AWS Auto Scaling vs Stackify comparison

Amazon Web Services (AWS) and Stackify are both solutions in the Application Performance Monitoring (APM) and Observability category. Amazon Web Services (AWS) is ranked #14 with an average rating of 8.7, while Stackify is ranked #61. Amazon Web Services (AWS) holds a 0.4% mindshare in APM, compared to Stackify’s 0.6% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 71% of Stackify users who would recommend it.

AWS Auto Scaling

Read 22 AWS Auto Scaling reviews

802 Views
754 Comparison Views

91% willing to recommend

Stackify

Read 6 Stackify reviews

1,335 Views
734 Comparison Views

71% willing to recommend

AWS Auto Scaling

Stackify

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 24, 2024

Stackify and AWS Auto Scaling are prominent solutions in the cloud management space. AWS Auto Scaling appears to have the upper hand due to its extensive feature set and robust scalability.

Features: Stackify is praised for its intuitive application performance tracking, error monitoring features, and real-time logs and metrics. AWS Auto Scaling is valued for its adaptive scaling based on real-time demand, seamless integration with other AWS services, and automation capabilities.

Room for Improvement: Stackify users suggest enhancements in its integration capabilities and performance lags. AWS Auto Scaling users would like improvements in initial setup complexity and more straightforward user documentation.

Ease of Deployment and Customer Service: Stackify users highlight easy implementation and responsive customer service. AWS Auto Scaling's deployment is complex, requiring more expertise, but has extensive AWS support resources available.

Pricing and ROI: Stackify users appreciate its cost-effectiveness and quick ROI through rapid issue diagnosis and resolution. AWS Auto Scaling users find pricing higher but justify it with the range and power of features for long-term ROI through efficient resource management.

To learn more, read our detailed AWS Auto Scaling vs. Stackify Report (Updated: December 2025).

Buyer's Guide

AWS Auto Scaling vs. Stackify

December 2025

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Review summaries and opinions

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

Categories and Ranking

AWS Auto Scaling

Ranking in Application Performance Monitoring (APM) and Observability

14th

Average Rating

8.8

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Stackify

Ranking in Application Performance Monitoring (APM) and Observability

61st

Average Rating

7.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (59th), Log Management (59th)

Mindshare comparison

As of January 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.4%, up from 0.1% compared to the previous year. The mindshare of Stackify is 0.6%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Market Share Distribution
Product	Market Share (%)
AWS Auto Scaling	0.4%
Stackify	0.6%
Other	99.0%

Application Performance Monitoring (APM) and Observability

Featured Reviews

Ishaka Michael Efe

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.

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Moses Arigbede

Head of DevOps at Partsimony

Easy to set up with great custom dashboards but needs to improve non-.NET infrastructure

They need to improve non-.NET infrastructure. We always had difficulty when it comes to reporting or metrics that come from Linux operating systems and Docker containers. For anything that runs within the Unix environment, we always had problems with them, however, if it was a document-based application, Stackify was 100%, it gave everything. Now, the aggregation agent, the metric agent for Stackify for Linux, collects everything. When I say everything, I mean, everything. It collects so much information that we now started to term it as useless data as all that ingestion will just come in and overwhelm your log retention limit for the month and really this spike up your cost at the end of the month. You'll need to do a lot in order to train down the data coming in from all your Linux environments, to get to what you really need, which actually takes some time as well. I would like to be able to see metrics about individual running containers on the host machines. Stackify has not really gotten that right, as far as I'm concerned. Netdata has done a better job and New Relic has also done a better job. They need to improve on that. We need to be able to see the individual resource usage of containers running within a particular host.

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Quotes from Members

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

Pros

"The tool gives you the flexibility to scale up and grow. The solution is also fast to deploy."

"The solution helps optimize the cost of the AWS environment."

"I would highly recommend Auto Scaling to others because it is a fantastic feature that simplifies scaling processes and makes deployment efficient."

"It is a stable platform."

"It efficiently handles traffic, ensuring we are not running expenses and the infrastructure is strong enough to handle the load."

"The solution's monitoring effectively monitors our application and CPU utilization."

"Our internal business applications are hosted in AWS Auto Scaling."

"AWS Auto Scaling is very good for managing traffic and creating new instances when necessary."

More AWS Auto Scaling pros

"The filter feature on Stackify is one of the features I found valuable. It's awesome. When I want to get the application logs, the solution gives me many filters. For example, if I want to get logs from my test environment, the option is there for me to select the environment from Stackify, and you can also select the particular application, and you'll see the information you need there. The filter feature alone and the fact that Stackify offers a lot of different filters is what I like the most about the solution because I've used other tools with the filter feature, but the filtering was very difficult, versus Stackify that has good filtering. On Stackify, you can filter the information by the last one hour, or the last four hours, and you can also select the date range and specify the timestamp, then the solution will give you the information based on the date range you specified. Another feature I found valuable on Stackify is its rating feature because it tells you how your application is faring. For example, a rating of A means excellent, while a rating of F means very bad, or that your application is not doing well at all. The ratings are from A to F. I also like that Stackify helps you in terms of load management because the solution gives you information on overutilized resources. These are the most valuable features of the solution."

"The performance dashboard and the accurate level of details are beneficial."

"The deployment is very fast."

"The solution is stable and reliable."

Cons

"The tool must include AI features."

"AWS Auto Scaling's documentation could be better."

"The only area of improvement is the speed at which servers are launched. When cleaning up to six servers at a time, it can take up to 15 to 20 minutes to launch new servers."

"The solution's infrastructure scalability and elasticity could be improved."

"The setup can be a bit complex in some situations."

"It is sometimes very critical to deploy on AWS since some servers are already running in the background. There are challenges for employees on how to deploy at a given time."

"Setting up the configuration involves too much work for the cloud engineer."

"We can have more auto scaling algorithms implemented in AWS Auto Scaling."

More AWS Auto Scaling cons

"It should be easily scalable and configurable in different instances."

"I would like to be able to see metrics about individual running containers on the host machines."

"I've not used Stackify for a while, and I'm currently using a solution now that's not as good as Stackify. Among the solutions I've been using so far, Stackify has been one of the best for me, but there's always room for improvement. For example, I don't know if it's just me, but when I try to get the log from Stackify, sometimes it doesn't appear in real-time. It takes a few minutes before the logs appear. When I redeploy my solution and the application starts, I don't see the logs immediately, and it would take two to three minutes before I see the logs. I don't know if other customers have a similar experience. It's the wait time for the logs to appear that's a concern for me, could be improved, and is what the Stackify team should be looking into. In terms of any additional feature that I'd like added to the solution, I'm not sure if Stackify has a way to export logs out. I've been trying to do it. On the solution, you can click on a spiral-like icon and it shows you the entire error, and I'd prefer an export button that would let me download the error and save that into a text file, for example, so it'll be available on my local machine for me to reference it, especially because the log keeps going and as you're using the solution, the system keeps pushing messages on to Stackify, so if I'm looking at a particular error at 12:05 PM, for example, by the time I go back to my system and would like to revisit the error at 12:25 PM, on Stackify, the logs would have gone past that level and I won't see it again which makes it difficult. When you now go back to that timestamp, you don't tend to see it immediately, but if the solution had an export feature for me to save that particular error information on my local machine for reference at a later time, I won't have to go back to Stackify. I just go to that log, specifically to that particular export that I've received on my local machine. I can get it and review it, and it would be easier that way versus me going back to Stackify to find that particular error and request that particular information."

"The search feature could be improved."

Pricing and Cost Advice

"The product is expensive."

"AWS Auto Scaling is a cheap solution."

"The product has moderate pricing."

"AWS Auto Scaling is an expensive solution."

"AWS Auto Scaling's price is high."

"AWS Auto Scaling is a pay-per-use and pay-as-you-use service."

"The pricing is good. I have not had any customers that have complained about the price."

"The price is variable. It depends on how much data we have received in that particular month. Usually, it goes up to $2,000, or, at times, $3,000 USD per month."

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Top Industries

By visitors reading reviews

No data available

Comms Service Provider

11%

Media Company

11%

Performing Arts

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	2
Large Enterprise	11

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	2

Questions from the Community

What do you like most about AWS Auto Scaling?

The tool's most valuable feature is vertical auto-scaling, which is easy to use. However, most companies now prefer horizontal scaling. I set up the health check integration to monitor CPU usage. W...

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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.

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What needs improvement with AWS Auto Scaling?

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Comparisons

Akamai mPulse vs AWS Auto Scaling

Compared 30% of the time

VMware Aria Operations for Applications vs AWS Auto Scaling

Compared 30% of the time

Splunk ITSI (IT Service Intelligence) vs AWS Auto Scaling

Compared 22% of the time

Splunk Enterprise Security vs AWS Auto Scaling

Compared 18% of the time

More AWS Auto Scaling Competitors

New Relic vs Stackify

Compared 14% of the time

Splunk Enterprise Security vs Stackify

Compared 7% of the time

DX Spectrum vs Stackify

Compared 6% of the time

Splunk AppDynamics vs Stackify

Compared 6% of the time

Nagios XI vs Stackify

Compared 6% of the time

More Stackify Competitors

Product Reports

Buyer's Guide

Application Performance Monitoring (APM) and Observability

January 2026

Download AWS Auto Scaling product report

Buyer's Guide

Stackify

January 2026

Download Stackify product report

Also Known As

AWS Auto-Scaling

No data available

Overview

AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Using AWS Auto Scaling, it’s easy to setup application scaling for multiple resources across multiple services in minutes. The service provides a simple, powerful user interface that lets you build scaling plans for resources including Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. AWS Auto Scaling makes scaling simple with recommendations that allow you to optimize performance, costs, or balance between them. If you’re already using Amazon EC2 Auto Scaling to dynamically scale your Amazon EC2 instances, you can now combine it with AWS Auto Scaling to scale additional resources for other AWS services. With AWS Auto Scaling, your applications always have the right resources at the right time.

Amazon Web Services (AWS)

Stackify is an application performance management (APM) solution that combines application performance monitoring with logs, errors, and reporting. It is a SaaS solution that is developer-focused. Users can quickly scan, identify, and repair issues with applications. Stackify APM offers valuable tools, such as Prefix and Retrace, which help to make it a comprehensive and valuable APM solution. Stackify is now part of the Netreo family of IT Infrastructure Management (ITIM), which is considered one of the fastest-growing IT organizations in the marketplace today.

Stackify Prefix

Stackify Prefix helps developers write better code, faster. The tool examines, tests, and approves code as it is being written. Almost every new application is code-perfect, negating the need for exhausting troubleshooting and frustrating time-consuming code review.

Prefix is able to discover poor-performing SQL queries, ORM queries, potential bottlenecks, and concealed exceptions prior to moving the application into production.

Prefix offers Summary Dashboards, intuitive suggestions, integrated logs, and distributed tracing. Distributed tracing expands visibility to cloud-native applications, microservices, and containers and can also provide additional transparency to cache services, web services, third-party services, and more. Users are able to easily move from logs to traces and back.

This valuable tool ensures developers are able to consistently release the best code possible in the least amount of time, while improving performance, productivity, and profitability.

Prefix is a very robust and easy-to-use tool. It can be used seamlessly with Linux, macOS, and Windows. Prefix integrates well with numerous languages, such as Java, Python, Ruby, PHP, Node.js, .Net, and .Net Core.

Stackify Retrace

Stackify Retrace is a user-friendly, trusted APM solution used in more than fifty countries worldwide. Users know that Retrace is able to ensure they can complete quicker, more efficient application development and consistently enhance overall application performance by suggesting important intuitive suggestions users need.

This solution is beneficial to both developers (Dev) and operations (Ops) personnel to learn to improve code and immediately finetune issues by:

Establishing effortless collaboration between Dev and Ops personnel via an easy-to-use GUI dashboard.
Delivering complete transparency of all stages of the application development process, from pre-development to production.
Utilizing performance protocols, such as error tracking, application logs, and code profiling, in real time in order to thoroughly understand how long a code will take to complete various tasks.
Improving overall efficiency and productivity by immediately discovering and repairing application issues.

Retrace Real User Monitoring (RUM) uses both front-end and back-end monitoring to give users a complete picture of what is going on with the applications. This intuitive dashboard displays performance with a complete breakdown of resource usage and integrates the server-side and client traces into one engaging, user-friendly, extensive view.

Retrace is an out-of-the-box solution that works seamlessly with Java stacks, PHP, Node.js, Ruby, Python, .Net, and .Net Core. It is also compatible with many of today’s popular frameworks, such as AWS, Azure, Elasticsearch, MongoDB, MySQL, Oracle, PostgreSQL, Redis, and SQL Server. Additionally, Retrace will work effectively with many cloud providers, containers, and languages, and offers excellent and easy integration with today's favorite tools such as Jira, Slack, Jenkins, and more.

Stackify

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

MyRacePass, ClearSale, Newitts, Carbonite, Boston Software, Children's International, Starkwood Media Group, Fewzion

Buyer's Guide

AWS Auto Scaling vs. Stackify

December 2025

Free Report: AWS Auto Scaling vs. Stackify

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