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 #15 with an average rating of 8.6, while Stackify is ranked #62. Amazon Web Services (AWS) holds a 0.1% mindshare in APM, compared to Stackify’s 0.2% 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 21 AWS Auto Scaling reviews

264 Views
138 Comparison Views

91% willing to recommend

Stackify

Read 6 Stackify reviews

498 Views
351 Comparison Views

71% willing to recommend

AWS Auto Scaling

Stackify

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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: April 2025).

Buyer's Guide

AWS Auto Scaling vs. Stackify

April 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

15th

Average Rating

8.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Stackify

Ranking in Application Performance Monitoring (APM) and Observability

62nd

Average Rating

7.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (57th), Log Management (63rd)

Mindshare comparison

As of April 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.1%, up from 0.1% compared to the previous year. The mindshare of Stackify is 0.2%, down from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability

Featured Reviews

Mbula Mboma

AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)

Boosts deployment efficiency with seamless automatic scaling capabilities

My primary use case for Auto Scaling is mainly to deploy applications at scale Auto Scaling has made the deployment of applications more efficient, allowing us to manage traffic and maintain performance as user counts increase. Auto Scaling is a cool feature that works well and its automatic…

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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 health check integration feature ensures that the instances are healthy and capable of absorbing traffic, thus serving their purpose effectively."

"The most valuable feature is the ability to select a minimum amount of active servers so that a new server automatically launches if one fails."

"The most valuable feature of the solution is that it scales automatically without manual intervention based on the metrics we provide."

"When a lot of traffic comes into our organization, the product scales our instances based on our environment’s requirements."

"I like the graphs provided by the tool."

"It can scale."

"Auto Scaling is a cool feature that works well and its automatic scaling capabilities are very useful."

"The product provides self-healing features."

More AWS Auto Scaling pros

"The deployment is very fast."

"The solution is stable and reliable."

"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."

Cons

"The billing and cost optimization of the solution could be improved."

"The product could add more features for managing instances."

"In comparison to other public clouds, the product is costly."

"It could be cheaper."

"The solution must improve automation."

"It requires a downtime before deploying the Auto Scaling group."

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

"The tool must include AI features."

More AWS Auto Scaling cons

"The search feature could be improved."

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

"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."

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

Pricing and Cost Advice

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

"AWS Auto Scaling is a cheap solution."

"The product has moderate pricing."

"AWS Auto Scaling's price is high."

"The product is expensive."

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

"AWS Auto Scaling is an expensive solution."

"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

Financial Services Firm

20%

Computer Software Company

15%

Manufacturing Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

The pricing of Auto Scaling is medium range, neither high nor low.

See all answers

What needs improvement with AWS Auto Scaling?

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. It requires a downtime ...

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Product Reports

Buyer's Guide

Application Performance Monitoring (APM) and Observability

April 2025

Download AWS Auto Scaling product report

Buyer's Guide

Stackify

March 2025

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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

April 2025

Free Report: AWS Auto Scaling vs. Stackify

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