Auto Scaling group.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
 

Setup Cost

AWS Auto Scaling pricing varies widely, with costs ranging from high to reasonable based on usage and application needs.
Gigamon Deep Observability Pipeline is often seen as expensive, but pricing perceptions vary based on needs and roles.
The pricing of Auto Scaling is medium range, neither high nor low.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
 

Valuable Features

AWS Auto Scaling ensures efficient, flexible scaling with integration, minimal downtime, cost-effectiveness, and enhanced reliability for growing environments.
Gigamon Deep Observability Pipeline improves network visibility, performance, and security through advanced traffic analysis, integration, and process efficiencies.
During peak traffic times, the Auto Scaling group can be deployed to ensure that the client works well, and the traffic remains average.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
The automation aspect where you can automate it to whatever you want is what I value the most about Auto Scaling.
DevOps Engineer Intern at HNG Tech
Its automatic scaling capabilities are very useful.
AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)
The Pipeline's Comprehensive Insights into data flows have helped improve operational efficiency and security.
Senior Relationship Banker at Joint stock Commercial Bank for Foreign Trade of V
 

Categories and Ranking

AWS Auto Scaling
Ranking in Application Performance Monitoring (APM) and Observability
39th
Average Rating
8.8
Reviews Sentiment
6.6
Number of Reviews
22
Ranking in other categories
No ranking in other categories
Gigamon Deep Observability ...
Ranking in Application Performance Monitoring (APM) and Observability
41st
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
9
Ranking in other categories
Event Monitoring (15th), Data Loss Prevention (DLP) (34th), Security Information and Event Management (SIEM) (43rd), Web Application Firewall (WAF) (34th), Advanced Threat Protection (ATP) (25th), Network Packet Broker (NPB) (1st), Network Detection and Response (NDR) (16th)
 

Mindshare comparison

As of July 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.5%, up from 0.2% compared to the previous year. The mindshare of Gigamon Deep Observability Pipeline is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
AWS Auto Scaling0.5%
Gigamon Deep Observability Pipeline0.7%
Other98.8%
Application Performance Monitoring (APM) and Observability
 

Featured Reviews

Ishaka Michael Efe - PeerSpot reviewer
DevOps Engineer Intern at HNG Tech
Automation has simplified traffic management and improved workload efficiency
I'm not really sure what improvements I would want to see in AWS Auto Scaling because I haven't really used it extensively or explored most of it. To the extent that I've used it so far, I think it is very good. I can't really say for certain what should be improved because I haven't really explored it a lot. However, what I've been using it for has been very good. If there could be training for AWS Auto Scaling, that would be fine. If you could add more training on how to use it correctly and on the functions that I haven't used before or some people have not really used before, that would help. If there could be more documentation and training on it, that would be beneficial.
TN
Senior Relationship Banker at Joint stock Commercial Bank for Foreign Trade of V
Experience boosts operational efficiency while performance sees room for improvement
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, Firemon, Gigamon Deep Observability Pipeline, and other solutions. I think it's a good tool, and I am satisfied with it. We have not stored cloud workloads with Gigamon Deep Observability Pipeline yet; we are still on-premises. The technical support takes about one to two hours to respond, which is acceptable. I am satisfied with the scalability of the product. The interface is good.
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Top Industries

By visitors reading reviews
Construction Company
16%
Educational Organization
11%
Financial Services Firm
10%
Comms Service Provider
8%
Financial Services Firm
14%
Computer Software Company
9%
Manufacturing Company
9%
Healthcare Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise2
Large Enterprise12
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
 

Questions from the Community

What is your experience regarding pricing and costs for AWS Auto Scaling?
I'm not sure about the pricing aspect of AWS Auto Scaling or the cost of it.
What needs improvement with AWS Auto Scaling?
AWS Auto Scaling can be improved in many ways, such as providing better visibility into scaling decisions and clarifying why exactly scaling happens. Sometimes, I am not sure why scaling occurs. Ea...
What is your primary use case for AWS Auto Scaling?
My main use case for AWS Auto Scaling is automatically scaling EC2 instances behind a load balancer based on traffic, CPU, and memory usage, as well as custom CloudWatch metrics. I also use it with...
What needs improvement with Gigamon Deep Observability Pipeline?
Gigamon Deep Observability Pipeline needs to improve its performance. I face issues with performance because we use SPAN, and the SPAN traffic is not good. They need to improve their performance.
What is your primary use case for Gigamon Deep Observability Pipeline?
I am working with Gigamon Deep Observability Pipeline and Firemon, and I have been working with it for a year.
What advice do you have for others considering Gigamon Deep Observability Pipeline?
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, F...
 

Also Known As

AWS Auto-Scaling
Gigamon, GigaSecure
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Amica Insurance, College of William & Mary, Gamma, IntercontinentalExchange, OppenheimerFunds
Find out what your peers are saying about AWS Auto Scaling vs. Gigamon Deep Observability Pipeline and other solutions. Updated: June 2026.
902,988 professionals have used our research since 2012.