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AWS Auto Scaling vs Coralogix comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 24, 2024

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
4.0
Coralogix streamlines app performance monitoring, enhancing debugging efficiency and integration, reducing NOC staff needs, and boosting productivity.
I have seen a return on investment with Coralogix, particularly in terms of time saved.
Presales Engineer at Crayon AS
I see a return on investment in time saving.
Cloud Engineer at To The New
I have seen a return on investment as it is time-saving for debugging since this costs a lot over a period of time.
Senior DevOps Engineer at a manufacturing company with 501-1,000 employees
 

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
7.0
Coralogix's support is highly praised for responsiveness, effectiveness, and proactive communication, often outperforming competitors like AWS.
AWS support is very good.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
I am satisfied with their response time and overall competence.
Engineering Manager at a tech vendor with 51-200 employees
They are helpful, especially when we created several custom dashboards.
SDE II at Nutanix
They were very responsive and thoroughly communicative.
DevOps at a tech vendor with 201-500 employees
 

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
6.8
Coralogix efficiently scales to meet organizational demands, though some users find the cost of scaling potentially limiting.
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)
We have never faced any scalability issues.
SDE II at Nutanix
Handling scaling with Coralogix is good, as it is easy to scale up or down as my needs change.
Presales Engineer at Crayon AS
I would rate the scalability of Coralogix as easy; it's easy and goes faster.
Fullstag at a tech vendor with 10,001+ employees
 

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
7.9
Coralogix is stable and reliable with minor issues, like Kafka lag, but no significant downtime or performance interruptions.
There are no downtimes, no crashes, or any performance issues that I've noticed since we started using it.
Platform Engineer at a tech vendor with 51-200 employees
High CPU usage on one pod can be averaged out by others, concealing potential issues.
SDE II at Nutanix
 

Room For Improvement

AWS Auto Scaling needs enhancements in speed, usability, pricing, scalability, security, flexibility, and simplicity for better user experience.
Users seek improved interface, documentation, AI enhancements, integration, customization, data handling, notification features, and intuitive design in Coralogix.
This complexity led me to migrate to CloudFormation, which simplifies the deployment process.
AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)
It requires a downtime before deploying the Auto Scaling group.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
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
We require some form of grouping or categorization of logs to identify them better.
SDE II at Nutanix
Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions.
Engineering Manager at a tech vendor with 51-200 employees
If I could improve Coralogix in any way, I would suggest additional customization options for our dashboards.
Platform Engineer at a tech vendor with 51-200 employees
 

Setup Cost

AWS Auto Scaling pricing varies widely, with costs ranging from high to reasonable based on usage and application needs.
Enterprise buyers find Coralogix pricing high but manageable with easy setup, starting at $400 monthly, monitoring is essential.
The pricing of Auto Scaling is medium range, neither high nor low.
AWS Cloud at AeonX Digital Solutions Pvt. Ltd.
Despite the expense, I believe it is worth the money to have Coralogix as a tool.
SDE II at Nutanix
Currently, we are at a very minimal cost, which is around $400 per month since we have reduced our usage.
Engineering Manager at a tech vendor with 51-200 employees
It is charged based on what we store.
Presales Engineer at Crayon AS
 

Valuable Features

AWS Auto Scaling ensures efficient, flexible scaling with integration, minimal downtime, cost-effectiveness, and enhanced reliability for growing environments.
Coralogix excels with its user-friendly interface, AI insights, seamless integration, and flexible, efficient log and error management.
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)
I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible.
Presales Engineer at Crayon AS
Coralogix has positively impacted our organization by providing us with a clearer data flow, which allows us to analyze data better and find errors easier using the smart logs it offers.
Automation Engineer at MyDubai.io
Out of real-time analytics, cost-efficient storage, and AI-powered insights, the most valuable for my team has been the cost-efficient storage.
Software Developer at Styx Global
 

Categories and Ranking

AWS Auto Scaling
Ranking in Application Performance Monitoring (APM) and Observability
25th
Average Rating
8.8
Reviews Sentiment
6.6
Number of Reviews
22
Ranking in other categories
No ranking in other categories
Coralogix
Ranking in Application Performance Monitoring (APM) and Observability
14th
Average Rating
8.4
Reviews Sentiment
6.3
Number of Reviews
20
Ranking in other categories
Log Management (11th), Security Information and Event Management (SIEM) (12th), API Management (11th), Streaming Analytics (13th), Anomaly Detection Tools (2nd), AI Observability (8th)
 

Mindshare comparison

As of May 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.5%, up from 0.1% compared to the previous year. The mindshare of Coralogix is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
Coralogix1.1%
AWS Auto Scaling0.5%
Other98.4%
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.
Naveenkumar Lakshman - PeerSpot reviewer
Presales Engineer at Crayon AS
Centralized monitoring has improved real-time issue tracking and reduced root cause analysis time
One of the best features that Coralogix offers is that it is integration friendly. I can seamlessly work with different cloud providers including AWS, Azure, and GCP. I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible. Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool. I have the interface where I can use the drag-and-drop feature, and I can create different types of charts. Mainly, I have the line charts and time series ones that I generally use in many use cases, gauges, tables, pie charts, or markdown widgets. These are the ones generically available, and I can switch between the visualization types. I am getting the underlying query in that and can import and export dashboards built upon the JSON format. I can have my own APIs integrated with my dashboards as well, such as with Terraform, which is useful for scaling across my environments. Regarding root cause analysis, mainly what I can do is correlate across all of the layers because the main logs that I work on are storage-related, including CIFS, NFS, SAN traffic, and the metrics including storage, throughput, or VM resource usage. Being able to view logs, metrics, or traces available, I get all of these in one place, and I can do root cause analysis much quicker.
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Top Industries

By visitors reading reviews
Construction Company
13%
Financial Services Firm
11%
Educational Organization
8%
Comms Service Provider
8%
Financial Services Firm
11%
Manufacturing Company
8%
Comms Service Provider
8%
Computer Software 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 Business8
Midsize Enterprise7
Large Enterprise10
 

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 is your experience regarding pricing and costs for Coralogix?
My experience with pricing, setup cost, and licensing has been transparent since I am only the engineer using it.
What needs improvement with Coralogix?
Coralogix has many features, but we usually use only these two, and the syntax has not been so straightforward. It was a bit difficult to write specific queries, so I have templates of specific que...
What is your primary use case for Coralogix?
My main use case with Coralogix has been to troubleshoot, narrow down the problem, understand the logs, and identify errors. For troubleshooting or analyzing logs, we usually employ two methods. Th...
 

Also Known As

AWS Auto-Scaling
No data available
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Payoneer, AGS, Monday.com, Capgemini
Find out what your peers are saying about AWS Auto Scaling vs. Coralogix and other solutions. Updated: April 2026.
894,738 professionals have used our research since 2012.